Notice

Until I finish recovering from surgery I will be posting less frequently than normal. I hope to be back to my normal "schedule" by the end of the month.

Finalizing & Implementing Your Personal Strategic Plan

DRAFT

Here are some preliminary thoughts re finalizing and implementing your personal strategic plan.

Create SMART Goals and Strategies

Make your goals and strategies SMART: Stretching, Measurable, Achievable, Relevant, and Time-bound. (Note: There are many variations of what SMART means, but all are similar. See, e.g., Wikipedia).

Additional Thoughts re Creating Personal Goals and Strategies

If you're having trouble organizing your SWOTs, here are some additional ways to organize SWOTs within a dream to arrive at goals, or within a "goal clump" to arrive at strategies:

• By major outcome: For example, for your health dream 2 big goals/ major outcomes might be to lose 30 pounds, and to lower cholesterol to 200 or less.
  
• Chronologically: But group the SWOTs by major milestone, not every single step. Some special cases of chronological sequence are:
  
• Study, plan, do.
  
• Analyze, design, construct, test, implement, monitor/maintain.

Avoid Analysis Paralysis

Don't try to create a perfect plan -- especially if it's your first one. If you're comfortable that you have a plan that will help you, go with it.

Focus Your Plan

If it's your first one, keep it simple and focused. Don't spread yourself too thin. Initially, try to limit yourself to at most 3 dreams, picking one as your priority, until you've had some successes.

Create a summary version of your plan to help you focus; it should be no more than one page. Typically, my summary plan includes only my dreams and goals -- though on occasion I may include some critical strategies as well. The "outline view" within Microsoft Word is ideal for this purpose since it allows you to hide the lower levels of your outline (click "View" - "Outline"). If you prefer something less "dry," consider using "mind mapping" software such as Mindjet (but also see the Dream Board discussion below).

Have a copy of this one page version of your plan in view to automatically remind you of your plan every day -- for example, on the refrigerator, on the bathroom mirror, or in a picture frame by your bedside.

Use a Dream Board to Keep Your Dreams in Mind

Another good tool for reminding you of your dreams, especially if you are more visual, is a Dream Board. The idea is to create a collage of pictures of your dreams -- pictures that evoke the feelings you will have when you achieve your dreams. This can be a very powerful tool. You want at least one picture for each dream. You can include pictures for your major goals as well.

In the old days, the primary source of pictures for your dream board was magazines. Now, images are easier to find on the internet (e.g., using Google Images). I use a mixture of both. The advantage of magazine pictures is that they tend to be higher quality. Equally important, it takes longer to find pictures in magazines; that means you spend more time searching -- and more time thinking about and visualizing your dreams.

Some people mount their pictures on poster boards. I've even heard of people who use a whole wall! I like to use 18" x24", or larger, poster frames. That way it's easier to replace a picture with another picture that captures my dream even better -- and, it gives me a reason to think about my dreams all year long as I search for more and more effective pictures. (Target has some inexpensive poster frames that work well.)

Spending a few minutes a day viewing your Dream Board can be a very powerful reminder and motivator. For a more in-depth discussion of Dream Boards see this post.

Success Requires Action

The plan is just your roadmap, you still have to make the journey. Remember, a plan is only part of the reason why people are successful. You still need HARD WORK. There are no magic bullets. To help you transition from planning to action I suggest you consider weekly and daily to-do lists.

Monitor Your Progress

Review your progress at least once a month. Are you happy with your progress? If not, what can you do to improve your performance?

Keep Your Plan Evergreen

Update and revise your plan yearly; typically, most of the changes will be at the strategy level rather than at the goal or dream level. Re-do your plan from scratch (i.e., rethinking dreams and SWOTs) as you approach the end of the planning period (e.g., 5 years), or if there is a major change in your life in the interim, such as those mentioned in Do You Need a Personal Strategic Plan?

Note:

I'm still a little under the weather, recovering from minor surgery a couple of weeks ago. I'm still having trouble putting thoughts together. I wanted to get at least a draft of this post up this week for those of you who are developing plans. I'll finalize this post as soon as I can think straight. Meanwhile, if you'll let me know what problems you're having developing and implementing your plan I'll address those in a future post.

Previous Posts In This Series:

Do You Need a Personal Strategic Plan?
A Sample Personal Strategic Plan
Discovering Your Vision
Developing Strengths, Weaknesses, Opportunities & Threats (SWOTs)
Creating Your Personal Strategic Plan

The picture is from Public Domain Pictures.

Last updated 7/10/2009

This work is licensed under a Creative Commons Attribution 3.0 unported license.

Stock Market Normalized Earnings and Returns

Cyclical Stock Market Returns

In the most recent stock market post, we looked at 10 Year Rolling Returns vs. the normalized P/E Ratio in an attempt to discover what was causing the very regular stock market cycles that we first observed in the 10 Year Rolling Returns post. The graph provided clear visual evidence of both the the cyclicality of (normalized) P/E ratios and the impact of those ratios on future returns. More specifically, it was clear that, as a general rule, investors who bought when the normalized P/E ratio was high experienced low 10-year returns; on the other hand, investors who bought when the normalized P/E ratio was low experienced high 10-year returns. (If you are not familiar with normalized earnings and P/E Ratios, see this post for a more detailed discussion.)

Stock Market Earnings

I think over the long run earnings are a more important determinant of stock market performance than price/earnings ratios. Therefore, it seemed reasonable to ask to what extent, if any, earnings contributed to the cyclicality that we observed in returns.

Over the long run, earnings can continue to go up indefinitely -- the P/E ratio cannot. The second chart in the Dow P/E Ratios since 1929 post shows that while the normalized P/E ratio has gone up and down, normalized earnings appear to have gone steadily upward. It turns out, that chart is somewhat misleading -- to me anyway. The increase in normalized earnings is not as steady as it appears in that chart.

Dow 10-Year Normalized Earnings Growth Rate

In the above chart (click to enlarge) the dotted line shows the same normalized earnings (NE) as in the P/E Ratios since 1929 post, again using a log scale. (For a discussion of log scale, see this post.) In addition, I've added a solid line showing the normalized earnings 10-year annualized growth rate. Each point on the line plots the growth rate of NE over the following 10 years. For example, the last point on the line is 1993, with a value of approximately 6.4%. That 6.4% represents the annual percent increase in Dow normalized earnings from $237 in 1993 to $443 10 years later.

Now we can see that there is ebb and flow to the NE growth rate; it increases sharply for a while, then tends to drift downward. As a result, earnings are another potential source of the cyclicality that we observed in rolling 10-year stock market returns.

Dow 10-Year Earnings Growth Rate vs Returns

In the chart above (click to expand), the 10-year growth in normalized earnings is plotted against the 10-year growth in the stock market. Coincidentally, both series peak in 1988. The 10-year normalized earnings growth rate peaks at 10.9%, and the 10-year stock market annual return peaks at 18.6%. However, that is the only year where the peaks correspond. For some periods, increasing earnings growth seems to precede increasing stock market returns; in other periods, the sequence is reversed. In short, the relationship between 10-year earnings growth rate and 10-year returns is not as clear cut as I hoped it would be. I guess I would call it "suggestive" -- but you can draw your own conclusion.

Bottom line: For now, I think the clearest "view" of the impact of earnings on returns is still through the Historical Analysis tab of my Stock Market Analysis Model.

Related Posts:

Rolling Returns vs. P/E Ratio
For a list of all stock market posts, by subject area, click here.

This work is licensed under a Creative Commons Attribution 3.0 unported license.

About P/E, Normalized Earnings and Normalized P/E Ratios

Valuation

How do you decide whether something is cheap or expensive? Often, you will look at the price per unit. If you are buying bananas, it's the price/pound; for homes, price/square foot; for perfume, price/ounce; and so forth.

When you buy a share of stock, you are buying a portion of a company. As a result, you own a portion of its earnings. Therefore, valuation is often measured by the price you are paying for each dollar of earnings -- that is, by the price/earnings (P/E) ratio. To calculate the ratio, you divide the price of a company's stock by that company's earnings for one year. If the result is, say, 17, your broker might tell you Company X has a P/E of 17, or Company X is selling at 17 times earnings. The P/E is also referred to as the earnings multiple.

Similarly, since you are also buying a portion of the company's dividends, valuation is sometimes measured by the price/dividend ratio -- i.e., how much you are paying for each dollar of dividends. Other methods of valuation include price/cash flow and price/book value (the accounting, or "book," value of the company's assets).

Normalized Earnings (NE)

When calculating the P/E ratio, it's relatively easy to determine the "price." But, what earnings should you use? The most recent calendar year? The most recent four quarters? The next calendar year? The next four quarters? If you use any of these earnings, you will find that the P/E can vary significantly in a relatively short span of time. More importantly, if you are using earnings to determine the price you are willing to pay, that measure of "worth" will also vary significantly. Investors who are investing for the long term look for more stable/consistent measures of earnings (and worth). Often, they will "normalize" earnings so that the earnings appear less volatile. I think of this as an attempt to estimate "sustainable" earnings.

In this blog, I normalize earnings by averaging the earnings over an 11-year period -- from 5 years before through 5 years after. (See, for example, the graph of normalized earnings since 1929 in this post.) Other methods for normalizing earnings include using the prior 10 years' earnings, and using peak earnings. I often abbreviate normalized earnings as NE.

Normalize Price/Earnings Ratios (NPE)

An important reason for normalizing earnings is so that you can calculate a normalized price/earnings ratio. If you use yearly earnings, the resulting P/E varies more than seems intuitively reasonable. This volatility can be dampened by using a normalized P/E. The normalized P/E is calculated by dividing price by normalized earnings. I often abbreviate this as NPE.

Dow Jones NPE

In this blog I treat the DJIA (Dow Jones Industrial Average) as though it were one big company. Therefore, the price I use is the closing price of the Dow; earnings (before I normalize them) are the sum of the earnings of all 30 Dow component companies for that year. The Dow normalized P/E ratio (NPE) is, then, the closing price divided by normalized earnings, and is an indication of how cheap or expensive the Dow is at that time. For an example, see the graphs of normalized P/E ratios in Dow P/E Ratios since 1929.

Last modified 6/18/2009
This work is licensed under a Creative Commons Attribution 3.0 unported license.

The 10 Best NBA Players Ever

Who Were the Greatest NBA (National Basketball Association) Players of All-Time?

In my last basketball post, I looked at "Total" Production per-Minute -- a rough measure that I use to evaluate the performance of the players on "my" team, the Houston Rockets. At the time, the Rockets were battling the Lakers for the right to go to the NBA Western Conference Finals, so I threw Kobe Bryant into the mix to see how our best player, Yao Ming, compared to the Lakers' best player. Kobe won.

But, that got me thinking.... Using this measure, who were the best NBA players ever? Who were the best of the best, the greatest of the many great NBA players I have seen over the past more-than-half-century? The table below shows you how it came out (click to expand).

Top 10 NBA Players All-Time?

First, let me remind you, who's "best" depends on your evaluation criteria. These are not the only possible criteria. What this methodology has going for it is: a) it's simple, b) the components are all important, and c) the components are all readily available -- even for most of the old-timers.

Primarily, I'm measuring offensive productivity -- not who is the most skilled player, or the best in the clutch, or the most exciting to watch, or .... The most obvious deficiency of the methodology is that it doesn't adequately measure a player's defensive contribution. That's the case partly because defense is difficult to measure, and partly because the few measures that we currently have did not exist in the old days. Therefore, if I included defensive stats I wouldn't have the data for the older players, and would have to exclude them. Bottom line: In effect, I'm assuming all the players were roughly equal on the defensive end.

I like to look at stats on a production per minute or production per 40 minutes basis for reasons that I explained in Houston Rockets Production per-Minute. However, since most people aren't used to thinking in those terms, I've included the per game stats as well so that you can get the full impact of how extraordinary these players were.

Note that I've ranked the players based only on their "best" season. For these purposes, I prefer that to career averages. However, their best three years or so might be a better gauge.

Miscellaneous Observations

These results make intuitive sense to me. These are 10 true NBA superstars. I might quibble about some of the rankings within the top 10, but overall I think it's a pretty good top 10. Some other notes:

• Wilt's dominance is astounding. There's nobody close. And, if you added defensive stats, it would make his production even more dominant!
  
• The biggest surprise to me was Bob Pettit. I remember him as being an excellent player (that I didn't like), but not as productive as he really was.
  
• I thought the Big O (Oscar Robertson) would rank even higher. As far as I can tell, he was the only player to ever average a triple double for a whole season!
  
• I think it's instructive that not one member of the Celtic dynasty teams is in the top 10. One reason I was such a huge Celtic fan in those days was because they were such a great TEAM.

Some Other NBA Superstars

Here are some NBA super stars that you may be surprised did not make this list.

• George Mikan: He probably belongs in the top 10. He played so long ago that I can't even get rebounding stats for his early years. More importantly, his best years were before the NBA implemented the 24-second clock for the 1954-55 season. In 1950, his team lost a game 19-18! This methodology does not adequately measure his contribution in games like that. The first year that I have rebounding stats for is 1950-51 -- midway through his career. His best season that I have complete stats for was 1951-52; his per game stats that season were 23.8 PPG, 13.5 RPG and 3.0 APG -- with no shot clock.
  
• Julius Erving: The problem here is how to handle Dr. J's ABA years. If you include the ABA years, he comes in 8th overall with a 1.17/minute (47/40 minute) contribution in 1975-76. That year, his per game stats were 29.3 PPG, 11 RPG and 5 APG.
  
• Charles Barkley: There is a whole generation that thinks of Chuck as an announcer. However, the "Round Mound of Rebound" had some awfully good years. His best score was 1.14/minute (45.6/40 min) in 1992-93 -- just outside the top 10. That season he averaged 25.6 PPG, 12.2 RPG and 5.1 APG.
  
• Jerry West: Excellent player, and the model for the NBA logo -- but didn't make the cut. Best year was 1965-66 with 1.09/minute (43.7/40 minute) contribution. That year his per game stats were 31.3 PPG, 7.1 RPG, 6.1 APG.
  
• Kobe Bryant: Great player, but didn't make the list. His best year was 2005-06 with a contribution of 1.1/minute (44.2/40 minutes).

Full disclosure. It may surprise you to know that I have not done this analysis for every single player that ever played in the NBA. I started with players I remember as being extraorinary, and used The 50 Greatest Players in NBA History to add additional candidates. I haven't calculated the results for all, but have for many recent stars including, for example, Dwight Howard, Carmelo Anthony, Kevin Garnett, Tim Duncan, Dirk Nowitzki, Allen Iverson, Vince Carter, Dwyane Wade, Amare Stoudemire. I've also run the numbers for older players such as Bill Russell, Karl Malone, George Gervin, Bill Walton, Bob Cousy, David Robinson, and, of course, all the old Rockets stars.

Related Material:

My data sources are NBA.Com and Basketball-Reference.com.
Here's another guy's take, using different criteria.

Last modified 6/5/2009
This work is licensed under a Creative Commons Attribution 3.0 unported license.

Creating A Personal Strategic Plan

Creating Your Personal Strategic Plan

This post will help you create the document that could change your life -- your first personal strategic plan! You've already described your dream/ideal future; your SWOTs have documented the obstacles that must be overcome to realize that dream, and the skills & resources you possess to overcome those obstacles. Now it's time to analyze your SWOTs and create a roadmap to the future you've dreamed of.

Note: This is one of a series of posts on personal strategic planning; the first is Do You Need a Personal Strategic Plan?

Your completed plan will be an indented outline of dreams-goals-strategies. It will contain all of the critical goals that you need to achieve in order to realize your dreams. Not only that, it will remind you of the steps you need to take in order to achieve each goal -- what you need to start and stop doing, and by when. Finally, it will make clear why you need to take each step by linking each step to a goal and a dream. For example, you need to track all your expenditures for one month (strategy), so that you can develop an annual budget that saves 10% of your salary (goal), so that you can have a sound long-term strategy for managing your financial affairs and retiring with $1,000,000 (dream). (See A Sample Personal Strategic Plan for additional examples.)

SWOT Analysis

To get started, organize your SWOTs into groups, starting with one group for each of your dreams. (Note: see Developing Your SWOTs for a more detailed discussion of SWOTs.) Index cards are handy for this. Or, you can use a spreadsheet, as I do; this will also allow you to easily handle SWOTs that are relevant to more than one dream. Add additional groups as needed.

Setting Personal Goals

For each of your dreams, you want to identify the 3-5 major goals that are the keys in that area. These should be challenging, yet feasible, goals that, when accomplished, will make that dream a reality! You are creating a multi-year plan, not a to-do list. Therefore, typically, your goals should only include major milestones, or goals that will continue to be relevant for most or all of the planning period.

There are two ways to go about this -- top-down, and bottom-up. I recommend you use both methods, starting with the method that feels right to you.

