Why not just buy low and sell high? That’s easy enough, right? The classical answer is a resounding no and there are reams of analyses to prove that it’s not a good idea to try to do this. Most arguments against timing make the case that the market is extremely volatile and impossible to predict. It’s extremely easy to miss the best performing days and if you do you will have substantially worse performance than if you had stayed in the market the entire time. I’ve seen many variations of the following analysis [1] over the years:

The bottom line of this analysis is supposed to be that unless you have a crystal ball you are going to miss major upward market moves and you will seriously undermine your returns. In fact, in 1975 William Sharpe published a seminal article on this topic: “Likely Gains from Market Timing”. In this article Sharpe demonstrated statistically that in order to benefit from a market timing strategy you had to guess right 74% of the time. [2]

Historic performance data seems to confirm this conclusion. When Brinson, Hood, and Beebower conducted their analysis of the performance of 91 pension plans from 1974 to 1983 they determined that market timing had detracted from performance by .66% [3]

So maybe we should just end the article here. Why go on? Maybe because everyone believes that they are above average and people don’t like the idea of a passive strategy. More importantly, these analyses don’t tell the entire story.

First, every anti-timing analysis that I have seen, such as the first example given, focuses on the performance of binary strategies – you switch from being 100% in the market to being 100% out of the market. A more prudent strategy, and one that is actually practiced by portfolio managers, involves moderately adjusting your market exposure depending upon some appropriate signal. However, I have not seen this examined in the research.

Secondly, bubbles do occur and after the fact everyone clearly sees how overvalued the bubble assets were. There are historic patterns and there are limits to what is a reasonable price for any asset. If we can learn to leverage this knowledge then perhaps we can boost our returns.

I skimmed through parts of Graham (In case you didn’t know, Benjamin Graham was a young Warren Buffet’s mentor) and Dodd’s 1934 classic book, Security Analysis, in early 2002 and was awe struck by the timelessness of their writings. Considering the parallels between 2002 and 1934, I had to keep reminding myself that the book had been written almost 70 years prior. Let me share a montage of interesting quotes from the book (italics theirs): “…the prices of common stocks are not carefully thought out computations, but the resultants of a welter of human reactions. The stock market is a voting machine rather than a weighing machine. It responds to factual data not directly, but only as they affect the decisions of buyers and sellers…a conservative valuation of a stock issue must bear a reasonable relation to the average earnings. In addition, it must be justified by whatever indications are available as to the future. This approach shifts the original point of departure, or basis of computation, from the current earnings to the average earnings, which should cover a period of not less than five years, and preferably seven to ten years…But it is the essence of our viewpoint that some moderate upper limit must in every case be placed on the multiplier in order to stay with the bounds of conservative valuation. We would suggest that about sixteen times average earnings is as high a price as can be paid in an investment purchase of a common stock…it is difficult to see how average earnings of less than 6% upon the market price could ever be considered as vindicating that price. It would be acceptable only in the expectation that future earnings will be larger than in the past. In the original and most useful sense of the term such a basis of valuation is speculative.” [4]

Notice that Graham and Dodd heavily discounted expectations of future earnings. Maybe they were from Missouri and they never had to figure out what Google was worth but frankly I agree with their approach. It’s hard enough to know what a company really earned over the last 10 years, let alone project future earnings.

Fast Forward to February 2006 at The CFA Institute Risk Symposium and Yale professor Robert Shiller discusses the characteristics of bubbles and how they propagate. He also presents a few compelling market valuation indicators. [5] (Shiller is famous for his 2000 book, Irrational Exuberance, named after a term used by Alan Greenspan in a famous speech. Interestingly, Shiller had discussed the impact of market valuations on returns with Greenspan 2 days prior to the famous speech.) First, he examines the S&P P/E ratios from 1881 - 2005, calculated as Graham and Dodd would have them calculated. The graph below, from Shiller’s Web site, is the same one used in his presentation but is updated through February 2007.

