In What’s the Significance, we addressed the importance of considering statistical significance when drawing conclusions from noisy data. Noise in the data is problematic when investors overemphasize what might have been a period-specific outcome rather than a robust and repeatable result that is likely to persist going forward. Manager selection is a process that requires analyzing noisy performance data, so it should lean heavily on the notion of statistical significance.

When advisors, consultants, or investors select a manager, their approach often involves a combination of qualitative and quantitative analysis. The latter, by necessity, requires the use of past performance, as it is essentially all we have to evaluate. The focus is typically on managers with a positive “alpha” (i.e., outperformance relative to a benchmark or asset pricing model). Although past performance represents what actually happened, new investors cannot get those returns; therefore, the objective of the analysis is to determine whether outperformance in the past is any indication of skill, or simply good luck. In other words, is the positive alpha likely to persist in the future, after the manager is selected?

This task is more difficult than many investors might think. Several notable studies of manager performance found little persistence in past performance. Regardless, investors rarely hire managers with a history of poor relative performance, so the manager selection merry-go-round often becomes:

1. Hire managers who have outperformed in the past.
2. Fire managers who underperform in the future.
3. Repeat.

This activity meets Einstein’s definition of insanity, as many investors do the same thing over and over again while expecting different results. There are many reasons why this is an exercise in futility:

• It generally takes a long track record for a manager’s alpha to be statistically significant.
• Positive alphas, even statistically significant ones, may not be an indication of skill.
• By the time you are confident there is skill, it’s probably too late to benefit.
• Past performance is (really) no indication of future performance.
• If you know for sure the manager has skill, you likely won’t benefit because the scarce resource captures the rent!

It Takes Time

Finding managers with positive alphas is like looking up the box scores from last night’s games, but picking those who will outperform in the future is anything but trivial. To begin with, a quantitative analysis of past performance should incorporate tests of statistical significance to determine the likelihood their true alpha is not zero. In most cases, a long track record is required for the manager’s alpha to be statistically significant. Given the average alpha and the standard deviation of the alpha, we can determine the track record required (in years) to obtain a t-stat of 2.

Table 1. Minimum track record for a statistically significant alpha (t-stat > 2)

A track record of outperforming a benchmark or asset pricing model by an average of 2% per year (net of fees) over the life of the fund would get the attention of many investors, especially when you consider that the equity premium might only be around 5%. A representative standard deviation of alpha in the Morningstar universe of actively managed US equity mutual funds is approximately 6%. As illustrated in the table above, a 2% average alpha and a 6% standard deviation of the alpha requires a track record of thirty-six years before you can be 95% sure that the true alpha is not in fact zero (i.e., there was no skill at all). Based on these parameters, by the time you are reasonably confident there is some amount of skill, the manager is likely retired and on her yacht!

The Effects of Chance

Identifying a skillful manager involves more than simply narrowing down the universe to funds with positive alphas and a t-stat of 2 or more. This approach ignores the effects of chance. There is still a 2.5% probability the outperformance was due to good luck, and the true alpha of the manager is zero. Said another way, one out of forty managers is expected to have a positive alpha with a t-stat of 2 by chance. With so many funds in the universe, many will have statistically significant alphas even when there is no skill at all.

For example, in a 5,000-fund universe, 125 managers are expected to have a positive alpha with a t-stat greater than 2, even if their true alpha is zero. Unfortunately for investors, the opportunity is not in sorting through the many managers with statistically significant alphas, but rather in finding these managers because there are too few of them. Fama and French recently studied 3,156 US equity funds and compared their performance to a simulated universe of funds in which the true alpha for every fund was zero. Their results identified fewer funds with statistically significant alphas than you would expect to find by chance.

By Then, It’s Too Late

An investor concluding that a statistically significant alpha is evidence of skill could be guilty of data mining, meaning he is making inferences from what might have been a chance outcome limited to that time period. To counter these claims, academics conduct out-of-sample tests to confirm a statistically significant result. For example, out-of-sample data can be obtained by repeating the experiment using an independent time period (e.g., 1926–1962 rather than 1963–1992) or a different data set from an overlapping time period (e.g., international rather than US market data).