Creating Personal Goals "Bottom-Up"

This approach to creating goals is "bottom-up" since it starts with your SWOTs. SWOTs for a dream will sometimes fall naturally into smaller, related clumps. Let's call these "goal clumps." For example, your financial dream might include a goal clump consisting of SWOTs such as: I spend too much eating out; I have no savings; I don't know where my money goes; I make a good salary; I'm behind on my credit cards; I'm living paycheck to paycheck; etc.

The idea is to create a goal that, when reached, overcomes these obstacles (weaknesses and threats) and takes advantage of your strengths and opportunities. In this case, you might create a goal such as "Develop and implement an annual budget."

Creating Personal Goals "Top-Down"

The "top-down" approach starts with your dream. What are the most critical goals you need to accomplish in order to realize this dream? This approach will be especially useful when you naturally envision a sequence of goals that you must reach in order to make the dream a reality. For example, if one of your dreams is to start a new business, one of your early goals might be "Develop business plan."

If you create your goals top-down, follow up with a bottom-up approach using your SWOTs to flesh them out and clarify what reaching each goal will entail. If you create your goals bottom-up, follow up with a top-down, "big picture," approach to make sure that you've covered all the important goals.

As you are writing goals, continue to refine the dream/vision you drafted initially. Often this will mean making it broader. For instance, a financial dream of "get out of debt" might become "I will have my finances under control."

Creating Strategies

For your most important dreams, typically the ones that have a lot of SWOTs, you will want to repeat the process and divide the "goal clumps" you've created into sub-clumps in order to drive your plan down an additional level. Let's call these "strategy sub-clumps." Identify approximately 3-7 strategies for each of the more complicated goals following the same process as above -- just for a smaller area. Do this both bottom-up and top-down, just as you did with the goals.

Conclusion

When you are through, you will have a roadmap to your ideal future. However, just as a vision is only a dream without a plan, a plan is only a possibility until you implement it. The plan is just your roadmap -- it's not the journey. But, it is a critical first step. And, as Confucius say, "A journey of a thousand miles starts with a single step." Good luck on your journey!

For some additional thoughts on finalizing and implementing your strategic plan, see the next post in this series.

Previous Posts In This Series:

Do You Need a Personal Strategic Plan?
A Sample Personal Strategic Plan
Discovering Your Vision
Developing Strengths, Weaknesses, Opportunities & Threats (SWOTs)

The picture is from Public Domain Pictures.

Last modified 7/6/2009

Stock Market Rolling Returns vs. Price to Earnings (P/E) Ratio Graphs

In this post, we are going to continue our investigation of stock market rolling returns. In previous posts, we have looked at the range of stock market returns over periods of from one to 100 years, and drilled down to look at "rolling" returns from two to 50 years. The rolling returns series was fascinating, to me anyway, because I was surprised by the cyclicality -- especially by the regularity of the 10-year rolling returns cyclicality. In addition, I expected the cyclicality to wash out by the time we got to 50-year rolling returns. It did not.

The obvious question is what is causing the cyclicality?

Stock Market 10-Year Rolling Returns vs. Price-to-Earnings (P/E) Ratio Graph

Above is a graph (click to expand) of the 10-year total return of the DJIA (Dow Jones Industrial Average) compared to the normalized P/E ratio. If there is a chart that I find even more fascinating than the 10-year rolling returns chart, it's this one. Each point on the rolling return graph represents the average annual return earned by an investor who bought the Dow at that year-end and sold 10 years later, reinvesting dividends in the interim. For example, the first point on the graph shows that an investor who bought at year-end 1901, reinvested dividends annually, and sold at year-end 1911 earned 7.9% per year.

The dotted line is the normalized price/earnings ratio (NPE) at the time of purchase. The NPE in 1901 was 15.6. This is calculated as the Dow price divided by the average earnings from 1896 through 1906. The earnings in the years prior to 1929 have been estimated. (Note: For a more detailed discussion of NPE, see About Normalized P/E Ratios.)

Implications of Normalized Price-to-Earnings Ratio on Future Returns

It certainly appears that the 10-year return graph is very close to a mirror image of the normalized price-to-earnings graph. That is, when NPE goes up, returns tend to go down -- and vice versa. To the extent that is true, the message would be that the normalized P/E ratio (NPE) at time of purchase is the major determinant of 10-year returns. More specifically, Dow history shows high initial NPEs are associated with below average future returns; low initial NPEs are associated with above average future returns.

For example, the highest NPE (32.8) was in 1928, and so was the lowest 10-year return. That 10-year return, -1.3%, was the only negative 10-year return in our database -- so far. You might be interested to know that the third highest NPE (28.0) was in 1999. It doesn't show on the chart since the jury is still out; we won't know how buying in 1999 worked out until the end of 2009. (Note: To get a feel for the dollar impact of high vs low NPE investing, see the graph in this post.)

Stock Market 20-Year Rolling Returns vs. P/E Ratio Graph

Above is the same chart as before (click to expand), but for rolling 20-year returns -- just to show that the first one isn't a fluke. I'm not including the 5 and 50-year charts. However, they convey the same basic message.

Comments

This may be the clearest visual evidence so far of the impact of valuation (P/E) on stock market performance. However, see The Extraordinary Impact of P/E Ratios for a different graphic representation of this same phenomenon, and also for a method for quantifying the impact of multiple expansion/contraction.

For some reason, these charts make the cyclicality of valuation (P/E ratios) more obvious to me than the Dow P/E Ratios since 1929 graph did. Looking back at that chart, the cyclicality is clearly there, but, at the time, I guess I was more impressed by the range of valuations.

I'll continue this anlalysis in a future post.


Note: The above charts are based on DJIA (Dow Jones Industrial Average) data from my Stock Market Analysis Model. Results would be essentially the same if we used S&P 500 data.

Related Posts

For an index of all stock market posts, by subject area, click here.

Last modified 6/20/2009

A Sample Personal Strategic Plan

Are you less than thrilled with your financial status, career or personal life? Do you dream of a better life? Just imagine if you could make those dreams come true. The most successful people make their dreams come true; they not only have a dream, they have a personal strategic plan.

Personal Strategic Plan Example

In this post, I will sketch out an example of a plan to give you at least a general idea of what your completed plan might look like. That will make it easier for you to understand the purpose of each step in the planning process. (Note: for a more detailed introduction to strategic planning, see Do You Need a Personal Strategic Plan?)

Personal Strategic Planning Starts with Your Dreams

Let's assume that as you dream about the future you'd like to create 5 years from now, you decide that three of your important dreams are:

• I will have a sound, long-term strategy for managing my financial affairs, have my finances under control, and be on track to have $1,000,000 when I retire!
  
• I will have a healthy life-style, striving for the presence of good health -- not just the absence of sickness and disease.
  
• I will be a Group Project Manager for my current company or a company in a similar industry.

Remember, this is just an example. Your actual plan might well include more than three dreams (e.g., what about family? friends? fun? etc.). You might even have an overriding "life vision." (For more detail on this part of the planning process, see Discovering Your Vision.)

Sample Personal Goals

After developing and analyzing a list of your strengths, weaknesses, opportunities and threats (SWOTs), you begin setting personal goals that you need to achieve in order to realize your dreams. Below is an example of what those goals might be for your financial vision. (Note: For a more detailed discussion of SWOT development, see Developing Your Personal Strategic Plan.)

Dream/Vision: I will have a sound, long-term strategy for managing my financial affairs, have my finances under control, and be on track to have $1,000,000 when I retire!

• Reduce my on-going credit card debt to ZERO, and keep it there.
  
• Develop & implement an annual budget, saving 10% of my salary.
  
• Build an emergency fund that will cover my non-discretionary expenses for 6 months.
  
• Develop my initial plan to retire with $1,000,000.

Again, these are just examples. There could well be additional goals that you need to achieve in order to realize your financial dream. Your actual plan would include goals for your other dreams as well.

Adding Strategies to your Personal Strategic Plan

The final step is developing strategies for achieving each of your personal goals. For example, you have decided you would like to save 10% of your salary, but how are you going to do that? What do you need to stop or start doing in order to save that money? That part of your plan might look like this:

Goal: Develop & implement an annual budget, saving 10% of my salary.

• Buy Quicken or Microsoft Money this month to help with tracking and budgeting.
  
• Track all expenditures for one month to figure out where my money has been going and establish a baseline.
  
• Do a budget for the remainder of the year, then every December


• Initially, budget savings at 5% of take-home salary
  
• Ramp up to saving 10% of gross salary by allocating at least 50% of each annual salary increase to savings


• Start giving myself a weekly allowance (and sticking to it)!
  
• Begin doing monthly spending reviews to stay on track

Your actual plan would include strategies for your other goals as well.

Start Planning to Realize YOUR Dreams

In short, your completed personal strategic plan will include your dreams, goals and strategies. It's a description of your dream future, and the key steps you plan to take to make that dream a reality.

How about you? Are you still dreaming of a better life? If so, click here and start PLANNING for a better life.

The picture is from Public Domain Pictures.
Last updated 5/31/2009

Range of Stock Market Returns for 1-100 Years

In recent posts, we have looked at stock market performance over rolling 5, 10, 20 and 50-year periods on a more or less stand-alone basis. However, it also makes sense to look at these returns as a group -- as a series. What can we learn by analyzing differences in performance as we go from 1 to 100 years? The most obvious place to start is with the range of returns.

Chart of Range of Stock Market (Dow) Returns Over 1 to 100-Year Periods

The graph above (click to expand) shows the minimum, maximum and average DJIA (Dow Jones Industrial Average) annual returns for holding periods ranging from one year to 100 years. The assumption is that the investor bought at the beginning of the holding period and sold at the end, re-investing dividends in the interim. The minimum, maximum and average shown are for the entire holding period, not for individual years within the holding period. The data used is year-end data starting around 1900 and going through 2008.

Best and Worst Stock Market (Dow) Returns

The graph shows that the maximum gain was greater than the maximum loss for all holding periods. For example, the first bar shows that the best one-year return was around 95%; the worst was a loss of approximately 48%. However, this difference is misleading since, for example, it takes a 100% gain to recover from a 50% loss, as I will explain in more detail in a future post. The second bar shows that the best compound annual growth rate for the more than 100 two-year periods was about 45% per year; the worst was a loss of a little less than 40% per year. The final "bar" on the right summarizes the results of the ten 100-year periods, the most recent being from 1909 through 2008. (Note: The rolling return series mentioned at the top of this post includes graphs of all the returns for each holding period -- not just the minimum and maximum.)

As you might have expected, as the length of the holding period increases, the maximum compound annual return decreases; the minimum annual return increases. By the time we get to the 100-year returns, the range (9.4% to 10.3%) is too small to be visible in the chart. Therefore, the longer the holding period, the less likely it has been that investors experienced a loss for the full holding period. Investors who held for 1-3 years frequently experienced an overall loss; however, investors who held for just 5 years experienced an overall loss less than 10% of the time. Less than 1% of the 10-year holding periods resulted in an overall loss; holding periods of 20 years or longer never resulted in an overall loss. Reminder -- these are nominal returns; negative real returns were more frequent. (See this post for a discussion of nominal vs real returns.)

Average Stock Market (Dow) Returns

The average return starts at 11.8% for the one-year returns, drops rather sharply to 10.6% for the two-year periods, and then declines gradually to 9.9% for the 100-year periods. Historically, the longer the holding period the less likely it was to end with the investor losing money, and, the closer the return has been to the long-term average of around 10%. In fact, the maximum, minimum and average returns are all converging toward the long-term average return.

Based on this history, it appears that readers who are planning to buy and hold for 100 years or more are assured of performance very close to the long-term average return of around 10% per year -- regardless of when they buy. For those of us holding for shorter periods, there is a significant difference between the minimum and maximum annual rates of return that gets smaller the longer we hold. However, even for 50-year holding periods the annual returns range from 6.8% to 12.8%. That 6% difference, when compounded every year for 50 years, still results in a huge difference in dollars!

So, for most of us, it seems worth investigating factors that influence whether we earn the maximum returns or the minimum returns. We'll continue that investigation in the next post in this series.



Note: The above charts are based on DJIA (Dow Jones Industrial Average) data from my Stock Market Analysis Model. Results would be essentially the same if we used S&P 500 data.

Related Posts:

Graphs of rolling returns for five, ten , twenty, & fifty years.
Average Return for some key periods of interest
100 Years of Stock Market History (log graph)
For an index of all stock market posts, by subject area, click here.

Last modified 5/29/2009

Houston Rockets "Total" Production per-Minute

"Total" Production Per-Minute (A Simple Model)

A lot of people are surprised by Luis Scola's "emergence" during the National Basketball Association (NBA) playoffs. They wouldn't be if they had been looking at the stats that I track. You could make a strong argument that Luis has been the second most productive Rocket all season -- at least on offense. If you're surprised by the guy in first place, you haven't been paying attention.

The most reported measures of basketball productivity are points, rebounds and assists. Since these have been typically regarded as the primary measures of the contribution of a player, it makes sense that a reasonable first approximation of a player's total contribution is a combination of these three stats. However, normally the NBA reports these stats on a per-game or season-to-date basis. I prefer to look at these stats on a production per minute or per 40 minutes basis (my approximation of the results for a full game). This helps me adjust for the significant differences in minutes played -- especially by starters vs bench players. In the first post in this series, we looked at the Rockets' points, rebounds and assists per 40 minutes played.

Houston Rocket's "Total" Production Per-Minute

Below is a table summarizing the Rockets' "total" production per 40 minutes of playing time. The top 3 are Yao Ming (37.3 units of production per 40 minutes of playing time), Luis Scola (30.3), and Tracy McGrady (29.6). As I mentioned, the "surprise" is Scola in second place. If T-Mac had been healthy, it seems reasonable to assume that T-Mac would have come in second, given his 35.9 average last year. However, even in third place Scola would be a surprise to some.

The traditional NBA reported statistics essentially ignore defense -- primarily because a) it's not "sexy", and b) it's difficult to measure. In effect, this "total" metric assumes all of the players are equally effective on the defensive end. As a result, it undervalues players if a major portion of their contribution comes on the defensive end of the court. For the Rockets, this means it especially undervalues players like Chuck Hayes, Shane Battier and Ron Artest; maybe Yao as well -- though probably not relative to other centers.



Since the Rockets are about to go into the second round facing the LA Lakers, you might be interested in how Kobe Bryant stacks up against the Rockets using this metric. With 2201 points, 429 rebounds and 399 assists in 2960 minutes, he'd be first -- with a rating of 40.9 per 40 minutes of playing time.

Related links:

Houston Rockets "Per-Minute" Statistics (points, rebounds, assists)
More Houston Rockets "Per-Minute" Statistics (blocks, steals, FTAs)
The 10 Best NBA Players Ever calculates "total production" for some of the all-time greats.
The source of my data is nba.com

Last updated 6/4/2009

The Best & Worst 5 (and 50) Year Returns in Stock Market History

In recent posts, we've looked at intermediate-term stock market performance -- in particular, returns over 10 & 20-year periods. In this post, at the request of a reader (John W), we'll look at 5-year returns. I'm not sure what to call five years; to me, it's not really a long enough period to consider intermediate term, but too long to call short-term. In any event, we'll again look at rolling returns beginning around 1900.

"Rolling" 5-Year Stock Market (Dow) Returns Graph

Above is a chart of the 5-year total return of the DJIA (Dow Jones Industrial Average) beginning around 1900. Each point on the graph represents the average annual return earned by an investor who bought the Dow at that year-end and sold 5 years later, reinvesting dividends in the interim. For example, the first point on the graph shows that an investor who bought at year-end 1901, reinvested dividends annually, and sold at year-end 1906 earned approximately 13% per year. As always, I've had to estimate the returns prior to 1929.

The Best & Worst 5-Year Returns in History

As usual, the worst return (-16.4% per year) resulted from buying before the 1929 crash -- 1927 in this case, rather than our usual 1928. (Note: for more on the 1929 crash, see this post.) Also as usual, the best returns were the result of, in effect, selling near the top of a bubble. Buying in 1923 and selling in 1928 earned a 30.7% 5-year return; buying in 1994 and selling in 1999 earned a 26.8% return. Finally, again as usual, the average return was 10%.

Observations & Questions

Not surprisingly, the best 5-year return is better than the best 10-year return, but not as good as the best 1-year return. The worst 5-year return is worse than the worst 10-year return, but not as bad as the worst 1-year return. In addition, while I don't think the cyclicality of the 5-year returns is as pronounced as the 10-year returns, it's clearly more than is visible in the 1-year returns. And, that starts me down a whole new path.

We've been looking at the rolling returns to see what we can learn from them individually. However, there is clearly some kind of a pattern developing if we think of them as a series. For instance, you might ask, as you go from 2-year rolling returns to, say, 100-year rolling returns, what happens to the range of returns? When does the cyclicality start? When does it end? And, what's causing it??