As you might expect the graph shows massive fluctuations, with the most prominent peaks in 1929 and 2000. Of course there are two ways that a high P/E can come back down to earth – either the E can go up or the P can go down and you would have no way to know in advance which was going to occur. However, Shiller analyzed the relationship between the P/E and the subsequent 10 year return. Although the relationship would not make for a very good regression it clearly shows that a high P/E results in lower returns over the next 10 years. In particular, after the lows of 1919 the market averaged more than 15% per year and when the P/E was 20 – 25 the subsequent returns were near zero. So it would appear that Graham and Dodd were correct and that P/E is a valid indicator of fair value. By the way, as of February 2007 the P/E was at 30, which is not a positive indicator.

Shiller also presents his Valuation Confidence Index, which he has calculated since 1990 and which reflects the percentage of investors that believe the market is not overvalued.

Interestingly, the index bottomed out at around 30% right before the market peak in early 2000, which begs the question “if investors believed the market was overvalued then why didn’t they sell?” Maybe they didn’t believe in market timing. Unfortunately, his data only goes back to 1990 so we can’t be sure that this is a valid market indicator but it certainly bears watching. Note that by this measure the market is not currently at risk for a pullback.

In 2002 Pu Shen, an economist at the Federal Reserve Bank of Kansas City, took the P/E indicator a step further and empirically examined the performance of a signaling tool similar to the Fed Model. For the period from January 1962 to December 2000 he tested buy/sell decisions based upon what he calls the “short spread” between the S&P earnings yield and the yield on 3 month treasuries (E/P – 3 month treasury bill yield). (He also looked at the “long spread”, based upon the 10 year yield but that was not as powerful.) He used the tenth percentile of the spread as the signal – i.e. when the spread dropped below the tenth percentile it was time to get out of the market and into 3 month treasuries and when it rose above the tenth percentile it was time to get back into the market. (Note that this is one of those binary strategies.) The idea here is that when the earnings yield on stocks is too close to the yield on 3-month treasuries stocks are not a very good investment. Seems reasonable.

Here is a summary of the important findings from his 39-page paper:

• The buy and hold strategy returned 1.117% per month over the test period while the switching strategy returned 1.322% per month.
• On an annualized basis that amounts to 14.26% vs. 17.07%.
• Whether or not you consider this difference to be statistically significant depends upon how you frame the analysis. I did not find this part of the paper particularly enlightening.
• The switching strategy resulted in a less risky portfolio over time. The Sharpe ratio of the switching portfolio was 0.205 vs. 0.13 for the buy and hold strategy.

Seems like it would be hard to pooh pooh these results. However, Pu also tested switching strategies based upon just the earnings yield and just the 3-month yield and concluded that almost all the predictive power was in the 3-month yield. His interpretation of this result is that trading based upon the 3-month yield keeps you out of the market during inflationary periods, which are not good for the market. I think it’s just as valid to view this from the perspective of higher yields mean a higher discount rate on stocks, which gives lower stock valuations.

While I think this study raises some interesting possibilities, I do have one major concern. Given the amount of historical data available and the varied economic environments that the market has encountered I don’t think 39 years is a long enough time period for this kind of study. In fact, Robert Shiller pointed out that “Since 2000, [the Fed Model] has broken down, and also before 1970, there really was not a correlation. Thus, people seem to have been exaggerating the impact of interest rates on the stock market.” [7] Clearly he is of the mindset that we should focus on the P/E ratio alone and from my perspective there is good reason to believe him. Interest rates are going to go up, they are going to go down, they are going to oscillate around some “normal” level, and you can’t very effectively predict where or when they are going to move. So you might as well take a long-term perspective and focus on the P/E ratio alone. Unfortunately, Shiller did not do nearly as rigorous an analysis as Pu.

A similar analysis from Ned Davis Research shows that extreme values of the S&P P/E can be effective predictors of future stock returns. Analyzing the period from March 1926 to June 2006, using trailing 12 month earnings, they point out that the average P/E has been 15.9 and they have set buy/sell triggers at P/E ratios of 9.3 and 20.2. (I was unable to discover how they determined these thresholds.) 24 months after responding to these triggers the median return of the S&P has been 27.5% after a buy signal and 0.8% after a sell signal.