Practitioners should also conduct out-of-sample tests when analyzing manager performance to help rule out that a statistically significant alpha didn’t occur by chance. On the surface, conducting out-of-sample tests might seem like an overly cautious approach akin to wearing a belt and suspenders. However, even if this were true, when you consider the consequences and what is at stake, it sure beats getting caught with your pants down.

The only way to test out-of-sample data when doing performance analysis is by using totally independent time periods. Accordingly, the number of years required in Table 1 gets multiplied by the number of independent periods you’re comfortable with before you have faith there is some amount of robust and repeatable skill.

Table 2. Minimum track record for two independent periods with statistically significant alpha (t-stat > 2)*

* Assumes the average alpha and standard deviation is the same in both time periods.

Using the prior example of a 2% average alpha and a 6% standard deviation of the alpha means you need a track record of seventy-two years if you’re satisfied with a statistically significant result from only two independent time periods. But, in this instance, by the time you think there is evidence of skill, it’s too late—the manager may be dead!

Persistence

Having said that, let’s assume you’ve found a manager with statistically significant alpha in multiple independent periods and she is not yet retired or deceased. The question still remains: will the positive alpha continue? You cannot rule out luck because of the effects of chance noted above, but more important, many performance studies conclude that winners do not continue to win, and even when there is alpha in the extremes, it does not persist. The only slight indication of persistence is among the extreme losers, and it is mostly explained by high fees and high turnover.

If we eliminate these funds from consideration, manager selection becomes a random draw, but whether investors know they are picking them at random is another question. Their goal is often to achieve top quartile performance, and pursuit of this goal usually boils down to choosing from managers among the top quartile in the past. However, excluding the persistent losers noted above, yesterday’s top quartile performers have the same 25% probability of being in tomorrow’s top quartile as every other manager!

Scarce Resources

Ironically, the predicament is not only for the investor trying to identify skill but for managers trying to prove they have it. A fundamental of economics is that the scarce resource captures the rent. If capital is freely floating and perfectly liquid, then the scarce resource is not the investor’s money but the manager’s skill! There is an enormous economic incentive for managers to indisputably prove they are in possession of this elusive ability.

Let’s assume a manager has a twenty-year track record of outperforming by 4% each year. In this extreme example, a t-stat is meaningless since the standard deviation of the alpha is zero. If we rule out the possibility of a Ponzi scheme, the manager surely has undeniable skill. However, as soon as she proves her unique ability, she can capture the rent by increasing her fees to nearly 4%. An increase in fees of this magnitude may draw the ire of her investors, so, alternatively, she could raise more and more assets, thereby distributing her alpha over a larger asset base, which would dilute investor results. This latter approach may largely go unnoticed by investors, but either way they lose as their alpha subsequently becomes zero.

Making Progress

So, herein lies the paradox of skill. Many investors are searching for the Holy Grail of fund management. Their goal is to identify a skillful manager with certainty and participate in future returns. But confirming skill takes an investment lifetime, and you can never be fully confident that the alpha is not random. Even if you could identify skill ahead of time, you probably would not benefit. Winning managers hike their fees or attract large volumes of new investment long before their skill is statistically confirmed—and both actions can dilute returns.

But this paradox is not a case of “damned if you do and damned if you don’t” for all investors. You can get off the manager selection merry-go-round and start making progress toward a successful investment experience by following these simple principles:

1. Diversify by asset class rather than by fund manager, broker, or advisor.
2. Buy into markets, not managers, and let capitalism be your guru.
3. Focus on what you can control—costs, asset allocation, risks, and discipline. Ignore what you cannot control—the media, prognosticators, market returns, and your gut.
4. Work with an advisor who understands these principles and can help you apply them.

The comments of Weston Wellington are gratefully acknowledged.

1. Noteworthy studies include: Mark Carhardt, “On Persistence in Mutual Fund Performance,” Journal of Finance 52, no. 1( March 1997). Garrett Quigley and Rex A. Sinquefield, “Performance of UK Equity Unit Trusts,” Journal of Asset Management 1, 72-92. James L. Davis, “Mutual Fund Performance and Manager Style,”Financial Analysts Journal 57, no. 1 (Jan/Feb 2001).