John, thanks for encouraging me to continue this line of inquiry. As a first step, let's take a look at a longer-term rolling return.

Dow 50-Year "Rolling" Stock Market Returns Chart

The winner is (drum roll please) 1949, with a 12.8% annual return for the next 50 years -- at least partly because, 50 years from 1949 is ... 1999. And, the loser is (another drum roll) 1928, again, with a 6.8% annual return -- for the next 50 years. (Note: The average return was again 10%.) Remember, these are nominal returns, so assuming inflation averaged around 3%, the real return from 1928 was 3.8%. (For more on nominal vs real returns, see this post). As we have seen (e.g., in Stock Market Yearly Returns), investing in the stock market for 50 years exposes you to substantial year-to-year risk. Seems like a lot of risk, and for a lot of years, for less than 4% real return....

I have no idea how you know when you're 50 years before a bubble peaks so that you can buy. But, maybe we have a hope of figuring out when we're already at or near a peak so that we can at least consider not buying.

Let's keep digging.



Note: The above charts are based on DJIA (Dow Jones Industrial Average) data from my Stock Market Analysis Model. Results would be essentially the same if we used S&P 500 data.

Related Posts:

See this post for an index of all stock market posts, by subject area -- including:
Range of Returns for 1 to 100-Year Holding Periods
The Best & Worst 10 Years in Stock Market History
The Best & Worst 20 Years in Stock Market History
Stock Market Rolling Returns vs P/E Ratio Graphs

Last modified 5/21/2009

About Nominal & Real Rates of Return

Nominal Rates of Return

The nominal rate of return is the return that you see most often; most published rates of return are "nominal" rates of return. This is true whether they are stock, or bond returns. For example, if you pay $100 for a CD that will pay you back your $100 plus $5 in interest one year from now, the interest rate is quoted as (5/100=) 5%. Similarly, if you invest $100 in mutual fund XYZ on January 1 and a year later those shares are worth $105, the return on that fund is also 5%. If, in addition, the fund pays you $3 in dividends at the end of the year, the total return will be quoted as ((5+3)/100=) 8%.

While nominal rates of return are "the standard," they can be somewhat misleading -- especially when looking at returns over many years. That's because they ignore the impact of inflation.

Real Rates of Return

"Real" rates of return reflect the impact of inflation. If inflation is 3% per year, then a year from now it will cost $103 to buy what we can buy now for $100. In that case, if we have a $100 investment that earns 3% in nominal terms, a year from now it will represent the same purchasing power as it does today. That's because goods that you could buy now for $100 will cost you $103 a year from now. In that case, the "real" return is (3% nominal return on investment, minus 3% lost to inflation=) 0%. So, in our examples above, the real return on the CD is (5% - 3%=) 2%; the real total return on XYZ is (8% - 3%=) 5%.

Some Implications

It is often important to look at real rates of return when comparing rates of return during different eras. For example, a 12% 1-year CD when inflation was 14% per year, say, during the early 1980's, gave you a real return of (12% - 14%=) -2% -- i.e., you lost 2% of your purchasing power. On the other hand, a 3% CD when inflation is 1% has a (3% - 1%=) 2% real rate of return. The 3% CD is actually a better deal than the 12% CD was!

It's especially important to consider inflation when looking at performance over a long period of time. For example, a $100,000 house purchased 24 years ago and now worth $200,000 has had nominal price appreciation of 3% -- and, assuming inflation has averaged 3%, a real return of 0%. At three percent inflation, prices double approximately every 24 years. Note that this also means that, for example, over a period of 24 years, the purchasing power of a $2,000/month pension would fall to the equivalent of about $1,000/month. Therefore, when doing retirement planning it is critical that you either use real rates of return, or adjust your future expenses for inflation.

In this blog, returns are always nominal returns -- unless otherwise stated. However, when I'm looking at long-term returns, I mentally subtract 3% in order to approximate the real rate of return.

More Houston Rockets "Per-Minute" Statistics

In a previous post, we looked at the most frequently reported Houston Rockets statistics -- points, rebounds, and assists. In this post, let's look at blocks, steals and free throw attempts -- an important, but underappreciated statistic, for reasons that I will explain. While the National Basketball Association (NBA) normally reports these as season-to-date and per-games-played totals, I prefer to look at them on a per-minute, or per 40 minutes of playing time, basis.

Blocks per 40 Minutes of Playing Time

The top 3 are Dikembe Mutombo (4.9 blocks per 40 minutes of playing time), Yao Ming (2.3), and Shane Battier (1.0). Deke leading the way is, of course, no surprise; he's one of the best shot-blockers in the history of the game. However, his 4.9 is probably artificially high because he played so few minutes; the prior two years, he was right around 3.

The surprise here, for some anyway, is Shane -- and this was an off year for him. My sense is that it took him more than half the season to fully recover from his off-season surgery; otherwise, his number might have been closer to the 1.4 he had last year. Another surprise, for some, is the under-appreciated Chuck Hayes, with 0.9. Landry was close behind with 0.8 -- a big increase over last year's 0.4.

Steals per 40 Minutes of Playing Time

The top 3 are Ron Artest (1.8 steals per 40 minutes of playing time), followed by Chuck Hayes and Kyle Lowry (tied at 1.4). No one should be surprised to see Artest in first place. But, here's the "Chuck Wagon" again excelling at defense -- in this case, because he has quick hands. Note: I'm trying to get a good read on Lowry's game, so I'm using his full season totals -- i.e., I'm including his games with Memphis.

Free Throw Attempts per 40 Minutes of Playing Time

The top 3 are Yao Ming (7.0 free throw attempts per 40 minutes of playing time), Kyle Lowry (5.6), and Carl Landry (5.5). I wouldn't have been surprised if Yao's number was higher. In fact, you could argue it should have been higher. For reference, take a look at Shaq (9.2) and Dwight Howard (12.0)!

I'm using free throw attempts to approximate the number I'd really like to see -- fouls drawn. (If anyone knows where I can get fouls drawn please let me know.) It's an under-reported and under-appreciated stat. Drawing fouls is important not only because you get free throws (sometimes), but also because:

• You get the opposing team closer to its limit for the quarter -- so, you're increasing the number of foul shots, and points, your team will get later in the game.
  
• You get the opposing player closer to his limit for the game. If he's a starter, and he fouls out, he'll be replaced by a less accomplished player -- which generally means fewer points for the opposition, or more points for your team, or both. More likely, he won't foul out. However, you've still increased the probability that you will be able to get that player in foul trouble and force his coach to play him fewer minutes. Again, a less accomplished player will replace him. Finally, you've increased the probability that, in order to avoid another foul, he'll play less aggressive defense -- which increases the probability that your team will score. It's most obvious when you see a good shot blocker not even attempt to block a shot because he can't afford to take the chance of another foul.

Rockets fans have seen the impact of fouls demonstrated many times -- especially in Yao's early years. How many times have we lost a game because foul trouble limited Yao's minutes?

One of the reasons I'm so fond of Kyle Lowry is because of his ability to draw fouls. Don't misunderstand, I'm a big "AB" fan as well -- he and Kyle are just very different point guards. Having both may well turn out to be a significant plus for the Rockets during this year's NBA playoffs. This is another example of the depth and flexibility that the GM, Daryl Morey, is building into this team, as I mentioned in my season kickoff post. Tracking free throw attempts allows you to "guesstimate" how many fouls a player draws on the offensive end -- but not on the defensive end. Looking only at free throw attempts, Shane Battier and Chuck Hayes come in 10th and 12th on the team. That obviously significantly underestimates the contribution that those two make drawing fouls.

I'll try to do at least one more post in this series in the next couple of weeks -- as long as the Rockets are still playing....

For more detail on the above stats, see below.

Houston Rockets 2008-2009 Production per 40 Minutes Played

The table below (click to enlarge) shows the Rockets' results per 40 minutes of playing time for blocks, steals, and free throw attempts. For example, I divide a player's total blocks by his number of minutes played to get blocks per minute, and multiply that result by 40 to approximate his results for a full game (players rarely play a full 48 minutes). Note: I've omitted Brian Cook, Joey Dorsey and James White; they didn't play enough minutes to yield reliable results.

Related Material:

Houston Rockets "Per-Minute" Statistics
Houston Rockets: Is it Time Yet?
Houston Rockets "Total" Production Per-Minute
The source of my data is NBA.COM

Last modified 5/3/2009

Houston Rockets "Per-Minute" Statistics

Another Way of Looking at NBA Individual Statistics

Since we're headed into the National Basketball Association (NBA) playoffs, it is a good time to look back at some regular season statistics. I'm not crazy about the way the NBA publishes individual statistics. They generally just show you the totals; I prefer to look at production per-minute, or production per 40 minutes played. This helps me adjust for the significant differences in minutes played -- especially by starters vs bench players. In this post, I'll identify the top 3 Rockets in points, rebounds and assists per 40 minutes played. Yao is the top scorer and rebounder no matter how you look at it; beyond that, you may find a few surprises.

Points per 40 Minutes of Playing Time

The top 3 are: Yao Ming (23.5 points per 40 minutes), Von Wafer (19.7), and Ron Artest (19.2). McGrady was 4th at 18.5; however, if he had been healthy, he would likely have been closer to his 2008 number, 24.1, which would have put him in first place.

The surprise here, of course, is Von Wafer. I liked him a lot in pre-season, but thought it was a toss-up between keeping Von and keeping D.J. Strawberry (maybe because I'm a reformed NY Mets fan??). He seemed like such an unimportant addition to the team that he didn't even get a mention in my season kickoff post. These numbers tell you why the fans have fallen in love with him. Unfortunately, basketball is about more than scoring. However, if he can continue to improve the rest of his game, this will go down as another great move by GM Daryl Morey. Anyway, though Von is around 7th in total points, in my book he's clearly the 2nd most productive scorer. (I say clearly, even though he only has a half-point margin over Artest, because I strongly suspect that his stats for the last couple of months are significantly better than his early season stats. Wish I had the numbers to prove that, but I don't.)

Rebounds per 40 Minutes of Playing Time

The top 4 are: Yao Ming (11.7 rebounds per 40 minutes of playing time), Luis Scola (11.6), and Chuck Hayes & Dikembe Mutombo (tied at 11.4).

Yao, of course, is no surprise. It may be a surprise to some that Scola and Hayes are so close to him in production. Now that Scola is more acclimated to the NBA, his production has increased. His number last year was 9.9; that's a significant change. Chuck Hayes will also be a surprise to some. The "Chuck Wagon" is a very accomplished defensive player -- I just wish we could get a little more offense out of him. In my mind, Deke is clearly the best rebounder on the team. I suspect that, even at his age, had he played more, his results would have been closer to his 2008 number of 12.7 -- which would have put him in first place. Absent injuries, Carl Landry would likely have been in this discussion as well; last year, his 12.0 average was second only to Mutombo's.

Assists per 40 Minutes of Playing Time

The top 3 are: Kyle Lowry (6.6 assists per 40 minutes of playing time), Tracy McGrady (5.9), and Aaron Brooks (4.9). If "Skip" Alston were still with the team, he probably would be in first place, given his 6.7 average last year. And, if McGrady had been healthy, he might have been closer to his 2008 average of 6.3. The surprise, to some, is Kyle Lowry. In my view, Kyle is more of a "pure" point guard than Brooks; these numbers reflect that.

More Houston Rockets "Per-Minute" Statistics discusses blocks, steals and free throw attempts. I think "free throw attempts" are an important, but underappreciated, stat -- for reasons that I explain in that post.

For a little more detail on the above stats, see below.

Houston Rockets 2008-2009 Production Per 40 Minutes Played

The table below shows these key Rockets stats per 40 minutes played (click to enlarge). For example, a player's total points are divided by his minutes played to get points per minute, and that result multiplied by 40 to approximate the results for a full game. These stats are through the end of March. However, the results at the end of the season would be almost exactly the same. One advantage of looking at the stats this way is that they don't change very much from week to week or month to month; in fact, for established players they're quite consistent from year to year. For example, early in Yao Ming's career, when many were still questioning his skills (e.g., Charles Barkley), in my view he was consistently putting up close to 20 "ppg" and 10 "rpg" stats. The problem was he couldn't stay on the floor because of foul trouble and lack of stamina.

I've omitted Brian Cook, Joey Dorsey and James White since the've played so few minutes. On the other hand, I've included Dikembe Mutombo because he's a veteran with a track record, and could conceivable play an important role in the playoffs.

Related Stuff:

Houston Rockets: Is it Time Yet?
Houston Rockets' "Total" Production Per Minute
The 10 Best NBA Players Ever looks at this same data for some all-time greats.
The source of my data is NBA.COM

Last modified 6/4/2009

The Best & Worst 20-Year Returns in Stock Market History

Intermediate-Term Stock Market Performance since 1900

In a recent post we looked at a graph of yearly stock market performance since 1929; it appears to be completely erratic. Yearly returns varied from gains of close to 75% to losses of almost 50%, with no apparent rhyme or reason. We then looked at stock market rolling 10-year returns. The range of returns was dramatically smaller, roughly 0-20%, and much less erratic. The question is, what happens if we look at twenty to twenty-five year stock market returns?

In this post, we'll look at 20-year returns. As before, we'll look not only at the best and worst 20-year returns, but at a graph of all rolling 20-year returns for the last 100 years or more of stock market history.

Stock Market "Rolling" 20-Year Returns Graph

Above is a chart of the 20-year total return of the DJIA (Dow Jones Industrial Average) beginning around 1900. Each point on the graph represents the average annual return earned by an investor who bought the Dow at that year-end and sold 20 years later, reinvesting dividends in the interim. For example, the first point on the graph shows that an investor who bought at year-end 1901, reinvested dividends annually, and sold at year-end 1921 earned 7.1% per year. Note that the returns prior to 1929 are estimated (I have accurate closing prices, but have estimated the dividends).

As you might have expected, the maximum 20-year annual return is somewhat less than the maximum 10-year return -- 18% compared to 19.5%. The difference in minimum returns is somewhat larger; the minimum 20-year return was 2.5% compared to the worst-case 10-year loss of 1.3%.

The Best and Worst 20-Year Returns in Dow Jones History (since 1900)

What were the best and worst 20-year periods to own stocks? Well, if you bought in:

• 1941: the return was about 15% per year for the next 20 years, or
  
• 1979: 18% annual return

The worst years to buy were:

• 1928: the return was about 2.5% for the next 20 years
  
• 1958, 59 & 61: about 5-5.5% annual return

Summary/Conclusion

On average, 20-year returns were the same as 10-year returns -- around 10% per year. But again the start year had a significant impact -- as much as 10% per year or more. It's worth noting that, whether you're looking at a chart of returns over 10-year periods or over 20-year periods, 1928 is at the bottom of the pile. The obvious reason is that those investors had the great misfortune of starting just before the 1929-1932 stock market crash. Similarly, 10 or 20-year periods ending close to 1999 are near the top. Ten-year returns appeared to cycle between 0% and 20%. Twenty-year returns exhibit a similar, but more muted, cyclicality. However, unlike the 10-year returns, they appear to have a slight upward slope. That might be interesting to look into further at some point since it's somewhat counterintuitive.

Fiinally, it's again important to remember that these are nominal returns, not "real" returns. That means that these returns have not been adjusted for inflation. If you assume 3% inflation, the 2.5% nominal return for 1928 turns into a 0.5% loss, and the 5-5.5% nominal returns become 2-2.5% returns -- for 20 years. (For a more detailed discussion of nominal vs real rates of return, see this post.) Twenty years of negative, or barely positive real returns is not what most people expect. It could be a serious problem if, for example, the 20 years start the year you retire. That's one reason why I think those long, flat periods that I mentioned in 100 Years of Stock Market History are important.

Note: The above charts are based on DJIA (Dow Jones Industrial Average) data from my Stock Market Analysis Model. Results would be essentially the same if we used S&P 500 data.

Other Related Posts:

Stock Market Rolling 5 (and 50) Year Returns Graphs
Range of Returns for 1 to 100-Year Holding Periods
20-Year Rolling Returns vs P/E Ratio
Stock Market Average Annual Returns since 19xx
For an index of all stock market posts, by subject area, click here.

Last modified 5/21/2009

The Best & Worst 10-Year Returns in Stock Market History

Intermediate-Term Stock Market Performance

In previous posts we have looked at stock market performance over both the short term and the long term. In this post, we'll focus on performance in the intermediate term -- in particular, returns over 10-year periods. However, we are not only going to look at the best and worst 10-year returns, we're going to look at all of the so-called "rolling" 10-year stock market returns since around 1900.