So where does all this leave us today? The current trailing P/E ratio of the S&P 500 doesn’t look so bad at 15.6. However, based upon Shiller’s 10 year trailing analysis above which shows the February P/E to be 30, it’s clearly north of 30 now, which is darn high. The reason for the big difference is that S&P earnings have been on a rocket since 2002. As long as you have confidence that earnings won’t retreat then maybe valuations aren’t so out of whack. However, consider the data over the past 135 years:

Using Shiller’s entire data set I have determined that the historic earnings growth rate has averaged 1.45% per year and earnings are currently well above the trend line. Picking different time periods than the last 135 years can give slightly different results for the average earnings growth rate but nothing dramatically different. For instance, in a 2002 Yale ICF working paper Ibbotson and Chen stated that earnings have grown at a 1.75% annual rate since 1926. [8]

Each time that earnings have shot well above the trend line in the past they have eventually regressed back to the trend line. There are several reasons to expect that to occur. First, as Ibbotson and Chen point out, earnings just can’t grow faster than the overall economy unless equities are becoming a larger factor in the economy. While the factor share of equities has grown it is not a huge effect. Therefore, one would expect earnings to grow at about the rate of productivity growth, which has been about 2% per year. [8]

Second, market forces also throttle earnings growth. Extraordinary profits invite additional competition, greater employment levels eventually cause labor rates to rise, and high production levels bid up energy and raw material costs. With unemployment at a 6 year low and rising commodity prices we’re already seeing evidence of this.

My belief is that we have been experiencing an earnings bubble – perhaps driven by huge liquidity injections and lax home mortgage originations. It would seem that profits are destined to go down. If that’s the case then Graham and Dodd are correct to be looking at the longer-term earnings average. We could very well be at a market peak right now and, while a complete withdrawal from the market might not be prudent, reducing one’s exposure to stocks might be wise.

[1] ING Special Report: Market Timing, July 2005
[2] William Sharpe, “Likely Gains from Market Timing”, Financial Analysts Journal, Vol. 31, No. 2, March-April, 1975, pp. 60 - 69
[3] Gary P. Brinson, L. Randolph Hood, and Gilbert L. Beebower, “Determinants of Portfolio Performance”, Financial Analysts Journal, Vol. 51, No. 1, January-February, 1995, p. 135
[4] Benjamin Graham and David Dodd, Security Analysis, 1934, pp. 452 – 453
[5] Robert J. Shiller, “Irrational Exuberance Revisited”, CFA Institute Conference Proceedings Quarterly, Volume 23, Number 3, September 2006, pp.16 – 21
[6] Pu Shen, “Market-Timing Strategies That Worked”, Research Division, Federal Reserve Bank of Kansas City, May 2002
[7] Robert J. Shiller, “Irrational Exuberance Revisited”, p. 19
[8] Roger G. Ibbotson and Peng Chen, “Stock Market Returns in the Long Run: Participating in the Real Economy”, March 2002

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The opinions and views expressed in this article do not necessarily reflect the views of InvestingMinds. InvestingMinds did not prepare and does not endorse such content. Please note that this document is intended for general circulation only and the recommendations contained herein do not take into account the specific investment objectives, financial situation or particular needs of any particular person. This document is for information purposes only and it should not be regarded as an offer to sell or as a solicitation of an offer to buy securities or other financial instruments. No part of this document may be reproduced in any manner without the written permission of InvestingMinds.

The investor who wishes to make a serious effort to manage his/her own financial investments faces a formidable task. Virtually all professional investment managers follow a continual process that involves collecting relevant data and then analyzing it to produce decisions on how to act. Both the data used and the methods of making decisions vary widely, but it is not our purpose here to describe the details of either area. Rather, this article concentrates on helping the reader locate free sources of information on investment decision-making processes that she might be able to employ in managing her own investments.

We divide the sources into three areas to be discussed in turn, but of course there are other sources.