2. Source: Index Funds Advisors.

3. Eugene F. Fama and Kenneth R. French, “Luck Versus Skill in the Cross Section of Mutual Fund Returns,” Journal of Finance 65, no. 5 (October 2010): 1965–1947.

4. Carhardt, “On Persistence in Mutual Fund Performance.” Fama and French, “Luck Versus Skill in the Cross Section of Mutual Fund Returns.”

5. Jonathan Berk and Richard C. Green, “Mutual Fund Flows and Performance in Rational Markets,” NBER Working Paper No. W9275, October 2002.

Professor Jim Davis of Dimensional Fund Advisors asks the very interesting question of just how much skill must a manager-picker possess to have at least a 50% chance of achieving positive alpha? Davis sets up a hypothetical situation where 10% of managers have true skill (i.e., they are capable of delivering alpha of 1.5%), while the remaining 90% are unable to cover their costs and thus have an alpha of -1.0%. Given the CRSP result of -1.5% for all managers over the last ten years, these are generous assumptions. Now suppose we delegated the job of manager-picking to our monkey who would throw darts at a list of managers rather than a list of stocks, then our expected alpha would be -0.75% (assuming that 10% of the monkey’s picks are skilled). Alternatively, we can ask our would-be manager-picker to do the job, based on his in-depth analysis of Morningstar and Lipper data. Throwing in the additional assumption that that a manager’s realized alpha will vary randomly from his true alpha (i.e., truly skilled managers can be afflicted with bad luck and truly unskilled managers can be blessed with good luck), Davis calculates that our manager-picker must have at least a 40% accuracy rate in his identification of skilled managers  (four times better than what could be expected from chance) in order have a measly 50% chance of achieving positive alpha.

The bottom line is that if you are going to play the mug’s game of manager-picking, you better be sure that you are really good at it. The better option, or course, is not to play and instead invest in a risk-appropriate portfolio of globally diversified index funds.

¹Sharpe, William, 1991. The arithmetic of active management. Financial Analysts Journal, January-February, 1991, 7-9.

In order to determine whether being named “Fund Manager of the Year” engenders a valid expectation of higher returns for the fund’s investors, Index Funds Advisors ran a statistical test (the t-test) of sixteen domestic equity mutual funds which received this Morningstar recognition (cached article) to determine if the fund’s outperformance was truly attributable to skill (95% or higher probability) or if it could be explained as luck. For each fund, the performance from the manager’s inception date (or the inception date of Morningstar’s benchmark in two cases) through year-end 2011 was evaluated against the benchmark designated for the fund by Morningstar.  The charts below show each fund’s alpha (the difference in returns between the fund and the benchmark) on a year-by-year basis. Only one of the sixteen funds (about 6%) met the requirement of the statistical test that would suggest ruling out luck as the explanation for the outperformance based on a 95% confidence level. Before you get too excited however, please note that this fund belongs to the small growth category which of has the lowest expected return per unit of risk of all the different equity style boxes. Among the sixteen funds, the median number of years needed to conclude the presence of skill over luck was 72 years. Five of the funds showed a high enough degree of volatility in their returns (relative to their benchmarks) as to require a minimum of 100 years.

Even when there is a statistical indication of skill in a manager’s performance, it is often confined to a single time period and does not persist beyond it. A perfect example of this is Bill Miller of the Legg Mason Value Trust who carries the distinction of being the only mutual fund manager to have beaten the S&P 500 for fifteen consecutive years. Viewing the fifteen-year winning period alone indicates over a 99% probability of true skill, but if we broaden the scope of analysis to his entire tenure, we no longer can statistically conclude the presence of skill over luck.

Perhaps the first step to becoming a successful investor is acquiring the ability to tune out the “The Siren Songs of Active Management.” The Fund Manager of the Year is exactly such a song.

The reaction was no less muted in Europe. A headline in the Guardian stated: “Eurozone in new crisis as ratings agency downgrades nine countries.”

All over the world, analysts weighed in with their views of the dire consequences of this stunning news. Peter Apps, the political risk correspondent for Reuters told investors to “[D]itch the assumption developed economies are safe.”