Stock Market "Rolling" 10-Year Returns Graph

Above is a graph of the 10-year total return of the DJIA (Dow Jones Industrial Average) beginning around 1900. Each point on the graph represents the average annual return earned by an investor who bought the Dow at that year-end and sold 10 years later, reinvesting dividends in the interim. For example, the first point on the graph shows that an investor who bought at year-end 1901, reinvested dividends annually, and sold at year-end 1911 earned 7.9% per year. Note that the returns prior to 1929 are estimated (which is why I sometimes omit them).

This is the same data as was used for the 10-year return histogram in the Stock Market Yearly Returns since 1929 post. However, this presentation gives us a significantly different impression. The 10-year histogram left us with the impression that 10-year returns have been consistently between 0% and 20%, and much less variable than yearly returns. That's true. However, what the histogram misses is the cyclicality. Ten-year returns now appear to cycle from near-zero to nearly 20% per year, and back again. This is another example of the boom and bust nature of the stock market alluded to in the discussion of the graph in 100 Years of Stock Market History.

The Best and Worst 10-Year Returns in Dow Jones History (since 1900)

So, what were the best & worst 10-year periods to own stocks? That is, in hindsight, when would have been the best and worst years to buy?

The best 10-year periods to own stocks were the years beginning in:

• 1918: the return was about 19.5% per year for the next 10 years
  
• 1948 & 49: 18.5% annual return
  
• 1987 & 88: about 18.5% annual return

The worst years to buy were:

• 1922: the return was 0.4% per year for the next 10 years
  
• 1928: -1.3% annual return (loss)-- because you would have had the great misfortune of buying just before the 1929-1932 stock market crash.
  
• 1964: annual return of 0.3%

The 10-year return histogram presentation in the Yearly Returns post was incomplete because:

• It completely hides the cyclicality.
  
• We started in 1929 and missed the fact that 10-year returns can in fact be negative (a key reason why I started in 1901 for this post)
  
• It wasn't as clear how often returns are almost zero

The graph shows several instances of near-zero 10-year returns. To my way of thinking, ten years is a long time to go with essentially no return on your investment. In addition, there were a number of 10-year periods with returns of 5% or less. Remember, these are "nominal" returns, not "real" returns. That means that these returns have not been adjusted for inflation. If you assume that over this period inflation has averaged about 3% per year, then the less than 5% nominal returns become less than 2% in real terms, and the near-zero returns become negative. (For a more detailed discussion of nominal vs real rates of return, see this post.)

Summary/Conclusion

On average, 10-year market returns were around 10% per year. However, it appears that the 10-year returns vary considerably, depending on your "start year." I like this chart! It's an area that I had not looked at carefully before. Many thanks to my readers for encouraging me to investigate (in ways that are difficult to explain at this point) -- though I'm not at all certain that I understand all of the implications. Perhaps we can uncover at least some of them with additional investigation.

Note: The above charts are based on DJIA (Dow Jones Industrial Average) data from my Stock Market Analysis Model. Results would be essentially the same if we used S&P 500 data.

Related Posts:

Stock Market Rolling 20-Year Returns Graph
Range of Returns for 1 to 100-Year Holding Periods
Rolling 5 (and 50) Year Returns Graphs
10-Year Rolling Returns vs P/E Ratio
Stock Market Average Annual Returns since 19xx
For an index of all stock market posts, by subject area, click here.

Last updated 5/21/2009

Subject Index for Stock Market Posts

This index organizes the stock market posts by general topic. (For non-stock-market posts, see the "labels" section of the sidebar.) I have grouped the posts into broad subject areas. The groupings are as follows:

• BASICS
• HISTORY/ANALYSIS
• Bull markets, Bear markets and Crashes
• Closing prices
• Earnings, earnings growth rates and Dividends
• Price/earnings ratios
• Rates of return for various time periods
• PROJECTIONS
• Potential Support Levels
• Worst-case scenarios
• OTHER

*****NOTE: SEE LINKS TO INDIVIDUAL POSTS BELOW*****

BASICS

About Stock Market Log Graphs
About Nominal & Real Rates of Return
About P/E, Normalized Earnings and Normalized P/E Ratios
My Favorite Personal Finance Books

HISTORY/ANALYSIS

Bull Markets, Bear Markets and Crashes

The 1929-1932 (Great Depression) Stock Market Crash Revisited -- includes log graph of daily closing prices, and comparison to current bear market.
Major Bull and Bear Markets Since 1900: secular bull and bear markets.
The Extraordinary Impact of Price to Earnings Ratios -- includes analysis of how much of the 1929 crash was "caused" by changes in p/e ratio vs earnings & dividends.
Three Scenarios for the Stock Market (and the economy): Includes links to detailed analysis of some previous major bear markets such as Japan's.
Analyzing & Understanding 100 Years of Stock Market History -- includes analysis of the 1994-1999 bull market.
My Favorite Personal Finance Books
Stock Market Analysis Model

Closing Price History

100 Years of Stock Market History: log graph of year-end closing prices since around 1900.
Dow Price to Earnings Ratios since 1929 - Yearly Graph superimposed over closing prices graph.
Stock Market Earnings Growth History, Average Returns, and a Worst-Case Scenario
Dow at 25-Year Moving Average (log graph)
Analyzing & Understanding 100 Years of Stock Market History: analyzing causes of price movement.
Stock Market Analysis Model
About Stock Market Log Graphs

Earnings, Earnings Growth Rates, Dividends

Dow Price to Earnings Ratios since 1929 - Yearly Graph superimposed over earnings and dividend growth.
Stock Market Earnings Growth History, Average Returns, and a Worst-Case Scenario: derives estimate of long-term earnings growth rate.
Analyzing & Understanding 100 Years of Stock Market History: comparison of impact of earnings and dividends vs the impact of p/e.
Normalized Earnings and Returns
Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History
Stock Market Analysis Model

Price/Earnings Ratios, Earnings Multiples, Valuation

Dow Price to Earnings Ratios since 1929 - Yearly Graph
Stock Market Rolling Returns vs Price to Earnings (P/E) Ratio Graphs: The impact of p/e on future returns.
The Extraordinary Impact of Price to Earnings Ratios -- compared to the impact of earnings & dividends.
Dow Price to Earnings Ratios since 1900 - A Summary: the distribution of p/e ratios over the last 100 years, and subsequent returns. Impact in $$$.
Analyzing & Understanding 100 Years of Stock Market History
Major Bull and Bear Markets since 1900: P/E ratios at major tops and bottoms.
Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History
The Crisis: A Contributing Factor
My Favorite Personal Finance Books
Stock Market Analysis Model

Prices (see Closing Prices)

Returns, Rate of Return

Stock Market Returns by Year since 1929 (bar graph)
Average Annual Stock Market Return since 19xx: rates of return for some key periods of interest.
Range of Stock Market Returns for 1-100 Year Holding Periods
The Best & Worst 10-Year Returns in Stock Market History (graph of all 10-year "rolling" returns since about 1900)
The Best & Worst 20-Year Returns in Stock Market History
The Best & Worst 5 (and 50) Year Returns in Stock Market History
Stock Market Earnings Growth History, Average Returns, and a Worst-Case Scenario
Stock Market Rolling Returns vs Price to Earnings (P/E) Ratio Graphs: The impact of p/e on future returns.
Dow Price to Earnings Ratios since 1900 - A Summary: the distribution of p/e ratios over the last 100 years, and subsequent returns. Impact in $$$.
Major Bull and Bear Markets since 1900
Analyzing & Understanding 100 Years of Stock Market History
Normalized Earnings and Returns
About Nominal & Real Rates of Return
My Favorite Personal Finance Books
Stock Market Analysis Model

PROJECTIONS

Potential Support Levels

100 Years of Stock Market History -- includes log graph with 25-year moving average.
Dow At 25-Year Moving Average (log graph)

Worst-Case Scenarios

The 1929-1932 (Great Depression) Stock Market Crash Revisited -- includes log graph of daily closing prices, and projection of 1929 crash to today.
Stock Market Earnings Growth History, Average Returns, and a Worst-Case Scenario
Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History
Three Scenarios for the Stock Market (and the economy): Outline of possible scenarios, including links to assessments by Nouriel Roubini, Bill Gross, Robert Shiller, Jeremy Grantham, and others.
Stock Market Analysis Model

OTHER/MISCELLANEOUS

Three Scenarios for the Stock Market (and the economy): Outline of possible scenarios, including links to assessments by Nouriel Roubini, Bill Gross, Robert Shiller, Jeremy Grantham, and others.
Sobering Comment
Subprime Mess: The Problem With Low Down Payments
The Fed Proposes Insurance for Money Market Funds
Wall Street Bailout, or Main Street Rescue?
The Crisis: A Contributing Factor
My Favorite Personal Finance Books
Stock Market Spreadsheet and Data Navigation Guide



Last updated 6/18/2009

Stock Market Annual Performance Chart since 1929

Previous posts have graphed Dow closing prices over the last 100 years and looked at the stock market's long-term average annual return for some key periods in history. However, in addition to looking at long term results, it also seems reasonable to graph stock market returns by year, again going all the way back to 1900 -- or at least to 1929. Here's what it looks like.

Dow Annual Performance Graph since 1929

The chart above (click to enlarge) shows the total yearly return of the DJIA (Dow Jones Industrial Average), beginning in 1929; total return is the result of price change plus dividends. (Note: For a daily graph of the 1929-32 stock market crash, see this post.) A regular line graph of this data seemed useless to me; I think the bar/column chart works better. What can we learn from this graph? Initially, about all I could conclude was:

• Stock market returns vary a lot from year to year
  
• The market goes up a lot more often than it goes down, but you can sometimes lose money
  
• The down years are often isolated, "one-off" events, and usually smaller than the up years -- kinda like speed bumps
  
• While most down years seem to result in "minimal" losses, a few resulted in substantial losses of more than 20%

Dow Yearly Return Frequency Chart

In the histogram above (click to enlarge), the label below the column is the maximum of the range. For example, we see that there were no years with losses greater than 50%, and 5 years with losses between 50% and 20%. For me, the histogram provides a more useful view of this data; the variability from year to year is still pretty mind-boggling. However, now I can see that:

• Stock market returns are negative about 20 (or 25%) of the 79 years; so, about 75% of the years have positive returns. There are relatively few bars with less than 0% return, but quite a few above 0% -- sometimes way above 0%.
  
• Most of the time (about 45 of the 79 years), the returns have been between 0% and 30%

What's not to like? It looks like when you lose, you lose a little, but when you win you can win a lot!

In addition, you could make the argument that investing is not a one year deal, so it makes more sense to look at longer-term performance. Here's the same histogram as above, but with 10-year returns instead of yearly returns.

Dow 10-Year Annualized Return Frequency Chart

Note that this is the same data, with the same return ranges along the x-axis (horizontal axis). However, in this case, instead of 79 data points, there are only 69 data points -- 1929-1939, 1930-1940, ... 1998-2008. The apparent message here is that, over 10 year periods:

• A little less than half the time your 10-year return will be between 0% & 10% per year
  
• A little more than half the time you'll make between 10 & 20% per year
  
• People have not lost money when holding for 10 years
  

Conclusions

Again, what's not to like? It appears that worrying about the year-to-year variability (let alone worrying about monthly, weekly, or day-to-day variability) is a fool's errand. You could conclude from looking at the above graphs that investing in the stock market can be a very good thing indeed; I think that's true. You might also conclude that it's virtually impossible to lose money in the stock market over the long term. I'd hold off on that one. We'll continue the analysis in future posts. (See, for example, this graph of rolling 10-year stock market returns.)

Note: The above charts are based on DJIA (Dow Jones Industrial Average) data from my Stock Market Analysis Model/Spreadsheet. Results would be essentially the same if we used S&P 500 data.

Related Materials

For an index of all stock market posts, by subject area, click here.

Last modified 5/8/2009

The 1929 - 1932 Stock Market Crash Revisited

Worse Than Worst-Case Scenario?

In a previous worst-case post, I developed a worst-case scenario with the DJIA (Dow Jones Industrial Average) closing in the neighborhood of 4100. An alert reader suggests that is optimistic! He maintains that, if we were to repeat the 1929 stock market crash, the Dow could fall to 2100.

Why the difference? The short answer is because my previous worst-case posts used very high-level, year-end data. The point I was trying to make in the earlier posts was that it would be prudent to at least consider the possibility of the Dow at levels that seemed unimaginable at that time. In this post, we will analyze daily data.

The 1929-1932 (Great Depression) Stock Market Crash Graph

As you can see in the graph above (click to enlarge), the Dow peaked in September of 1929 and continued "steadily" downward until it bottomed in July of 1932; the Great Depression continued for some years afterwards. (Note: For a much longer term graph, see 100 Years of Stock Market History. If you are not familiar with log graphs like this one, see About Stock Market Log Graphs) The bottom line? A $10,000 investment in 1929 was reduced to about $1100 in 1932 -- a loss of almost 90%! Some initial observations:

• It took almost three years to reach the bottom. People think of the 1929 crash as being a dramatic drop. Well, it was; the Dow dropped almost 50% in just over two months. However, at that point, the decline was far from over in terms of either magnitude or duration -- the market continued to decline for another two and a half years.
  
• If we look only at year-end numbers, the Dow dropped from 248 to 60, a drop of about 76%. However, the drop from the September 1929 high of 381 to the July 1932 low of 41 was an astounding 89%; looking only at year-end numbers misses about 13% of the drop.

Secular Bear Markets and Bear Market Rallies!

What I didn't fully understand until I looked at the daily chart was how agonizingly frustrating it must have been. The market changed direction about a dozen times -- typically every one to three months. During this approximately three-year period:

• There were at least six "false starts" that might have led an investor to believe that the bear market was finally over. Five of the rallies would qualify technically as bull markets -- the market rose more than 20%. All of these were "bear market rallies;" the resulting stock market highs were lower than the previous highs, and the following lows were lower than the previous lows.
  
• It's probably worth pointing out that each of the seven major declines was a bear market on its own; each was greater than 20%; six were greater than 35%. Think about it. In a period of less than three years, a typical investor lost more than 35% of his assets six separate times. Three of the declines were more than 40% (another was 39%).
  
• There were only two periods when the market maintained its direction for more than three months:
  
• The initial 2-month 50% drop was followed by a 5-month, 50% rally that was probably very reassuring, but ultimately just the first of many "head fakes" (reminder: it takes a 100% increase to erase a 50% loss)
  
• A four-month bear market that took the market from 89 to the final low of 41 -- a greater than 50% loss, and from a point where you have to believe many people felt things could not possibly get any worse; this decline was even greater than the more famous initial crash, and was the final capitulation.

Note: For an analysis of the contribution that earnings, dividends and valuation made to the drop in prices during this historic three-year period, see the "Analyzing the Stock Market Crash 1929-1932" section of this post.

What If We Repeated the Stock Market Crash of 1929 - 1932? --- An Even Scarier Chart

The question the reader raises is, what if we had another stock market crash "just like" 1929.



In the graph above (click to enlarge), the solid line is actual daily Dow closing prices from January 1, 2007 through March 17, 2009. The dotted line is 1929-1932 closing prices moved to 2007-2010 and multiplied by about 37; the 2007 high was (14165 divided by 381=) about 37 times the 1929 high. If you compare the descent beginning in the fall of 1929 to that beginning in 2007, you can see that the paths for the next 18 months were significantly different. However, coincidentally, in both cases March was approximately 50% from the peak.

The bottom line is, if the Dow again declined by 89.2% from its peak daily close, as it did in the 1929 - 1932 crash, the Dow would go to 1532! Note that this is even worse than the reader's worse-than-worst case. So, it appears that the reader was also being optimistic.

Some Final Comments

This is NOT a forecast. You can't generalize based on what is essentially one observation. On the other hand, I'm not going to ignore it. Could it happen again? Of course -- it's the future.

Related Materials

Click here for an index of all stock market posts, by subject area, including Three Scenarios for the Stock Market (and the economy), and Dow Price to Earnings Ratios Since 1929 - Yearly Graph.

If after reading this post you need an antidote, try Barton Biggs' article -- in the March 16, 2009 issue of Newsweek it was entitled "Brighter Days Ahead."
The source for my daily data is here


Last updated 5/2/2009

Stock Market Average Annual Return since 19xx

Stock Market Long-Term Average Annual Rate of Return
(e.g., from 1900 or 1929)

Many readers are wondering what the long-term performance of the stock market has been. Throughout stock market history, the average yearly return for periods of 25 years or longer has been around 9-10%. Of course, performance varies somewhat depending on what you mean by "long-term" and "stock market." Following are the results for several periods of particular interest:

• The yearly return from 1900 to 2008 was 9.3% (4.6% price appreciation, plus 4.7% in dividends)
  
• The annual return from 1901 - 2008: 9.4% (4.7%, plus 4.7%)
  
• The return from 1929 to 2008 was 8.9% (4.6%, plus 4.3%)
  
• From 1932 - 2008: 11.0% (6.8%, plus 4.2%)
  
• For the last twenty-five years, the annual return was 11.0% (8.1%, plus 3.0%)
  
• For the last 20 years, 9.8% (7.2%, plus 2.6%)
  

Notes: For graphs of performance over the long-term, see Stock Market Returns by Year, Range of Returns for 1-100 Year Holding Periods, Rolling 10-Year Returns, Rolling 20-Year Returns, and 100 Years of Stock Market Closing Prices. In all cases above, the returns are from year-end to year-end. In addition, by "stock market" I mean the DJIA (Dow Jones Industrial Average). The results would be essentially the same for the S&P 500.