ACADEMIC SOURCES

The management of financial investments for the benefit of others is a big business, to say the least. Each year investment professionals in the US collect hundreds of billions of dollars from their clients in fees, commissions, expenses etc. It is therefore not surprising that universities have devoted a lot of resources to business schools and departments of economics where faculty and students spend their time trying to understand how financial markets work, and more particularly how to profitably invest in these markets. Many of the students proceed to high-paying jobs in the investment industry, so that the universities can charge the students high fees. Many of the faculty gain by acting as consultants to financial institutions, and some of them are involved as principals of investment management firms. [see this article.]

It seems to be a situation where everybody concerned should be happy, except perhaps the clients.

The typical individual investor is an outsider to the above structure, but nevertheless there are opportunities for him to gain some benefit from the work that is produced. To an extent, the academic world follows the dictum of “publish or perish”. An academic gains prestige, salary, etc. on the basis of the length (and to a lesser extent the perceived quality) of her publication list. In every academic discipline there are journals that publish accounts of the research performed by people in the field. The shelves of university libraries buckle with the weight of years of volumes of each journal. For example, in 2006, the Journal of Finance, a leading publication in Financial Economics, published over 2500 pages.

In recent years the journals in many fields have been made available in electronic form, but only to those people affiliated with institutions that pay a fee to the body that publishes the journal. For the individual investor who is not lucky enough to have a connection to a university that includes electronic journal access, it may still be possible to obtain copies of some articles from the web sites of the authors, or perhaps by a general search of the Internet. Sometimes a friend might send the investor a copy of a specific article. Of course, for those near enough to travel to a university, it may be possible to obtain hard copies of articles from the library, even if the investor has no affiliation with the institution.

The first few interesting articles that an investor finds can be the start of an endless chain of others. Each article contains a list of references to other articles on related topics. In addition, for those with access to the ISI Web of Knowledge, it is possible to find a list of later articles that refer to a specific earlier paper. For those without this access, a standard search engine can partially take its place.

Some of many web sites of academics are:

• J. Campbell
• K. Daniel
• F. Diebold
• E. Fama
• H. Hong
• A. Lo
• R. Shiller

WORKING PAPERS

It may take several years from submission of the article to the journal to the time when it appears in the journal. Many academics produce drafts of articles, called working papers in the social sciences, that are freely available on their web sites long before the final version appears in print. With experience an investor may learn the names of academics whose articles are of interest, so that he can look at their web sites from time to time and keep up to date with recent developments. This process has been facilitated by the establishment of data banks of working papers, where authors may have their works listed and available for search and download, all at no cost. Note that these data banks do not require that the paper be evaluated by an expert in the field, as is the case with journals. There may be problems with the quality of some working papers, but the journals’ peer review system also has difficulties.

An important data bank in the social sciences is the Social Science Research Network (SSRN) - the section on financial economics will be the one for the investor to look for. The paper with the most downloads is “Market Efficiency, Long-Term Returns, and Behavioral Finance,” by Eugene Fama of the University of Chicago - Graduate School of Business. It was posted to the database on April 30, 1997, and it was also published in the Journal of Financial Economics in 1998. There have been over 60,000 downloads of this paper from SSRN, a staggering figure. Currently the two most popular recent working papers are

“We Don’t Quite Know What We are Talking About When We Talk About Volatility,” by Daniel G. Goldstein, Nassim Nicholas Taleb, London Business School, University of Massachusetts at Amherst,

“Where do Alphas Come From?: A New Measure of the Value of Active Investment Management”, by Andrew W. Lo, Massachusetts Institute of Technology (MIT) - Sloan School of Management,

Another working paper data bank is RePEc (Research Papers in Economics).

INVESTMENT PROFESSIONALS

Professionals such as portfolio managers and consultants probably have less incentive to disclose their ideas to the public, but some professionals have web sites containing interesting information. A small selection is

AlphaSimplex Group Founded by Lo and others

Arrowstreet Capital Founded by Campbell and others

Barra Leading supplier of risk management software - 300 articles available

Burns Statistics

E. Derman

Dimensional Fund Advisors Founded by Fama and others

Goldman Sachs

Haugen Custom Financial Systems

Northfield Information Services

Panagora Asset Management

Inclusion of a site in the above lists does not imply a guarantee that everything on the site is correct. In particular I and others have reservations about Fama’s ideas on the Efficient Market Hypothesis, and the Fama/French three-factor mode, the basis for DFA’s approach, has been criticized by Daniel.