For investors, this reaction is a day late and a dollar short. As discussed by Jim Parker, vice president of Dimensional Fund Advisors, the liquid market for credit default swaps factored in the increased risk of the downgraded countries as early as November 2011. Credit default swaps are insurance against default by sovereign borrowers. The higher the premium for this insurance, the greater the perception of the market of the risk of default.

Parker observed that Germany, France and Austria all had a triple-A rating from Standard and Poors until Jan. 13, 2012. As far as the credit agency was concerned, these countries all had comparable risk of default. The perception of the market was quite different.

Parker noted that, as early as November 2011, the difference in the price of credit default swaps for France and Austria over Germany (which was not downgraded) increased significantly. The market was way ahead of the credit agency. It had already taken into account the increased credit risk of these countries. After the downgrade, the spread narrowed, indicating a perception by the market that the probability of default by France and Austria, compared to Germany, actually decreased.

The market for stocks and bonds takes into consideration all publicly available information and instantly incorporates that information into the price. This irrefutable fact has profound ramifications. Think about how most individual investors make investment decisions. They trade on their own using research tools provided by discount brokers (or worse, relying on technical charts with purported predictive value). They rely on analyst reports and the recommendations of their brokers or advisers. These “financial experts” are all too willing to pick the next “fund manager of the year,” identify “mispriced” stocks, select high yielding bonds and predict the direction of the markets.

Relying on this advice, instead of looking at the market and recognizing the current price is a fair price, which reflects current and forecasted news, is the most fundamental error made by investors. The likelihood of identifying mispricings and profiting from them is 50 percent, before costs and taxes.

This is not an intelligent way to invest.

Dan Solin is a senior vice president of Index Funds Advisors. He is the New York Times bestselling author of The Smartest Investment Book You’ll Ever Read, The Smartest 401(k) Book You’ll Ever Read, The Smartest Retirement Book You’ll Ever Read and The Smartest Portfolio You’ll Ever Own. His new book, The Smartest Money Book You’ll Ever Read, was published December 27, 2011.The views set forth in this blog are the opinions of the author alone and may not represent the views of any firm or entity with whom he is affiliated. The data, information, and content on this blog are for information, education, and non-commercial purposes only. Returns from index funds do not represent the performance of any investment advisory firm. The information on this blog does not involve the rendering of personalized investment advice and is limited to the dissemination of opinions on investing. No reader should construe these opinions as an offer of advisory services. Readers who require investment advice should retain the services of a competent investment professional. The information on this blog is not an offer to buy or sell, or a solicitation of any offer to buy or sell any securities or class of securities mentioned herein. Furthermore, the information on this blog should not be construed as an offer of advisory services. Please note that the author does not recommend specific securities nor is he responsible for comments made by persons posting on this blog.

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The first of Lack’s devastating conclusions is that hedge fund investors as a group would have been better off if they had simply invested in Treasury bills, the quintessential risk-free investment. Lack reached this conclusion by using publicly available data from Hedge Fund Research, Inc., and he reminds us that his computations are likely overstating the true hedge fund returns because of survivorship, selection, and backfill bias. Specifically, hedge fund managers decide whether or not to report their returns (self-selection bias), and they will often report after a good run (backfill bias), and they can cease reporting if returns go south or if the fund folds (survivorship bias).

Lack’s analysis was inspired by the research of Ilia Dichev and Gwen Yu¹ who published a paper in the Journal of Financial Economics which showed that the annualized dollar-weighted returns are on the magnitude of 3% to 7% lower than corresponding buy-and-hold (time-weighted) fund returns. The essential recurring problem is that hedge funds that have a strong beginning attract a large amount of new capital which hinders them from repeating their outperformance (which may have been due to luck anyway). For the hedge fund industry as a whole, the attractive returns were achieved when there was relatively little invested. By the time of the 2008 financial crisis, the poor performance of hedge funds completely reversed all the investor profits made in the prior period.