Calculating the Dow's Historical Performance

I have created a Stock Market Analysis Model specifically to answer questions such as the above. Using that spreadsheet, you can calculate the Dow's average annual return between "any two years in history" (well, for now, between 1929 and 2008 anyway). In addition, the model separates the returns attributable to appreciation in closing prices from those attributable to dividends. Finally, for periods ending before 2004, the price appreciation is broken into appreciation caused by increases in earnings versus that part caused by increases in the price/earnings multiple. The chart/table below (click to enlarge) shows the results for 1929 to 1932.

Example: Dow Performance from 1929 to 1932

The model is useful for many other purposes. For a more complete discussion of the model and its capabilities, see Analyzing & Understanding 100 Years of Stock Market History.

What If? -- Calculating the Dow's Annual Return to 2009

Note that the model currently only contains data through end of year 2008 (see the "Dow Data" tab). However, you can approximate the results to date by replacing the 2008 year-end close with a recent closing price to see what the results would have been had 2008 ended at that price. An alternate method that will be more appropriate as we get later in the year is to enter data for 2009 into the spreadsheet (there is a row for 2009). If you enter a closing price in column C and estimated dividends in column J, the model will perform the calculations treating those as year-end 2009 numbers.

NOTE: If a spreadsheet cell is unreadable, click on it, hit F2, then hit enter.

Related Materials:

The Extraordinary Impact of Price to Earnings Ratios --especially if you think the results above are unusual.
Calculating the Long-Term Earnings Growth Rate
For an index of all stock market posts, by subject area, click here.

Last updated 5/8/2009

About Stock Market Log Graphs

Why Use Log Graphs for Long-Term Stock Market Graphs?

Some of you have noticed that on most of my stock market graphs, the "Y" (i.e., vertical) axis looks a little strange. That's because these are log graphs. Why, for example, are the graphs in 100 Years of Stock Market History log graphs? The simple answer is that if they were "normal" (linear) graphs they would look like this....

Dow Jones 100-Year Linear Graph

Not very enlightening is it? The problem is that, for example, a 100-point move looks the same in 1927 as in 2007 -- that is, you can't see it. A 100-point increase in the Dow from year-end 2007 to year-end 2008 would have been less than a 1% increase for the year -- hardly newsworthy (though WAY better than what actually happened!). However, the actual 100-point increase in the Dow from year-end 1927 to year-end 1928 WAS newsworthy -- it was a 50% increase.

Stock market graphs typically cover 5 years or less; in that case, normal linear graphs work fine -- unless it's an exceptionally volatile period with very large changes from year to year. For our purposes, we want a 50% increase to look the same whether it happens in 1927 or 2007; more to the point, we want a 50% increase to look the same if the Dow is at 200 as it does if the Dow is at 2000. That's the case with the log graphs. For example, notice that in the charts in the "100 Years" post, the distance between 100 and 1000 is the same as the distance between 1000 and 10000; a 10x increase is always the same distance. Also, note that the horizontal grid lines between 10 and 100 are in increments of 10; the grid lines between 100 and 1000 are in increments of 100, etc.

Technically, these are semi-log graphs-- that is, one axis is linear and the other is logarithmic. For a more in-depth discussion, see this article.

Was This Helpful?

I don't have a feel yet for the experience level of my readers; for the most part, I have been assuming a moderate level of experience. I am considering additional posts (articles) in this "Stock Market Basics" series, but don't know if they are necessary -- or which topics to cover. Comments would be appreciated: Have you found parts of other posts difficult to understand? Are there other concepts that you would like explained in more detail? Let me know.

Last updated 5/28/2009

Finally, A Little Love From Yahoo!

For a new blogger, one of the fun things is seeing traffic from all over the planet; I've now had visitors from every continent not perpetually covered by snow. Even more rewarding is the increasing attention from readers -- and search engines (without which, there would be few readers).

Speaking of readers.... This has been an historic 7-10 days for Observations' readership. February obliterated the previous monthly traffic record; last week, the daily and weekly records followed suit. Unfortunately, it's a mixed blessing. Because over 75% of my traffic is stock market related, if my traffic is up, it often means that the stock market is down -- a mixed blessing at best!

Google was the first search engine to discover Observations. However, getting discovered is just the start; you want to get ranked on the first page. Still, being ranked by Google is a good thing, even if not on the first page; they handle about 50% of the searches. Therefore, it was especially rewarding when I noticed the search below:



Observations has been at the top Google searches before, but, to my knowledge it' s never held the top TWO spots before.

Yahoo and MSN Live Search have been especially slow to discover Observations. So, I was even more surprised to finally get "a little love" from Yahoo, with the second and third spots in the "dow history chart" post below.




Note that this is Yahoo Glue, and (I just realized) they are apparently using a Google Blog search! Here's hoping Yahoo's right hand (Glue) is talking to their left hand (YAHOO's search engine). Most compilations like the above are computer generated; they just do a search and spit out what they find. What's encouraging about this one is that, while the selection process is automated, there is at least a hint of humanoid involvement in the creation of the abstract. Maybe somebody up there, at Yahoo, likes me! Who knows, maybe this could be the beginning of a beautiful friendship.


p.s. I have no idea why the quality of the graphics is so poor. Obviously this new blogger still has a lot to learn....

Dow At 25-Year Moving Average

In a previous post, I noted that the stock market rarely falls very far below its 25-year moving average. As you can see from the graph below, we are now right at that moving average (click on the graph to enlarge it). On Monday, March 2, the DJIA -- Dow Jones Industrial Average -- closed at 6763. If we treat that as the 2009 close, the 25-year moving average is 6768.

Dow 25-Year Moving Average Graph

A Critical Area on the Dow?

To my knowledge, this is not a widely followed metric. For one thing, it would be a "waste of time" -- kinda like watching grass grow. In the history of the Dow, I see only four previous periods when we have been in this area:

• The Great Depression -- the 1932 & 1937 troughs in the graph (For more on this period in stock market history, see 1929-32 Crash Revisited)
  
• World War II -- the 1940-43 trough
  
• The Vietnam War/ Oil Crisis years culminating in the 1974 trough
  
• The high inflation era culminating in the 1981 trough
  

In the most recent instances, 1974 and 1981, the 25-year moving average provided solid support. In fact, 1981 was the beginning of the greatest bull market in history. However, the support was less firm in 1941, and non-existent in 1932. The obvious question: Is today's environment more akin to 1974 and 1981, or more like the World War II and Great Depression eras?

Stay tuned.

Related Posts

The moving average in 100 Years of Stock Market History is updated monthly.
For a list of all stock market posts, by subject area, click here.

Last modified 6/26/2009

Dow Price to Earnings (P/E) Ratios Since 1929 - Yearly Graph

Dow Price to Earnings Ratios Since 1900 - A Summary provides a perspective on the stock market that I think is very important. However, it just occurred to me that many readers would like to see the DJIA (Dow Jones Industrial Average) yearly data -- as a graph. In fact, I now believe it is better to look at this yearly P/E ratio history chart first; I think it will help readers understand the real import of the summary post. (Many of you may also find the more detailed graph of the 1929-1932 crash interesting). So, ....

Yearly Graph of Dow Price Earnings (P/E) Ratios Since 1929

As you can see from the chart above (click to enlarge), this one does not go all the way back to 1900 -- it's 1929 through year-end 2008. But if it did, the message would be the same. What's most striking about this graph is the variability of the price/earnings ratio; the p/e ratio is the price you have to pay for $1 of earnings. This earnings multiple varies from close to 30 all the way down to around seven. And, remember, these are normalized price earnings ratios (the price divided by normalized earnings -- NE). I call this the NPE. If I had used the standard yearly p/e ratio, the variation would be even more dramatic. (As you might guess from just looking at the chart, the average normalized price/earnings ratio is about 15. See note at end of post for how normalized earnings are calculated.)

The other thing you might notice is the years in which the big decreases and increases in NPE occurred. Notice anything? The big drops in earnings multiples, or valuation, correspond to years when the stock market crashed -- 1929 for example. The long periods of increases just happen to correspond to years where there was a tremendous bull market -- 1994-1999 for example.

The Impact of Price/Earnings (P/E) Ratios on Dow Performance and Returns

The above chart (click to enlarge) shows the same NPE data combined now with a) normalized earnings, b) dividends, and c) the Dow year-end closing price. (Note: The 100 year graph of closing prices was first introduced, and discussed in more detail, in this post.) The vertical axis for NPE values has been moved to the right hand side. The vertical axis for the other data is on the left hand side. (The left vertical axis is log scale; for a short discussion of log graphs, see About Stock Market Log Graphs.)

This chart reinforces what you might have guessed from looking at the first chart. Notice how (relatively) smooth the growth is in the normalized earnings and dividends lines. There is a pretty consistent up-trend -- around 6%/year. However, the graph of Dow closing prices is not nearly as consistent. Where do we see the big drops in the Dow? When there are big drops in the earnings multiple -- NPE. Where do we see the Dow in long bull markets? When the NPE increases.

What Really Drives Stock Market Prices?

All of the above based on Dow Jones data; we'd see essentially the same pattern if we were looking at S&P 500 data. Bottom line: In my view, stock market value is driven primarily by earnings and dividends. However, based on about 100 years of stock market history, it looks like stock market prices are driven by the earnings multiples -- i.e. p/e ratios. As I have said before, and no doubt will say again, ignoring valutation may be hazardous to your (financial) health.

For another view of the impact of valuation on returns, see P/E Ratios vs Rolling Returns.

Note re normalized earnings (NE): The normalized earnings for any year are the average of that year's earnings with the 5 previous and 5 following years' earnings.

Related posts

The 1929-1932 Stock Market Crash Revisited (daily graph of the crash -- with potential implications.)
The Extraordinary Impact of Price to Earnings Ratios: A more in-depth look at the impact of p/e ratio.
Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History
For an index of all stock market posts, by subject area, click here.

Last modified 6/29/2009

Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History

A separate post in this series provides a graph of DJIA (Dow Jones Industrial Average) price/earnings ratios by year since 1929. The most recent post summarizes Dow P/E ratio history since around 1900. In this post, we will apply those historic earnings multiples to recent Dow Jones earnings -- primarily in order to create some worst-case scenarios.

One of the primary reasons for doing the original analysis was to get a feel for the range of multiples that have been applied to stock market earnings in the past 100 years or so. As the table below shows, the range of earnings multiples is very wide; the normalized price earnings ratios, NPEs, range from around 33 to around 7. (Note: NPE is price divided by normalized earnings.) What this means is that there have been years when the market charged ($100 of earnings x an NPE of 33=) $3300 for $100 of stock market earnings; there have been other years when you could buy the same level of earnings for about $700. The range between expensive and cheap is very wide indeed.

Pricing the Dow Using Historic Earnings Multiples

An important question is, based on our history of earnings multiples since 1900, what price might the stock market have assigned to the Dow given recent earnings. Answering that question will give us some perspective. First, we will look at 2002, and then extrapolate to 2008/2009.

Implications of Price to Earnings Ratios on Expected Dow Price Range for 2002

Note: The average NPE between 1898 and 2007 was 14.9.

The table above approximates the range of prices that the market might have paid for 2002 normalized earnings (NE) of $455. (Because of the way I normalize earnings, 2002 is the most recent year for which I have calculated normalized earnings.) The table shows:

• Normalized earnings: For 2002, $455 is the average of actual Dow earnings from 1997 through 2007.
  
• NPE Percentile: 10% of the NPE readings are at or below the 10th percentile; 20% are at or below the 20th percentile; 100% are at or below the 100th percentile.
  
• NPE: The normalized price earnings ratio for that percentile. For example, 10% of the years had NPEs of 9.4 or below.
  
• Dow Estimated Price: For 2002, this is normalized earnings (NE) multiplied by the NPE for each percentile. In other words, price is equal to earnings times the earnings multiple.

As you can see, if the 100th percentile NPE is used as the earnings multiple, the Dow would have closed 2002 around ($455 x 32.83=) 14,937; a valuation based on the 10th percentile would have resulted in a close around 4255. The actual close was 8341 -- just below the 80th percentile. So, at year-end 2002, even after the post dot-com bear market, the market was still quite expensive -- though not in "nosebleed" territory.

Extrapolating Normalized Earnings to 2008

I can't yet calculate the normalized earnings for 2008 since we don't know the earnings for 2009-2013. Therefore, I have had to estimate. That's ok; we're just trying to get some ballpark numbers anyway. I have estimated 2008 normalized earnings three ways -- that is, by extrapolating from three different "base years":

1. Based on 2002 -- the most recent year for which we have normalized earnings. If you increase the 2002 normalized earnings of $455 by the long-term earnings growh rate of 5.72%/year, you arrive at an estimate of $635 for 2008 normalized earnings. For various reasons, I think the 2002 NE are above trend; they probably generate an optimistic estimate for 2008. (See this post for how I arrived at 5.72%)
2. Based on 1974 -- the most recent secular trough. If you increase the 1974 normalized earnings of $83.11 by 5.72%/year, the estimate for 2008 normalized earnings is $551. Since 1974 and 1932 are secular bottoms, they probably (hopefully?) generate somewhat pessimistic estimates.
   
3. Based on 1932 -- the trough associated with the Great Depression. The 1932 NE of $8.32 project to $570 in 2008.

2008-2009 Worst-Case Scenarios

Based on 100 years of stock market history, it appears that the February 23, 2009 Dow close of 7115 is somewhere between the 30th and 50th percentile. For example, using the $635 estimate for 2008 normalized earnings, the 30th percentile is 7091 -- just below the actual close of 7115. Apparently, even after all this pain, the market is still not extraordinarily cheap. Some additional observations:

1. No matter which of the three estimates for 2008 normalized earnings we use, in at least 30% of the years in our database those earnings would have resulted in a Dow price lower than 7115.
   
2. Regardless of which estimate you use, in at least 10% of the years the Dow would be valued at less than 6000.
   
3. If "Mr. Market" decided to apply valuations comparable to those applied in 1932 and 1974, we might see the Dow in the neighborhood of 4100. In a way, this post clarifies the worst-case estimate in my previous worst-case scenario post. The years 1932 and 1974, are basically "bottom of barrel" valuations -- earnings multiples that we have seen only about twice in 100 years. So, another way to think about the Dow 4084 figure quoted in the previous Worst-Case post is that it assumes a) 1974 (i.e., near absolute worst-case) normalized earning -- projected forward, and b) 1974 (again, near worst-case) normalized price earnings ratios.

Conclusion

Obviously these numbers are not predictions; I am simply trying to "ballpark" POSSIBILITIES -- based on estimates and extrapolations. Primarily, I'm trying to get a feel for what MIGHT happen so that I can prepare for it. What I conclude from the analysis above is that prices could go lower and still be consistent with stock market history since 1900. (Note that though this analysis is based on Dow Jones data the results would have been similar if I had used S&P 500 data.) A future post will describe how I go about preparing for these possibilities. Bottom line: I'm not betting the farm quite yet.

Related Materials

Dow Price to Earnings Ratios Since 1900 - A Summary: The precursor to this post.
Stock Market Earnings History, Average Returns, and a Worst Case Scenario: My previous approach to developing worst-case scenarios.
The 1929-1932 Stock Market Crash Revisited: the ultimate worst case?
Managers Say Stocks Have Been Cheaper: Morningstar article quoting John Hussman and Jeremy Grantham who reach similar conclusions.
Why Stocks Still Aren't Cheap: New York Times article: same conclusion.
Three Scenarios for the Stock Market (and the Economy): A qualitative instead of quantitative description of scenarios.
The Extraordinary Impact of Price to Earnings Ratios

Al's Stock Market Analysis Model: The spreadsheet containing my source data. Note that that version contains closing prices beginning in 1898, but earnings only from 1929. However, for this post, I estimated earnings prior to 1929 using data from another stock market index. If you do the calcuations using that spreadsheet you will get slightly different NPEs. From the 30th percentile down the results are the same as presented above plus or minus 0.1.

Last updated 3/22/09

Dow Price to Earnings Ratios Since 1900 - A Summary

Note: Many readers find it helpful to read
100 Years of Stock Market History (log graph), and
Dow Price-Earnings Ratios Yearly Graph first.
The significance of this post may be clearer if you read those posts first and then come back to this one.