The topics covered by the sites listed may have a bias towards the quantitative approach. A reader interested in other topics could look through the areas of expertise of faculty at institutions such as those appearing in the academic websites, to find something more to his taste.

For the novice investor, or the newly initiated to the field of investment, there exists numerous “how-to” books and web sites dedicated to informing the new investor and assisting him in understanding the arcane language of the investment profession and financial market practitioner. The InvestingMinds’ “Books” section contains titles of books that can help familiarize the uninformed or novice investor to the ways of the financial markets, Wall Street and investing. The “Financial Encyclopedia” can help with finding the meaning of financial concepts and investment terminology.

The concepts and jargon in academic articles may be unfamiliar to some individual investors. The serious investor might think it worthwhile to spend some time educating herself with the aim of eventually understanding enough to make value judgments of the material. It is wise to question everything you read in connection with investing. A knowledge of the relevant mathematics is valuable. I am dubious about applications of probability theory contained in many articles, implicitly or explicitly, and some understanding of this tricky subject would be helpful.

From experience I know that self-education about investing is possible, and I encourage others to learn as much as they can. These days the Internet makes it much easier to learn about almost any topic.

Authors note: I thought it would be appropriate to keep this article short so if you want some detailed information on how shorting works check out this entry in our encyclopedia.

There comes a time when you may want to take a short position and when that time comes you need to be aware of some of the potential pitfalls and how to avoid them.

First, why would you want to do something like this? Let me give you a few sample scenarios, though there are many others:

1. You are convinced that a particular stock is overvalued and you want to profit when everyone else figures out what you’ve known all along. A side benefit of doing this is that if the company goes bankrupt you never have to close out the short position and thus you avoid paying income taxes.
2. You want to hedge your investments. You like your individual stock selections but you’re nervous about the direction of the market so you sell the market short. Shorting one of the many ETFs that represent various indices will eliminate that market risk from your portfolio.
3. Perhaps you’ve sold a put option on a stock but want to insure yourself against the possibility that the stock will decline. Of course, in this case you will lose if the stock moves up.
4. You find a closed end fund that is selling at a substantial premium and there are comparable closed end funds or ETFs that are selling at net asset value (NAV) or below. You can short the fund trading at a premium and buy the fund trading at NAV.

Aside from the inherent risk of unhedged shorting (like having unlimited downside), there are several other ways you can get stuck with the short end of the stick if you don’t know what you are doing. Let’s start with how shorting is executed and who gets what out of the deal. Your broker borrows a client’s stock and sells it. First and foremost that means that the stock has to be available for shorting. If the stock is not widely held there is a very good chance that your broker can’t find a position amongst all of their clients from which to borrow. Without a lender you cannot execute a short transaction. I’ve run into this dilemma many times. However, your broker has a stock lending department that can help in these situations. They can go outside of their firm and find the shares. For this service you pay a small fee. Fidelity charges 2.5% of the average short value per year.

The next problem you will encounter is that you are now liable for paying the dividends on that stock to the lender. Seems reasonable, right? Yes, but there’s one small problem. You have an investment expense and guess what? You don’t get to deduct it as an investment expense. You see, our government, in their infinite wisdom, taxes you on any dividends you receive but doesn’t let you immediately deduct the cost of any dividends you pay. Instead you are supposed to add the dividend payments on short sales to your tax basis, so you don’t get the tax benefit until you close the position. One would think that a dividend you pay would be like a negative dividend that offsets any dividends you receive, but the world we live in is not symmetrical. (I have no idea what happens when you short against the box and you receive dividends that you simply turn around and pay back out but we can all guess how that story probably plays out.)