The second major problem in the hedge fund is the imbalance between fees paid to managers and returns received by investors. Lack delves deeply into the returns data and finds that since 1998, hedge fund managers have kept 84% of profits, leaving a paltry 16% for investors. At the root of this problem is the common 2% of assets and 20% of profits charged by hedge funds. The 20% of profits often creates a perverse incentive for the hedge fund manager to take inordinately high risks since he shares only in the gains and not in the losses. Lack does not hold hedge fund investors blameless, as most of them have the sophistication needed to realize just how much the playing field is tilted against them. Although anyone with a passing familiarity with the hedge fund industry can name a few “superstars” such as John Paulson who have become multi-billionaires, it is far more difficult to find an actual hedge fund investor who vastly increased his wealth due to his manager-picking acumen. As Lack repeatedly states, the best way to make money in hedge funds is to manage one or provide seed money which entitles you to a share of the expenses collected from the other investors. The question, “where are the customer’s yachts?” is completely rhetorical.

Interspersed throughout the book are entertaining anecdotes concerning various characters that Lack encountered in the hedge fund business. While they tended to be incredibly smart and gifted people, some of them exhibited questionable if not outright dishonest behavior. To summarize, although we disagree with his utilization of hedge fund-like strategies for his investment advisory clients, there is no denying that Lack has made a unique and valuable contribution to the literature of popular finance. Anyone who is either currently a hedge fund investor or is contemplating becoming one would do well to read this book, and so would any financial professional who is looking for deeper insight into how the hedge fund industry operates.

¹ Dichev, I.,Yu, G., 2011. Higher risk, lower returns: What hedge fund investors really earn. Journal of Financial Economics 100, 248-263.

on a pack of cards. The casino interpretation seems even more apt for futures and options exchanges where the very structure of contracts traded emphasizes the “zero-sum” nature of the market. Casinos, of course, as suppliers of artificial risks to those with a taste for them, may well have their place in society, though presumably only a small place in a world already amply supplied with naturally occurring hazards. The danger some economists see is that as socially acceptable casinos, stock markets may actually be too attractive. They may mislead the unsophisticated into believing that stock market speculation offers a better, and certainly a quicker, way to wealth than working or saving.

That short-term trading of stocks (or futures or options) is a risky activity can hardly be denied. Indeed, much of the research thrust of the academic discipline of finance has been precisely to specify the probability distributions of returns from investments in different assets and over various horizons. But those distributions arise in a way fundamentally different from those of a casino. The distributions of returns on risky stock market investments are driven not by the random fall of dice or the spin of a wheel (although it is sometimes convenient in exposition to pretend that such is the case), but by the revelation or disclosure of new information about the underlying value of a security.

The information needed to value securities is not, however, just a mass of computer printout stored in a vault somewhere. Rather than a single objective entity, information, as Hayek (1945) has stressed, consists of millions of subjective bits and pieces scattered over the whole set of economic actors. One key function of secondary trading in the stock market is to aggregate these separate fragments of information. The prospect of speculative profits is the “bribe,” so to speak, society offers investors to speed the incorporation of the dispersed bits of information into prices. Once the information is incorporated, of course, everyone, including the uninformed, and not just the successful speculators, benefits from having more accurate prices on which to base decisions.”

—Merton H. Miller and Charles W. Upton “Strategies for Capital Market Structure and Regulation.” In Grundy, Bruce D., ed., Selected Works of Merton H. Miller, Vol. II: Economics. (Chicago: University of Chicago Press, 2002): 578-79.

Standard & Poor’s recent credit rating downgrade of nine Eurozone nations may have been treated as a big deal by the media, but for financial markets, the “news” was already in the price.

In fact, the market reaction to S&P’s lowering of the sovereign debt ratings of France, Austria, Malta, Slovakia, Slovenia, Italy, Spain, Portugal, and Cyprus has provided another timely reminder of how markets work.

This is not to downplay real concerns about the huge liabilities amassed by sovereign borrowers and the hardships being borne by their populations due to the profligate lending and borrowing of banks and governments.

But it is worth keeping in mind that, by the time the ratings agencies get around to registering their official disapproval, the market has already done the worrying for you. This really shouldn’t be a surprise, as the rating agencies work from the same information available to the market in aggregate.

As an example, let’s look at how the sovereign debt markets moved before and after the announcement by S&P on January 13. In this example, we look at the movements of bonds in three of the downgraded countries—France, Austria, and Spain—relative to those of Germany in the week prior and following the downgrade.