Stock Market Price-Earnings Ratios Are Important

In a previous post, I looked at the history of stock market prices over the last 100 years in order to provide some historical perspective. Price is important. However, I would argue that value is even more important; that's the subject of this post. My objective is to provide the same kind of perspective on DJIA (Dow Jones Industrial Average) valuation that the "100 Years" post provides on price.

Whether you are buying stocks, bonds, mutual funds, houses, cars or bananas, valuation is important. By "valuation," I mean relative price, the price you pay relative to the value you get, or relative to some measure of worth. Without some way of measuring worth we can't determine whether we're getting a good price.

In the stock market, valuation is most often measured by using price / earnings ratios, that is the price of a company's stock divided by the earnings of that company. This ratio is also referred to as the earnings multiple. Other methods used to assess valuation include price / book value, price / cash flow, etc. The common thread is that price does not exist in a vacuum, it is best evaluated relative to something else; only then can you tell whether the price is expensive, about average, or cheap.

Graph of the Dollar Impact of (normalized) P/E Ratios on 10-Year Stock Market Returns

Above is a graph (click to expand) showing the dollar impact of investing at high earnings multiples rather than low earnings multiples. This should give you a feel for how important valuation (p/e) is. The graph shows the growth of three hypothetical $10,000 portfolios over 10 years:

• The "10th dectile" portfolio was invested at the average return of the highest 10% of historical P/E ratios. These are the most expensive valuations that we have experienced. That portfolio would have earned 2.5% per year and had an ending value of $12,800.
  
• The "1st dectile" portfolio was invested at the average return of the lowest 10% of historical P/E ratios. These are the cheapest valuations that we have experienced. That portfolio would have earned 13.9% per year and had an ending value of $36,750.
  
• The "5th dectile" portfolio was invested at moderate P/E ratios. That portfolio would have earned 8.9% per year and had an ending value of $23,450.

Note: For another view of the relationship between valuation and returns, see 10-Year Rollings Returns vs. P/E.

The source of the data for this graph is the table below. That table expands the analysis to cover all 10 dectiles, and time periods from 5 to 20 years.

Table Summarizing Price Earnings Ratios Since 1900

Note: the average NPE is about 15.

Relationship of Price-to-Earnings Ratios to Subsequent Returns

The table above summarizes the history of price to normalized earnings ratios since around 1900 -- over 100 years of stock market history. I have used DJIA (Dow Jones Industrial Average) data for this analysis; the results using earnings multiples from the S&P 500 would be comparable. This analysis is based upon year-end prices and normalized earnings from 1898 through 2008 (see note at end of post). The table shows:

• Dectile: Dectiles are similar to percentiles, but with the data sorted into 10 groups instead of 100 groups. The first dectile, then, is equivalent to the first 10 percentiles.
  
• Normalized price-earnings ratio (NPE): This is the ratio of year-end price to year-end normalized earnings. The numbers shown are the maximum and average NPEs for the years in each "dectile."
  
• Forward returns: The average annual return earned over the next 5, 10 and 20 years for the years in this dectile.

One striking feature of the results is the consistent increase in forward returns as you go from the higher NPE dectiles to the lower NPE dectiles. I think this data clearly demonstrates the relationship that I hypothesized in Major Bull and Bear Market Cycles Since 1900 -- namely, as a general rule, the higher the normalized price earnings ratio, the lower the subsequent returns. (Note: the discontinuity at the 6th dectile is primarily due to the fact that most of the years in the first half of the 1990s were in the 6th dectile. Therefore, their 5-year and 10-year periods ended during the most recent bull market, providing some very nice returns.) The bottom line? Ignoring valuation may be hazardous to your financial health.

In the next post I use these results to develop some worst-case scenarios by applying historic earnings multiples to recent normalized earnings.

Note regarding Normalized Earnings calculation: The normalized earnings for any year have been calculated by averaging that year's earnings with the 5 previous and 5 subsequent years' earnings. Dow earnings prior to 1929 are estimates.

Related Posts

For an index of all stock market posts, by subject area, click here.
Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History
Major Bull and Bear Markets Since 1900
The Extraordinary Impact of Price to Earnings Ratios

This article was featured in the Carnival of Investing Strategies: Number 5.
Last Updated 5/26/2009

Planning To Buy A House - Part 1

Are you getting ready to buy a new home? According to CBSnews.com, "Nearly 12 percent of all Americans with a mortgage - a record 5.4 million homeowners - were at least one month late or in foreclosure at the end of last year." This post will help to keep you from joining that group.

In a previous post, I discussed the disadvantages of buying a house. In this post, I focus on ways to reduce the impact of four of those disadvantages -- the ones that are primarily related to income and expenses:
• The risk of foreclosure
• Increased monthly expenses
• Potentially significant start-up costs
• Less predictable expenses

Prepare for the Unexpected with Insurance

Ideally, you want to be confident that you can continue to make your mortgage payments for the life of the mortgage -- no matter what. What happens if you are "sick or hurt and can't work?" This is a double-edged sword of the worst kind. Just when you are hit with unanticipated medical expenses, you are potentially facing an unexpected decrease in your income. This could be devastating. Luckily, there is a way to help protect yourself against both edges of this sword -- insurance.

Many employers provide coverage for routine medical, dental and pharmacy expenses, and "major medical" for the really big bills that would result, for example, from a hospital stay. If your coverage is not adequate, consider buying supplemental insurance. Similarly, many employers provide income continuation (disability) insurance for both temporary and permanent disabilities; this insurance provides income in the event you are disabled -- though typically you'll get 100% of your income for only a limited time. Again, if your coverage is not adequate, consider buying additional coverage. Finally, if you have a family, you'll want to make sure the bills can still be paid even if the unthinkable happens. So, because the bills will continue even if you don't, you'll need life insurance.

Prepare for the Unexpected with an Emergency Fund

An emergency fund is money set aside for, umm, emergencies. Though you have done your best to budget for anticipated expenses (see below), and insured yourself against the standard risks, stuff happens. What if you have a major uninsured or partially insured loss, or lose your job? Unfortunately, your mortgage payment will still be due. (Note: make sure you understand your insurance coverage. "Insured" rarely means 100% insured. For example, if your major medical coverage covers 80% of your hospital expenses, your share of a $25,000 hospital bill will be $5,000. )

An emergency fund of 6 months expenses, plus or minus, provides protection when there are unanticipated decreases in income or increases in expenses; it increases the chances that you will be able to continue to pay your bills, including your mortgage, even in those extraordinary circumstances. The number of months expenses funded generally ranges from 3 – 12 and depends on factors such as perceived risk of income interruptions, adequacy of insurance coverage, ease of finding new employment, etc. This money is typically kept in a savings account or money market fund.

An Effective Budgeting Process

A very important key to reducing the risks of homeownership is getting your finances under control. In my view, the foundation for this control is a reliable, proven process of annual budgeting and monthly expense control. This is where you plan your savings, the amount by which your income exceeds your expenses. Ideally, you have been able to budget your expenses accurately and to live within that budget for at least the last two years, and as a result have saved enough to make a substantial down payment and cover your start-up costs. If not, now is the time to start.

A sound budgeting process reduces the risks listed at the top of this post in several ways.

1. It puts you a better position to estimate how much your monthly expenses will increase in your new home. While some of your expenses in your new home will be new and unknown, others may remain unchanged. You will be able to predict the continuing expenses with conviction. For those that change, you will be able to make a reasonable estimate because you at least know what they used to be. Finally, your successful experience with the budgeting process will put you in a much better position to make reasonable estimates for those expenses that will be brand new.
2. Similarly, budgeting experience will put you in a better position to estimate more accurately the costs you are likely to incur at start-up.
3. While some housing expenses are “unpredictable,” they are not completely unpredictable. You know you will have unexpected expenses, you just don’t know when, why, or how much they will cost. The fact that you have a budget will at least alert you to the fact that you need to understand what the possibilities are, and encourage you to include an estimate for these items. For example, I generally include at least ½% to 1% of the value of the house per year for home maintenance. (If my expenses are under budget, I SAVE that money for the years when I will be over budget.)

In addition, I strongly recommend that you prepare a 5-year, or more, plan -- though it does not have to be nearly as detailed as your annual budget. You may even want to consider developing a personal strategic plan. This will allow you anticipate the impact of future events on your ability to pay your mortgage. Do you plan to get married? Buy a new car? Have children? Go back to school? Events such as these could significantly affect your budget. Note that if you have an adjustable rate mortgage, a multi-year plan is MANDATORY. You need to be sure that even if the payments adjust at the maximum rate until they reach the cap you can still make the payments!

Reliable Income

The less reliable your income, the more you are at risk. A steady, reliable source of income for the life of the mortgage helps to counteract the unpredictability of some of the housing expenses. If your income is unreliable, it increases the chances that at some point your expenses will exceed your income, and your risk of foreclosure will increase. Income continuation and life insurance, discussed above, are two products that significantly increase the reliability of your income.

Beyond that, your risk is lowest if you have been consistently employed for at least the last two years – preferably with the same company. The reliability of your earned income may be the factor over which you have the least control. However, even there, in the long run, you exert at least some control by your choice of career, company, industry, location, etc. To the extent that you can, it will be to your financial advantage to choose positions, companies and industries that have the best prospects of long-term employment. To the extent that the reliability of your income is beyond your control, it is important that you recognize the risk, and take appropriate countermeasures elsewhere in your plans – e.g., by increasing the size of your emergency fund.

Conclusion

For many of you, much of this probably seems incredibly pessimistic. However, 30 years is a long time. I think the chances are good that you will experience at least one of these misfortunes some time in the next 30 years; you need to be prepared.

Many people feel that a poor credit rating or FICO score is what is keeping them from owning a home; often, not having their finances under control is the real problem. Once your finances are under control, your credit rating and FICO score will naturally improve. From an income and expense perspective, having your finances under control allows you to a) accumulate a substantial amount for the down payment and start-up costs, and b) be as confident as possible that under virtually all reasonably predictable circumstances you will be able to pay your home mortgage – on time -- for the next 30 years. What’s the point of buying a house if you end up losing it in foreclosure?

Preparing for the unexpected, and having a proven budgeting process and reliable source of income are the most important factors from an income and expense perspective in minimizing your risk of foreclosure, and maximizing your chances of becoming a successful homeowner. The next post in this series will address the homeownership risks from an asset and liability perspective.

Related Materials:

Is Homeownership Right for You? from the Freddie Mac web-site.
Do You Need a Personal Strategic Plan?: They're often useful when you're considering a major change in your life -- such as buying a new home.

For a more detailed discussion of disability, medical/health and life insurance, see Consumer Reports articles on insurance.
If you are new to budgeting, consider Quicken (free on-line) or Microsoft Money personal finance software as a way to get started.
For an even more comprehensive treatment, Making the Most of Your Money, one of My Favorite Personal Finance Books, has sections on insurance, budgeting, and buying a home.
The picture is from Public Domain Pictures.

Last updated 5/22/2009

Developing Your Personal Strategic Plan

SWOTs!

This post will help you identify the critical issues and obstacles that are stopping you from realizing your dreams, AND the most important factors that are going to help you overcome those obstacles! Strategic planners call these SWOTs -- strengths, weaknesses, opportunities and threats. They're the primary data for your personal strategic plan.

Note: This is one of a series of posts on developing a personal strategic plan; the first post in the series is Do You Need a Personal Strategic Plan? If you are new to strategic planning, see A Sample Personal Strategic Plan for an example.

Identifying SWOTs (Strengths, Weaknesses, Opportunities & Threats)

If the plan is for more than one person, brainstorming is usually an effective method for identifying SWOTs. If you're "brainstorming" alone, get a pencil and paper, or 3x5 index cards, or your PC, and set aside a half-hour or so of quiet time to do some serious soul-searching. You want to generate as complete a list as you can, covering:

• Strengths -- you will need to capitalize on these to achieve your vision. For example: I have a lot of supportive friends and family; or, I make a good salary.
  
• Weaknesses -- that you must overcome. For example: I'm not very good at math; or, I need more marketing experience; or, I'm not good at time management.
  
• Opportunities -- that you need to figure out how to take advantage of. For example: housing prices are declining, so maybe I will be able to afford to buy a house after all; or, I could significantly improve my health if I changed my eating habits/ stopped smoking/ exercised more....
  
• Threats -- that jeopardize vision attainment. For example: the economy is going down the tubes and there is a chance I could lose my job; or, I'm concerned about my parents' health.

I think of strengths and weaknesses as describing where you are now, whereas opportunities and threats provide the future orientation; in a sense, they are potential future strengths and weaknesses. In the spirit of brainstorming, try not to censor your thoughts too much. "I'm not very good at math" may seem irrelevant if your vision is to become a ballerina or NFL quarterback, but may turn out to be relevant when you think seriously about your financial goals.

Sources of SWOTs

Most of your SWOTs will come from:

• Your overall (general) strengths, weaknesses, etc.
  
• Thinking about your dreams, and SWOTs specifically relevant to each of those dreams
  
• The other major aspects of your life even though they may only play a "supporting" role -- e.g., "fun," or "health" (see Discovering Your Vision for a "starter" list of areas to consider)

Try to identify SWOTs not just from your own point of view, but from other peoples' points of view as well. What would your family and friends say? How about current and potential employers, and co-workers? What changes can your reasonably anticipate in your life in the next 5 years? For example, might you get married, buy a new home, have children? What emerging economic or social trends could affect your plans? Contemplating changes such as these can generate a new wave of SWOTs. Any perspective is useful if it helps you unearth additional SWOTs. This is all fodder for your plan.

There is no right answer for how much time to spend. If you're still coming up with good ideas after a half-hour or so, continue; if not, it's time to stop (but, feel free to come back and add more SWOTs later).

Refine Your Vision

As you discover SWOTs, your dreams will become clearer; update your original "vision" drafts as you go along. The revised descriptions of your dreams will often help you discover even more SWOTs. Get all those things you have been thinking about doing (and stopping!) "someday" out on the table.

One last thought -- be honest -- maybe even brutally honest. In many ways, the process is as important as the final product. Done properly, this process can help you surface issues that you have swept under the rug -- maybe hoping that if you ignore them they will go away; it can also help you recognize strengths and opportunities that you are taking for granted.

Prepare Your Plan for Success

To convert your SWOTs into a plan that maximizes your strengths, takes advantage of your opportunities, overcomes those pesky obstacles, and gets you on the path to realizing your dreams, Create Your Personal Strategic Plan.

Previous Posts in This Series

A Sample Personal Strategic Plan
Do You Need a Personal Strategic Plan?
Discovering Your Vision
The picture is from Public Domain Pictures.
Last modified 6/24/2009

Discovering Your Vision

It All Starts With Your Dream

Personal strategic planning starts with a dream. As they sing in the musical South Pacific, "You got to have a dream. If you don't have a dream, how you gonna have a dream come true?"

Actually, many people have several dreams. In this post, we'll identify your dreams; those dreams are the foundation for your strategic plan.

Note: This is one of a series of posts on personal strategic planning. If you are unfamiliar with this process, see A Sample Personal Strategic Plan for an example.

When I am helping organizations develop strategic plans, we try to develop a single, unifying, overriding vision for the organization from which everything else flows. For example, "We will be the number one widget-maker in Texas." This vision is the ultimate reason for everything they will do for the next 5 years. This approach also works for some people -- at least at some point in their lives; the desire to become a ballerina, or NFL quarterback, or neurosurgeon can be all-consuming. However, for many people, there is no single, unifying, overriding vision -- at least not initially.

Sources of Passion and Dreams

To begin your personal strategic plan, think about the major aspects of your life -- family, friends, fun, finances, career and/or education, home, community (not necessarily local, and not necessarily geographic), physical, mental & spiritual health .... Which of these areas are the sources of your inspiration, your passion? In which areas do you have dreams that are powerful enough to light a fire under you? You want mental pictures that are strong enough, motivating enough, so that you can't wait to start working toward them each day. They should be your primary "drivers" for the next 5 years, the ultimate reason for almost everything you do! For each of your 1-5 critical areas, draft a "vision" describing your dream -- not a detailed description, just enough detail so that you remember what it is. For example, "To be valedictorian of my class," or "Help my son get off drugs and become a happy, well-adjusted, productive adult."

I think of the remaining areas as support areas; they're important to you only because they help you achieve your real dreams. For some people, the financial vision is a critical one; for others, money only matters because they need enough so that they can paint -- or dance. For most 20 year olds, health is not a priority; they don't start each day thinking how can I improve my health today. However, if you had a heart attack 6 months ago, health is probably one of your critical areas.

Make it Yours

Feel free to combine areas or add new ones. For example, you might group career, education and community together and call it "fulfillment." Note also that there is nothing magic about 5 years. Look for a natural ending point. For example, if you're just starting college, a 4-year plan may make more sense; if you have young children, you might want to plan through the date when the youngest graduates from college. The point is, there is no one right answer; they're your dreams.