As if all this wasn’t bad enough there’s also the small issue of the cash generated from the sale of the stock. I think this is one of those dirty little secrets. When that stock is sold cash comes in the broker’s door, which generates interest. Who gets the interest? There’s only one possibility – the broker quietly pockets the money. I once brought this up with a trader who actively shorts stocks and he uncomfortably admitted that this is something that you can negotiate with some brokers. He claimed to have worked out a deal with his broker to give him a portion of the interest. I tried bringing this up with Fidelity and they acted like I was from another planet. So I just accept this as an unfair cost of doing business. This is just another glimpse into the asymmetrical world we live in: sell some stock and get interest on the proceeds; sell someone else’s stock and you don’t get interest on the proceeds.

Finally, shorting is not even an option in your IRA. I guess it’s viewed as too risky for retirement money.

Given all these problems what do you do? As a first step, before you short something (as in the case of a hedge) look around for alternative plays. Is there something else you can sell that will allow you to get interest on the proceeds? For example, you might be better off selling your GE stock, which is closely correlated with the S&P 500, rather than shorting the S&P 500.

Another alternative is to buy one of the recently introduced short funds (also known as bear or inverse funds). These are ETFs that move in the opposite direction of their corresponding target index. It would seem reasonable that the pros managing these funds have access to techniques that you or I don’t, which allows them to more efficiently take a short position. I just checked the prospectus for the Short S&P 500 ProShares fund (SH) and discovered that they basically have two holdings: S&P swaps via UBS and cash. So instead of shorting the index they’ve essentially achieved the same effect by entering into an agreement with someone who wants to bet on the S&P rising. When the index goes up ProShares pays the counterparty and vice versa. This structure has a benefit to the party taking the long position: they take a long position without tying up cash. So there is an inherent efficiency in this structure, the benefits of which you would expect to be shared by ProShares. In addition, ProsShares earns interest on all the cash that they receive from selling the fund.

The other advantage to these short funds is that you can purchase them in your IRA, which is a bit ironic since they don’t want you taking short positions there.

So, owning this short fund might be better than taking the short position yourself. To check this I compared the two alternatives during a time period between dividend payment dates (to make it easy) when the S&P changed by its maximum amount. From March 27, 2007 to June 4, 2007 the S&P Depository Receipt (SPY) went up 7.87%. Had you shorted it and held cash in the amount shorted (since you didn’t use cash to buy the short fund) you would have lost 7.87%, offset to some extent by interest of .95% (assuming your money market is returning 5%) for a net loss of 6.92%. During this same time period the Short S&P fund went down by only 5.93%. So it appears that during this period of rising stock prices owning the short fund was a better alternative. What I can’t tell you is what would happen during a period of falling stock prices, since these short funds haven’t been around long enough for us to measure that. Perhaps this fund just doesn’t track the index that well. I’ll be keeping an eye on this since I recently purchased the short fund.

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The opinions and views expressed in this article do not necessarily reflect the views of InvestingMinds. InvestingMinds did not prepare and does not endorse such content. Please note that this document is intended for general circulation only and the recommendations contained herein do not take into account the specific investment objectives, financial situation or particular needs of any particular person. This document is for information purposes only and it should not be regarded as an offer to sell or as a solicitation of an offer to buy securities or other financial instruments. No part of this document may be reproduced in any manner without the written permission of InvestingMinds.

Three asset classes - stocks, bonds, and cash make up the investable universe of all assets. How investors choose to allocate their investment dollars across these classes can have a significant impact on the long-term return of an investor’s portfolio. The decision to hold stocks, bonds or cash and in what amounts is believed to account, on average, for the bulk of the variation (risk) in an investor’s return. For a given investor, determination of the optimal mix is what is commonly referred to as an investor’s investment policy or asset allocation policy. It is also known as the asset mix, investment mix, and asset allocation for short.