Start Planning to Have YOUR Dream Come True

So, what's your dream? To be debt-free and living within your income? To be accepted by, and graduate from, an Ivy League medical school? To lose 50 pounds? To play first violin in the New York Philharmonic? Remember, as Daniel Burnham said, "Make no little plans; they have no magic to stir men's blood...."

To begin planning to have your dream come true, start Developing Your Personal Strategic Plan.

Related Posts:

Other posts in this series include:
A Sample Personal Strategic Plan
Do You Need a Personal Strategic Plan?.
The picture is from Public Domain Pictures.

Last updated 6/5/2009

Do You Need A Personal Strategic Plan?

Personal Strategic Planning Can Change Your Life

Not many years ago, a friend confessed that she was less than thrilled with her career. This came as a surprise to me since she was a young, up-and-coming professional earning a good salary. However, she confided, her real dream was to become a doctor. This is probably not a career her college science professors would have recommended; she had not done well in their classes.

Three years later, after completing the required pre-med science courses with a better than 3.5 gpa, she was in med school. Four years after that, she was a doctor. She is now living her dream.

Why was she successful? She had a compelling dream; she worked hard; and, she had a personal strategic plan.

What is A Personal Strategic Plan?

A personal or family strategic plan is a high-level plan for achieving your most important life goals -- for realizing your aspirations. At its simplest, the plan includes a description of a "desirable future," your goals and dreams, and the key steps you plan to take in order in order to make those dreams a reality. It really boils down to just two things:

1. Where do you want to be 5 years from now?
2. How do you get there from here?

Note: If you are not familiar with strategic planning, see A Sample Personal Strategic Plan for an example.

Why Do You Need A Personal or Family Strategic Plan?

The short answer is because, like my friend, you want to live your dream. To maximize your chances of success, you need a plan because, as the old saying goes, "failing to plan is planning to fail."

Developing a plan helps you set priorities and focus your resources -- time, money, energy, attention -- where they will do the most good; a plan helps you make better decisions and take the actions that will get you where you want to go.

When Do You Especially Need a Strategic Plan?

A plan is especially important if you are contemplating a new direction that could change your life forever -- such as:

• Planning for college or graduate school
  
• Beginning a new job or career, losing your job, retiring
  
• Buying or selling a home, foreclosure
  
• Major financial windfall (e.g., inheritance), bankruptcy
  
• Marriage, divorce, birth/adoption, death in the family

However, a plan is also useful if:

• You are less than ecstatic about the status quo. Your life is ok, but you want more. Or, worse yet, you are unhappy with your life.
• Or, even... Your life is good, but you want great; you're tired of settling for "good enough."

What Should Your Strategic Plan Contain?

The most important element of your plan is usually called a Vision; it is your ultimate goal, your dream. Whether your vision is to become a Pulitzer Prize winning novelist, or "just" to have a happy, well-adjusted family, it all starts with your dream. As the old saying goes, "If you don't know where you're going, any road will take you there." However, you can't stop with your vision. If you stop there, it really is just a dream.

The question is how do you get there from here? You need a roadmap. This is where your dream turns into a plan. What's important is that you identify what's working and what's not working in your life, the critical issues that need to be addressed, the obstacles that need to be overcome, the results that need to be achieved, and come up with a plan to make your dream reality. There is no magic. You have to make it happen, just as my friend did, with a compelling dream, hard work, and a plan.

Start Planning to Realize Your Dreams

So, how about you? Do you have a dream? Do you want to start living your dream just as my friend is living hers? If so, click here and get started now.

Related Posts:
See A Sample Personal Strategic Plan for an example.

Last modified 5/23/2009

Major Bull and Bear Markets Since 1900

I always find it instructive to look at the extremes. So, in this post I will look at the best and worst periods in the last 100 years or so of stock market history -- the secular bull and bear markets. By "stock market" I mean the major U.S. indices such as the DJIA (Dow Jones Industrial Average) and the S&P 500 Index.

Secular bull markets ultimately lead to a market top. I think of the periods that have followed as periods of disinterest. These are long periods where the market fails to reach a sustainable new all-time high. These long flat periods are where we typically see the major bear markets and stock market crashes -- though, interestingly, the crashes do not always immediately follow the peaks; some bubbles burst, others seem to just fizzle out.

Three Secular Bull and Bear Market Cycles

In my view there have only been three major, secular bull and bear market cycles in the last 100 years: (For this discussion, you may want to reference the graph of closing prices in 100 Years of Stock Market History.)

1. The 1920's bubble that burst in 1929 (see graph in this post). The Great Depression followed; during that stock market crash, the market went down every year until it bottomed in 1932. It took about 25 years for the stock market to close the year above the 1928 close.

2. The post WWII bull market that peaked in 1965. It took 17 years (1982) until the market permanently eclipsed the 1965 close. However, if you look at the graph in the 100 years post, you won't see anything nearly as dramatic as the post-1928 crash. The market looks pretty flat, with the largest decline not occurring until '73-'74 (that, trust me, felt like a lot worse bear market than it appears to be on the graph).

3. The bull market that began around 1982; it was the longest in history. The dot-com/internet bubble topped out in 1999. The bubble burst in a manner similar to the 1929 market crash, and reached a temporary bottom in 2002. However, it's not yet clear how this cycle will play out. We don't yet know when we will permanently close above Dow 11,500; nor is it clear where the cycle will bottom out.

What Can We Learn From Analyzing the Bubbles and Crashes Since 1900?

Note: To get a feel for the difference in 10-year returns in dollars, see the graph in this post.

The above table (click to enlarge) summarizes some information about the best and worst periods in stock market history that I found useful. You could argue that since I've only included known peaks and troughs it doesn't tell us much that we didn't already know. Obviously, the 5 and 10 year forward returns from a peak are not likely to be very good; similarly, the returns from permanent bottoms cannot be negative. However, it was useful to me to quantify the difference between the tops and bottoms.

Peaks, Troughs and P/E Ratios

Most striking is the difference in NPE, or normalized price/earnings ratios. (Note: For more on NPE, see About Normalized P/E Ratios.) If you divide the 76 years for which I have calculated NPEs into 10 groups (dectiles) according to increasing NPE, the really major peaks are in the top two (9th and 10th) dectiles. The two major bottoms are both in the first dectile. The highest NPE ratio (33) is close to five times as large as the smallest (7). I think it's fair to say that the best and worst years provide at least anecdotal evidence that valuation is critical. History, at least since 1900, shows that holding periods beginning in times of very high NPEs show poor returns; holding periods beginning in times of very low NPEs tend to show superior returns.

Because this is year-end data, the 2002 trough is somewhat understated. The actual low in October was around 7300. Even so, the NPE of 16 would only be a 7th dectile reading. Perhaps that's why the 2002 bottom did not prove to be an enduring one.

Note: The above table is in the Benchmark Dates tab of the Stock Market Analysis Model. I will add some additional benchmarks and discuss them in a future post.
Note2: If you see ##### in any fields, click on the field, hit F2 and then enter.

Related Posts:

For an index of all stock market posts, by subject area, click here. In addition to the links above, posts that may be of special interest include:
The 1929-1932 Stock Market Crash Revisited: Perhaps the ultimate bear market.
The Extraordinary Impact of Price to Earnings Ratios.
Dow Price to Earnings Ratios Since 1900 - A Summary

Last updated 6/15/2009

The Extraordinary Impact of Price to Earnings (P/E) Ratios

Key Components of Annual Stock Market Returns

In the most recent post in this series, I introduced a stock market analysis model/spreadsheet that allowed us to analyze the contribution that earnings, dividends and the change in price-to-earnings (p/e) ratios made to the performance of the Dow for any period during its more than 100 year history. As an example, we looked at DJIA (Dow Jones Industrial Average) total returns from 1994 to 1999 and observed that a large percentage of the annual return during this exciting period was due to an increase in the price/earnings ratio. This is sometimes called an increase in valuation, or earnings multiple expansion.

Is this typical in stock market history? Does a bear… Oops. How about “You betchum, Red Ryder” instead (if you have no clue who Red Ryder was, you can just ignore that comment). The variation in yearly returns is dominated not by earnings or dividends, but by valuation, by expansion and compression of the earnings multiple – though not typically to the extent that we saw in the bull market of the 1990s. On the other hand, in some ways the extremes give us the best clues about what’s really going on.

The Historical Impact of Price to Earnings (P/E) Ratio

The above graph (click to enlarge) is a close to 100 year history of this phenomenon. It breaks out the contribution to annual stock market return that came from normalized earnings (NE), dividends and the change in the normalized price to earnings ratio (NPE) from 1930 to 2003. It tells the same story. Historically, looking at year-to-year changes, the impact of expansion and contraction of the earnings multiple -- the white bars in the chart -- dwarfs the impact of changes in the earnings and dividends. In the long term, of course, that can't be true; in the long run earnings and dividends dominate.

Analyzing the Stock Market Crash 1929-1932

The screen shot below (click to enlarge) is from the same model, and focuses in on the stock market’s performance between 1929 and 1932. (Note: see this post for a more detailed graph of the 1929-32 crash.) The period leading up to 1929 was very similar to 1994-99. However, the 1929-32 period is in many ways the opposite; the stock market crash in 1929 was the beginning of the Great Depression. During this three-year period, investment portfolios lost an average of about 32% per year; a $3,000 portfolio would have been reduced to less than $1,000. It would have been worse if investors had not earned about 5% per year in dividends.

Notice, though, that only about 1% of the yearly loss was attributable to the change in normalized earnings! The decline in yearly (non-normalized) earnings was, of course, much more dramatic – earnings went from almost $20 to a loss of about $0.50. You could make the argument that more than 100% of the change in the Dow’s price from 1929 to 1932 was the result of changes in valuation. The normalized price/earnings ratio, or the ratio of price to normalized earnings, went from approximately 29 -- to 7; the (normalized) earnings multiple declined by over 36% per year, whereas total return was down “only” 32.5% per year.



Note that while this is Dow Jones data, the results for the S&P 500 are essentially the same. I don’t know anything about electrical engineering, but if I did, I'm guessing I’d be writing something about signal-to-noise ratios….

Here is a link to the current Stock Market Analysis Model mentioned in the intro (see the Historical Analysis tab). I will add additional features (tabs) to the model, and continue the analysis in future posts.


NOTE: This is still a test version. Especially, I’m sill having problems converting from Excel to Google Spreadsheets and back. When you first open the model on the Historical Analysis tab, you may see ###### and #VALUE! in some cells. Click on these cells one by one, starting in the upper left and ending in the lower right, and hit the F2 key and then the Enter key for each; the correct numbers will magically appear. There are also some minor formatting issues. If anyone has any idea why this is happening, please let me know.

RELATED POSTS

Major Bull and Bear Markets Since 1900: The next post in this series.
Dow Price to Earnings Ratios Since 1929 - Yearly Graph
Dow Price to Earnings Ratios Since 1900 - A Summary

For an index of all stock market posts, by subject area, click here.

Updated 4/16/2009

This post has moved

This post is now here.

Stock Market Spreadsheets Navigation Guide

Some people are apparently having trouble navigating the site to find the information they are looking for. This is partly because, for some queries, Google does not rank my posts in the most useful sequence. So, my most relevant post may be the second or even third post returned. This post will help you understand what data is in each spreadsheet, and which posts reference that data.

Dow Data

Key Data contained:
Yearly closing prices from 1901-2008 (using 10/10/08 for 2008 close); Earnings from 1929-2007; Normalized earnings.

Posts that reference this spreadsheet:
100 Years of Stock Market History (log graph)
Stock Market Earnings History, Average Returns, and a Worst Case Scenario

Stock Market Analysis Model

Key Data contained:
Yearly closing prices from 1897-2008; Earnings from 1929-2008; Normalized earnings; Normalized price/earnings ratio; Dividends from 1929-2008; Dividend yield; Annual total return; Annual return by major component (earnings, dividends, change in price/earnings ratio).

Posts that reference this spreadsheet:
Analyzing and Understanding 100 Years of Stock Market History
The Extraordinary Impact of Price/Earnings Ratios
Major Bull and Bear Markets Since 1900
Dow Price to Earnings Ratios Since 1900 - A Summary
Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History
Dow Price to Earnings Ratios since 19xx - Yearly Graph
Dow at 25-Year Moving Average
Stock Market Average Annual Return since 19xx
Stock Market Yearly Returns since 1929
The Best & Worst 10 Years in Stock Market History
The Best & Worst 20 Years in Stock Market History
The Best & Worst 5 (and 50) Year Returns in Stock Market History
Range of Stock Market Returns for 1-100 Year Holding Periods
Stock Market Rolling Returns vs. Price to Earnings (P/E) Ratio Graphs
Stock Market Normalized Earnings and Returns

Last update 6/18/2009

Analyzing & Understanding 100 Years of Stock Market History

Note: Many readers find it useful to read 100 Years of Stock Market History (log graph) for the perspective it provides before reading this post.

Understanding the Stock Market

The attention my 100 Years of Stock Market History post has received has made it clear to me that, because of the current volatility in the stock market, there is great interest in trying to get a broader perspective on the stock market. I think people are trying to understand the stock market (I know I am). To really understand the stock market, just looking at a graph of 100 years of Dow Jones history is not sufficient; we need to analyze it; we need to figure out “what makes the stock market tick.”

The objective of my Stock Market Analysis Model is to gain a better understanding of the performance of the Dow Jones and S&P 500 stock market indexes over time. The presumption is that earnings, dividends, and price/earnings ratios are the primary levers that drive performance. The model allows us to approximate the contribution of each of those components for any given period in the past. (Note: I may add additional “levers” in the future.)

Ten Questions the Stock Market Analysis Model Will Help You Answer

Here are some of the many questions this model can help us answer:
1. What was the DJIA’s (Dow Jones Industrial Average) average return between 1929 and 2002 (or for any other period)?
2. How much do dividends matter?
3. How can I tell if the stock market is undervalued (cheap) or overvalued (expensive)? What is the impact of stock market valuation (e.g., price/earnings ratio)?
4. What was the relative contribution of earnings, dividends and price/earnings ratio increase/decrease to the stock market’s performance between 1994 and 1999 (or for any other period)?
5. What is the long-term average performance (annual return) of the stock market?
6. What is the Dow’s earnings history? What's the average long-term earnings growth rate?
7. What were the best/worst 10 or 20 years in stock market history?
8. What is the cheapest the market has ever been? Where would the Dow be now if it were valued that cheaply?
9. Does it matter when I buy? If so, when is a good time to buy, and when is not so good?
10. After a market peak, what is the longest it has taken to regain that level? (I call these long flat periods “periods of disinterest.”)

Al's Stock Market Analysis Model (click to enlarge)

Analyzing the Bull Market From 1994 to 1999

The screenshot above (click to enlarge) shows that the Dow returned 26.9% per year between year-end 1994 and year-end 1999. (The annual returns ranged from a high of 37% in 1995 to a low of “only” 18% in 1998.) If you had invested $25,000 at year-end 1994, and re-invested dividends, by the end of 1999 your investment would have more than tripled -- to more than $80,000. It was definitely what I call a "period of excitement."

(Note: in my current methodology, I normalize earnings for each year by averaging those earnings with the five prior years and the five following years. The normalized price earnings ratio --NPE-- is the ratio of closing price to normalized earnings. For a more detailed discussion, see About Normalized Earnings and P/E Ratios.) Now, the not so good news. The biggest contributor to the returns was an increase in price/earnings ratios. In fact, 14.4% of the 26.9% annual return was due to an increase in the NPE; it increased from 15.3 to 28.3. Normalized earnings grew at 10.2% -- considerably higher than the long-term average of around 6%. However, a contributor to this increase was, believe it or not, earnings associated with appreciated stock holdings. Thus, we had the makings of a perpetual motion machine -- increasing prices increased earnings, which increased prices, which.... Finally, dividends contributed less and less as the market went higher.

At the end of this period, the dividend yield was at an all-time low of 1.5% and the NPE was an all-time high 28.3. If you had known all this in 1999, might you have done something different from what you actually did at the time? ….. Yeah, me too.

Here's Al's Stock Market Analysis Model (see the "Historical Analysis" and "Dow Data" tabs).

I will add some additional features (and tabs), and continue the analysis in a future post. Meanwhile, if you discover anything interesting about the stock market by playing with the model, or find novel uses for it, please let us know.

NOTE: This is still a test version. Especially, I’m sill having problems converting from Excel to Google Spreadsheets and back. When you first open the model on the Historical Analysis tab, you may see ###### and #VALUE! in some cells. Click on these cells one by one, starting in the upper left and ending in the lower right, and hit the F2 key and then the Enter key for each; the correct numbers will magically appear. There are also some minor formatting issues. If anyone has any idea why this is happening, please let me know.