A capital investment or equity ownership in an entity, commodity or enterprise is represented by holding an ownership certificate, stock. Equity investors earn a return premium that compensates for the perceived level of risk relative to the two other asset classes (bonds and cash). Equity ownership is indefinite, i.e. return of income is uncertain. Bondholders are lenders and they purchase debentures (debt contracts), in the form of bonds, and lend cash for a predetermined period of time. In return for lending their money, bondholders earn a rent, or rate of interest on the principle balance lent. Investors in cash earn the equivalent of a risk-free rate of return on their money. Stock and bond investors typically earn a risk premium, the rate of return above the risk-free rate that an investor demands for assuming risk. The rate of return on a risk-free investment, short-term (overnight) lending, is usually equal to or less than the rate of inflation.

A risk asset is an investment whose real (inflation-adjusted) return and the safe return of principle is uncertain. On the scale of least risky to most risky, cash is least risky and stocks are viewed as most risky. This is because stockholders are second to creditors, lenders of money, in the return of capital. Bondholders get paid before shareholders. As a consequence, shareholders demand higher rates of return to bondholders and bondholders earn higher rates of return to cash investors (who face virtually no insolvency risk). Portfolios made up of different proportions of stocks, bonds and cash will vary in return and risk (defined as the variance in return). There is a tremendous difference between a portfolio whose mix is 80% stocks, 15% bonds, and 5% cash and one whose mix is 60% stocks, 30% bonds, and 10% cash.

Typically, investors are characterized as either passive or active. Passive investors construct their portfolios by buying and holding a collection of randomly selected securities, a diversified portfolio. Investments are purchased with the intention of obtaining long-term appreciation and limiting turnover and maintenance. Passive management is better known as indexing, the designing of a fund to mirror the performance of a published benchmark. Unlike passive management, active portfolio management attempts to add value through one of two active strategies, market timing or security selection. Market timing is an attempt by an investor to benefit from the divergence of the current value of an asset from its “correct” or “rational” level. Security selection attempts to add value by purchasing undervalued (mispriced) securities or emphasizing a group of securities that make up an investment theme, i.e. small capitalization over large capitalization stocks. The objective with active management is to produce better returns than those of passively managed index funds. It has been demonstrated that active management detracts more often than not from overall portfolio performance; that asset allocation plays a more important role in overall portfolio performance.

Over the years, there has been considerable debate as to the importance of an investor’s asset allocation policy. In 1986, Brinson, Hood, and Beebower (BHB)[1], three knowledgeable investment management practitioners, studied the performance of ninety-one large U.S. pension plans over the 1974-1983 period and concluded that “investment policy (asset allocation) dominates investment strategy (market timing and security selection), explaining an average of 93.6% of the variation in total pension plan returns”. Others (most notably Jahnke[2] and more recently Kritzman[3]) have argued that BHB’s original conclusions and methodology are flawed. They contend that too much importance is given to asset allocation; that market timing and security selection have been marginalized.

Without getting into the specifics, Modern Portfolio Theory describes markets as efficient (all publicly available information on an asset is incorporated in the asset’s price nearly instantaneously). If one believes markets are informationally efficient, then it would be difficult to add value from active management. The certainty of market efficiency has been brought into question by some market practitioners, and thus as well, the relevancy of asset allocation. With little uncertainty, suffice it to say that we can probably ascribe efficiency to markets over the intermediate to long-run, which after all is what we should be concerned with as investors. Conventional wisdom accepts that for the “average” investor (especially the unsophisticated investor) it is very difficult to beat the market (earn a rate of return greater than the risk premium associated with an amount of risk). As well, it has been proven, again Modern Portfolio Theory, that in the case of a specific asset class (for instance, stocks), an investor does well to invest in a diversified portfolio.

In my experience, unsophisticated investors (those who do not make a career out of stock picking) are far off better focusing on the asset allocation decision than worrying about which stocks or bonds to hold (security selection) or when to buy them (investment timing). It is clear from financial theory and practical experience that investors’ asset allocation choices should be linked with their specific circumstances or long-term financial goals. Investors determine their asset allocation policy based on their risk tolerance, their financial goals, their time horizon, their non-financial wealth (such as employment income), and the risk premiums of the asset classes.

That is not to say that certain individuals using superior research or first-hand experience cannot take advantage of unique information from time to time through active portfolio management (trading). However, it is likely that the knowledge will become known by the rest of the market, or as well, be in the possession of others, and therefore in the long-run not have any intrinsic value. Only if investors have the ability to predict expected returns in financial markets can tactical (active management) asset allocation enhance portfolio performance. Keep in mind that the degree of skill required to justify an active management strategy is very high. Investing on the basis of event driven information (such as earnings releases or change in corporate control), which may materially impact the value of an enterprise, is likely to be viewed as insider information and construed as illegal.

A better way to consider this issue is to determine whether or not having better information about the asset changes its risk profile and thus the willingness of an investor to assume risk. If so, an investor should be willing to increase such holdings in his/her portfolio. As an investor becomes more knowledgeable about the ownership of equities and more comfortable with their risk, he would then consider increasing his allocation to equities, presuming the allocation meets his risk tolerance.

A passive investment strategy (no trading) with rebalancing (resetting the asset mix to meet your specific circumstances related to return objectives and risk tolerances) is likely to incur lower costs to manage than active portfolio management (buying and selling assets based upon market timing and security selection). The BHB study found that, on average, tactical asset allocation (market timing) and security selection work to detract 1.1 percentage points from the return that would have been achieved with strategic asset allocation (a passive investment strategy) alone. Depending upon one’s time, commitment, and experience, he/she might be better off creating a diversified portfolio of stocks or bonds by choosing to use exchange traded funds (ETFs) encompassing a basket of assets that replicate a “market” portfolio.

In the BHB study, it was found that a portfolio’s asset allocation policy dominates portfolio performance, and over a period of time typically explains over 90 percent of the variation in the portfolio’s returns. However, that is not to say that within a given portfolio’s return, active management did not play a role in imparting a return that varied significantly from a portfolio benchmark. The average ten-year annual return of the 91 actual portfolios was 9.01% and ranged from 5.85 percent to 13.4 percent. Portfolios yielding returns in excess of the average in all likelihood may have been attributed to superior skill or knowledge. As well, they were likely to have been far and few between; the exception. In the long-run, due to competitive forces, the benefit of skill and predictability will average out - losing as often as winning and reverting returns to the mean. Financial theory and empirical evidence show that exposure to systematic risk (market risk) is compensated over time. Active management risk is not compensated on average (Sharpe, 1991)[4]; however, it is compensated if skill overcomes the higher cost hurdle of active management. Active management creates opportunity to outperform. However, the most important consideration is how much extra return active management can add without exposing the portfolio to unwarranted risk. Overcoming the higher cost hurdle of active management is a challenge.

As L. Randolph Hood, the “H” in BHB, stated in a letter to the Financial Analysts Journal 20 years hence first publishing their findings in 1986, “Our message today remains the same as before: Carefully consider what goal you are trying to achieve, how important it is to achieve it, and how much risk you are willing to tolerate in pursuing it. Then, create a policy portfolio (a portfolio allocated to the three major asset classes - stocks, bonds, and cash) that reflects that goal and your risk tolerance for probable outcomes - because executing that policy will have a dominant effect on your success.”[5] Investment policy (the asset allocation decision) should be addressed carefully and systematically.

[1] Brinson, Gary, Randolph Hood, and Gilbert Beebower. “Determinants of Portfolio Performance.” Financial Analysts Journal, July-August 1986, pp. 39-44.

[2] Jahnke, William. “The Asset Allocation Hoax.” Journal of Financial Planning, February 1997, pp. 109-113.

[3] Kritzman, Mark. “Determinants of Portfolio Performance-20 Years Later”: A Comment. Financial Analysts Journal. January/February 2006, Vol. 62, No. 1: 10-11.

[4] Sharpe, William F., 1991. “The Arithmetic of Active Management.” Financial Analysts Journal 47 (1): 7-9.

[5] Hood, L. Randolph, CFA. “Determinants of Portfolio Performance - 20 Years Later.” Author’s Response. Financial Analysts Journal. September/October 2005, Vol 62.

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