Related Materials:

The Extraordinary Impact of Price/Earnings Ratios: The next post in this series.
The Crisis: A Contributing Factor: Discusses, among other things, the impact of investors not investing based on valuations.

The following describe similar methodologies for approaching stock market valuations. From a “big picture” point of view, they arrive at similar conclusions.
Bogle on Mutual Funds, by John Bogle: Analysis is based on S&P 500; uses dividends rather than earnings.
The Likely Range of Market Returns in the Coming Decade, by John Hussman (February, 2005): Analysis is based on S&P 500; normalizes earnings by using “peak earnings.” (Note: More technical than the others.)
Irrational Exuberance, by Robert Shiller: Analysis is based on S&P 500; normalizes using prior 10 years’ earnings; adjusts for inflation.

Note: The S&P 500 is clearly a better foundation. However, when I started this analysis in the 1990s, I only had DJIA data. Will probably switch at some point.

Last updated 6/15/2009

My Favorite Personal Finance Books

Every once in a while someone asks me to recommend some good books on personal finance. Here are some of my favorites.

General Personal Finance Books

These books cover the waterfront: budgeting, insurance, buying a house, investing, retirement planning, wills -- you name it.
Making the Most of your Money, by Jane Bryant Quinn

Basic Books About Investing

Barrons Guide to Making Investment Decisions, by Douglas Sease and John Prestbo: A nice overview of all asset classes (stock, bonds, real estate, etc.), but you may have trouble finding a copy these days.
A Random Walk Down Wall Street, by Burton Malkiel. Good explanation of modern portfolio theory (how to construct an investment portfolio) from one of the major proponents of index investing. Some parts are a bit technical.
Bogle on Mutual Funds, by John Bogle, founder of The Vanguard Group. Excellent book on investing in stock and bond mutual funds. Aims "to provide the same sort of framework for investing in mutual funds as Benjamin Graham provided for investing in individual stocks and bonds."
The Intelligent Investor: This classic, by Benjamin Graham, "the father of value investing," is oriented towards stock, not mutual fund, investing. Never the less, it's still relevant background for mutual fund investors.

Books About Behavioral Economics

The biggest financial mistakes I see people make are not caused by their deficiencies in accounting. These books deal with “the psychology of money.” This emerging field is sometimes called behavioral finance.

Extraordinary Popular Delusions & the Madness of Crowds, by Charles MacKay. This 1841 classic reviews bubbles of all kinds (real estate, stock, ...) from the beginning of time (well, almost).
Irrational Exuberance, by Robert Shiller. This one focuses on more recent real estate and stock bubbles. Apparently, not enough people read Charles MacKay....
Fooled by Randomness, by Nassim Taleb. Fascinating book about the misunderstood role that chance plays "in life and in the markets." Not very well written, but was a best-seller anyway. That ought to tell you something.
Why Smart People Make Big Money Mistakes and How to Correct Them, by Gary Belsky and Thomas Gilovich. "A terrific introduction to the emerging science of behavioral finance, which identifies the ways in which investors' minds play tricks on them." (Money Magazine)
Note: the last one is the only one that is "officially" from the field of behavioral economics, but I think the others are equally appropriate.

Happy hunting!

Last modified: 4/12/09

What's a Model?

DRAFT

I recently updated my blog description and the “About This Site” post to include the word “models.” What, you may ask, is a model?

From Dictionary.Com:

a simplified representation of a system or phenomenon, as in the sciences or economics, with any hypotheses required to describe the system or explain the phenomenon, often mathematically.

Got it? For example, I think of physics as a model of certain physical phenomena. Some decades ago, I often described a model as something used instead of something else, which replicates the important aspects of that “something else” for your purposes. Point being, that whether “A” is a good model of “B” depends on your objectives. One of my favorite examples was mannequins. For a tailor, a mannequin is a very good model of a young lady. In some ways, mannequins might even be better than the real thing – they don’t get tired, it doesn't hurt when you stick them with a pin, etc. However, as a thirty-something year old man, I found them a totally inadequate substitute for my purposes.

Often, mathematical models allow you to analyze the behavior of whatever you are modeling in ways that would be impractical in real life. For instance, with the proper model, you could model how a plane would behave in a crash and save yourself the expense of actually crashing planes. Closer to home, a budget is a model of your finances. So, you could examine how buying that Porsche you saw the other day would affect your finances without actually spending the money. Better to find out on paper that buying it is a bad idea than having to learn the hard way.

Models are very useful tools for analysis and planning, two things that I enjoy doing, and building them is an exercise in design (which I enjoy as well). Modeling ties three of my passions together.

Anyway, this is just a heads up that I will be posting models from time to time. For a very simple example, see the stock market spreadsheet referenced in one of my earlier posts.



p.s. For those readers who have been wondering why I haven’t posted in over three weeks, it’s because I’ve been hard at work developing a model that I will be posting soon.

Three Scenarios for the Stock Market (and the Economy)

Which way are the economy and stock market going to go? Up? -- or down. And, how far? Since the future is unknowable, rather than planning for a single future, strategic planners find it useful to develop multiple scenarios. Typically, one develops 3-5 scenarios covering a wide range of possible futures. In this post, I outline (literally) three scenarios that I think are representative of the range of possible outcomes of the current financial/economic crisis. They range from “Business as Usual,” the best-case scenario, to “Snowball,” the worst-case scenario. The “descriptions” help me to visualize a future environment so that I can conceptualize plans suitable for that scenario.

I apologize for the lack of prose, but the outline form may be clearer. Equally importantly, I don’t have time to make it "flowery." Note that these are preliminary descriptions and I may update them periodically.

Business As Usual Scenario

It’s always helpful to have a “status quo” scenario; this is also my best-case scenario. In essence it says this economic “crisis” will turn out to be just another one of our normal, periodic recessions. That is, we will have a recession that is the same “ballpark” in magnitude and duration as those of last 30 years or so.

We learn from, and avoid, policy errors made during the Great Depression and the collapse of the Japanese housing and stock markets.
...Avoid runs on banks and their equivalents
...Bernanke’s in-depth knowledge of the Great Depression pays off
We learn from past successes
...Swedish success in dealing with their banking crisis in early 1990s.
The unprecedented global cooperative intervention continues and is successful
We minimize job losses and their impact on spending.
...Create new jobs in infrastructure, alternative energy, education, etc.
...Unemployment insurance, possibly extended, cushions the blow
We are able to quickly
...Restore confidence to lend
...Restore consumer confidence to spend
...Reduce foreclosures to normal levels and stabilize the housing market
The stock market recovers in about same length of time as after dot-bomb era.

Headwinds Scenario

This scenario assumes it will not be business as usual; on the other hand, the crisis will not snowball out of control. The economy is severely injured and the stock market faces “headwinds” for an extended period.

Stock market earnings -- Decreased income
Reduced levels of consumer spending (~70% of GDP)
...Slow wage growth -- minus increased savings, paying off credit card debt, re-paying the equity taken out of homes, etc.
...Negative wealth-effect caused by reduction in value of homes & stocks
...Higher taxes and/or lower government benefits
...Less confidence
Reduced corporate spending & investment because of low consumer sales
Reduced state & local government spending because of reduced tax revenue

Stock market earnings --Increased expenses
Higher cost of credit (and equity)
Higher taxes and new regulations
Stronger unions
Higher medical costs, under-funded pension plans

Low Stock market P/E (price/earnings) ratio
High risk premium
Supply/demand: Reduced demand caused by de-leveraging by hedge funds and investors, and lack of confidence
Rising interest rates (though not immediately)
...At minimum, removal of the interest rate tail-wind

Snowball Scenario

This is the worst-case scenario. As the name suggests, it assumes that we are unable to short-circuit most or all of the following self-reinforcing cycles.

Job losses->fear->reduced spending->job losses
Job losses->foreclosures->lower home prices (& bankruptcies)->reduced spending->job losses
Job losses->lower state and local tax revenues->reduced services and job losses
Lower home prices->hopelessly negative home equity->bankruptcies/turn in keys->lower home prices
Stock market losses->reduced spending->job losses
Lower stock market->selling (and lack of buying)->lower stock market
Unwilling to lend->companies fail (= loss of jobs & loss of sales for their suppliers)->less willing to lend (credit less available, and only at high rates)
Hedge funds redemptions/de-leveraging->equity sales->lower prices->more hedge fund redemptions (note: they’re highly leveraged)
Lack of confidence->poor economy & stock market->lack of confidence
Deflation->fear of buying/wait for better price->deflation
Protectionism/nationalism->protectionism/nationalism
Every man (company, and country) for himself/ lack of cooperation->retaliation

Conclusion

So, where is the market going from here? No one knows for sure. However, it is helpful to be aware of the possibilities, and to develop plans that take those possibilities into account. Typically, the plans should be tilted toward the most likely outcome, but permit one to survive even in the event of the worst outcome. At this point, I think the “Business as Usual” scenario is the least likely of the three; the “Headwinds” scenario is the most likely. “Snowball” is somewhere in between.

The previously posted Worst Case Scenario can be thought of as “quantifying” the “Snowball” scenario. In that post, I calculated a worst-case value for the DJIA (Dow Jones Industrials Average) based on valuations seen during previous extreme bear markets such as the crash associated with the Great Depression. Note, however, that there can be degrees of “snowballing.” The more the factors above continue to snowball, the closer we are likely to approach those extremely depressed levels. With minimal snowballing, the Snowball scenario morphs into "just" Headwinds.

This is intended to be a preliminary, and high level, look at the possibilities. I welcome comments on important factors that you think I have omitted or misrepresented.

Recommended Articles:

Stock Market Earnings Growth History, Average Returns, and a Worst Case Scenario
Worst-Case Scenarios Based on 100 Years of Dow Price/Earnings History
The 1929-1932 Stock Market Crash Revisited
Will the U.S. Bank Re-Capitalization Work? Lessons from Japan: A fascinating, and somewhat disconcerting, 40 minute video presentation by Professor Anil Kashyap of the University of Chicago Booth School of Business. Explores similarities between the U.S. in 2008 and the Japanese experience in the 1990s -- and lessons to be learned from their experience. There are two links after you get to the site: one to the video; a second to a PDF file with the associated 20 pages of slides (which may be viewed while listening to the presentation, or separately).
Dow 5,000 Redux: Bond guru Bill Gross' assessment of the investment outlook as of December 2008. He discusses many of the factors mentioned in this post, but more eloquently.
8 really, really scary predictions (their words, not mine) from Fortune magazine's 2009 forecast issue. Prognosticators incluse NYU economics professor Nouriel Roubini, aka Dr. Doom, Bill Gross, Robert Shiller, and others.
Jeremy Grantham's January, 2009 Quarterly Letter: The second section compares the current financial crisis to both the Japanese experience in the 1990s and the Great Depression.

2009: The Emerging Picture (Selected Articles)

California risks "insolvency" amid budget woes: Reuters, Jan 15
Buy American Once Again: Gary Becker's February, 2009 article on the re-emergence of protectionism.
Brighter Days Ahead: Barton Bigg's March 2009 Newsweek article.
On the Urgency of Restructuring Bank and Mortgage Debt, and of Abandoning Toxic Asset Purchases: John Hussman's March 30 newsletter.
The Last Hurrah and Seven Lean Years: Jeremy Grantham's 1Q09 newsletter. Assigns probabilities to various outcomes. (Note: requires subscription, but it's free.)

Note: Additional articles with varying viewpoints will be added as I discover them.

Last modified 5/28/2009
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The Crisis: A Contributing Factor

As a result of the current financial crisis, there is a growing consensus that the government “dropped the ball.” (See, for example, Michael Grynbaum’s article in the October 24 New York Times.) In other words, the government itself is one of the causes of the crisis it is now attempting to resolve. In particular, the accusers argue, the government is at fault because it did not provide adequate oversight of our financial system. Generally overlooked are more subtle contributions to the current economic crisis, and to the associated stock market crash – some government “sponsored”, some not.

What do the following developments of the last half-century or so have in common?
1. Mutual funds
2. Modern portfolio theory and index funds
3. Deregulation of the stock brokerage industry
4. No-load mutual funds
5. Tax sheltered accounts (e.g., IRAs)

Each of the above was hailed, at least to some extent, as giving the general public broader access to the potential riches of the stock market. Largely because of these developments, over the last 50 years the public’s participation in the stock market has increased dramatically. Unfortunately, they have also inadvertently combined to engender some profound, and somewhat disturbing, changes in the investment landscape.

Then and Now

In Business 101, my first business course in college, I learned that the stockholders own corporations; the CEO reports to the board of directors who, in turn, “report” to the stockholders. The stockholders have the ultimate authority and provide the ultimate oversight. In my early days as an investor, I owned stock in three companies. I carefully reviewed every quarterly and annual report, and attended every annual meeting. I did this partly out of a sense of responsibility, and partly because if any one of those companies performed poorly it would have a significant impact on my net worth.

In addition, in those days, it was expensive to buy and sell stocks – especially in small amounts. Selling was especially expensive because in addition to paying a commission on the sale, any gains were taxable. The high transaction costs associated with buying and selling acted as a barrier to market participation by the general public; they also encouraged those that did buy to hold their shares for long periods of time – generally years.

Now, most investors own more mutual funds than I owned stocks. Via their mutual funds, most investors own shares in scores of individual companies. The barriers to buying and selling have virtually disappeared. You can buy or sell an unlimited number of shares of stock through a discount broker for less than $10; mutual fund loads are often low or non-existent. Finally, the majority of the average investor’s sales are tax-free since they take place in tax-sheltered accounts.

Unintended Consequences

One result of these developments is decreased stockholder oversight. Via their mutual funds, many investors own (a relatively small number of) shares in literally thousands of individual companies. Investors cannot have the level of understanding of, and commitment to, their holdings that I once had. I think it is likely that this reduced attention has contributed to the escalation in “risky behavior” on the part of our corporations. It may well have contributed to the escalation in executive pay as well. Could it be that through such broad diversification we have reduced company and industry risk in our portfolios, but unwittingly contributed to the creation of a new kind of risk -- “oversight risk”?

Another result of these developments is increased volatility. Because stockholders know less about and are less committed to the companies they own (directly or indirectly through mutual funds), and because transaction costs are low, the average holding period has decreased dramatically. Partly because investors know little about the companies they own, there is less emphasis on fundamentals, and more emphasis on momentum. We are replacing long-term investors with speculators. In many cases, it would be more accurate to say that individuals bet on, rather than invest in, companies. The result is “hot money” that moves rapidly into whatever asset class, or sub asset class, is in vogue. Since the influx of new money causes prices to rise, the process is self-reinforcing. The result is increased volatility, and asset “bubbles.” Finally, when valuations reach unsustainable levels, crashes inexorably follow as the self-reinforcing process reverses itself.

Theoretically, the mutual fund managers could assume much of the old oversight role; in the real world, few do. Similarly, they have probably increased rather than muted stock market volatility. According to Morningstar, the turnover ratio for the average mutual fund is close to 100%. That means the average holding period is approximately one year – hardly long-term investing.

In summary, developments over the past half-century or so have dramatically increased the general public’s participation in the stock market, as was presumably intended. However, some of the side effects are disturbing. I am not suggesting that these well-intentioned developments are the cause of the current economic crisis or of the stock market crash. However, I do believe they deserve a share of the blame along with investors, fund managers, and many others. The changes have helped cause the situation by effectively reducing the oversight historically provided by the stockholders, and fostering speculation rather than investing. This in turn has resulted in increased risk-taking, increased market volatility, and an increase in the frequency of “asset bubbles” – and their aftermaths.

Related reading:
Public Policy Matters After All, Columbia Journalism Review
The Financial Crisis: the Role of Government, The Becker-Posner Blog
The End of the Financial World as We Know It: New York Times Op-Ed piece by Michael Lewis and David Einhorn.

Last Updated: 1/25/09

VOTE (quickly)

My guess is that urging people to vote in this year’s election is “preaching to the choir” -- so, I won’t bother. Voters have turned out in record numbers across the country to vote early. Yet, there is the possibility that there may still be record numbers remaining to vote on Tuesday.

I believe that diversity is a good thing. Too much agreement often leads to sloppy thinking; disagreement leads to better decisions. Partly to encourage this diversity of thought, my completed ballot is often a hodgepodge of democrats, republicans, and an occasional minor party candidate or two. In the past, this has meant that I have often spent an inordinate amount of time in the voting booth. Recently, my hogging the voting booth has not been a problem since there have always been open booths available for the voters behind me.

However, this year, to do my part in speeding things along, I will be filling out a sample ballot beforehand. I have already spent more than 20 minutes completing my sample ballot. That’s 15 minutes less that I will need to spend in the booth. If you are a “booth hog” like me, as a courtesy to those behind you, I urge you to plan ahead and make your decisions before, not while, you’re in the booth – especially if you’re in line ahead of me.