Germany is used as the benchmark here because it is perceived as the most secure sovereign borrower within Europe—the “risk-free” rate, if you like. By the way, the “spread” is the margin that investors demand for the additional risk of investing in France, Austrian, and Spanish bonds over German bonds.

What the tables below show is that these spreads all “tightened”—the peripheral bonds rallied in relation to German bonds—in both the week prior to the downgrade and the week afterward.

The third table shows what happened to spreads in the full two weeks surrounding the S&P ratings announcement. You can see that spreads of all three sovereigns narrowed in that period. Put another way, their prices rose more than comparable-maturity German debt. That means those bonds produced positive returns during what was widely portrayed in the media as a ratings “shock.”

The second set of three tables details those positive total returns relative to comparable maturity German bonds in the three periods.

Markets vs. Ratings Agencies, Round 1:

Change in Yield Spreads Relative to Comparable Maturity German Debt

January 6–13: Before the downgrades:

January 13–20: After the downgrades:

January 6–20: Two weeks around the downgrades:

Source: Bloomberg.

Markets vs. Ratings Agencies, Round 2

Sovereign Incremental Total Returns vs. Germany¹

January 6–13: Before the downgrades:

January 13–20: After the downgrades:

January 6–20: Two weeks around the downgrades:

Source: Bank of America Merrill Lynch Indices. Indices are not available for direct investment.

Markets vs. Ratings Agencies, Round 3

Credit Default Swaps as a Market Signal

Another way of looking at the superiority of market pricing as a signal of sovereign risk is to look at credit default swaps, or “CDSs.” These derivative instruments are a form of insurance policy that some investors take out against a loan default. There are CDSs for corporate borrowers and for sovereign borrowers. Broadly speaking, the higher the price of default insurance for each sovereign borrower, the greater the market sees as the risk of investors not getting their money back.

The very liquid market for CDSs is a useful guide to how the market views the relative risk of default among various sovereign borrowers. And it is clear that risk judged by the market and risk judged by credit rating agencies are not necessarily the same.

So until January 13 this year, Germany, France, and Austria were all assigned by Standard & Poor’s highest rating, AAA, reserved for borrowers deemed the most creditworthy. Spain was rated AA- (and was downgraded to A).

But the chart below, showing historical credit default swaps for Germany, France, Austria, and Spain, demonstrates that the market was pushing up the price of insurance on French, Austrian, and Spanish bonds well ahead of the downgrades.

In fact, by last November, the perceived risk of French and Austrian bonds relative to German bonds was seen as significantly greater, despite all three countries being nominally AAA rated borrowers. In other words, France and Austria were behaving more like AA bonds well before the downgrade.

Furthermore, the insurance on default was actually falling in the week before the downgrade, which shows once again how markets move ahead of the agencies.

Why would the market view France and Austria as presenting a greater sovereign risk than Germany despite all three countries sharing the same credit rating? Clearly, the market was working off contemporaneous information. The debt crisis was moving at such a pace that the news was running ahead of the official rating. In the case of France and Austria, they were perceived as having less flexibility than Germany in raising new loans and rolling over existing ones.

As an aside, some investors who are skeptical about the ratings agencies might seek to rely on macroeconomic signals such as a country’s public debt-to-GDP ratio, but as we showed in the previous edition of our sovereign risk analysis, these numbers are no more a reliable indicator of risk than credit ratings.

Japan, for instance, has the highest debt-to-GDP ratio in the developed world—at around 200 percent (even more than Greece)—yet it maintains a AA- credit rating against the junk status of Greece. Australia, with the lowest debt in the OECD, has a AAA rating from S&P, yet in the CDS market, it is rated a greater risk than the AA+ rated US, which has the advantage of being able to borrow in its own currency.

So which offers the best signal: the credit rating agencies, the economic fundamentals or the market? The answer to that question is that no one knows for sure, because no one has found a way to correctly and reliably forecast the future.

But in pricing risk, it is usually better to give greater weight to market signals—if for no other reason than the price represents the combined wisdom of millions of market participants staking real money on the outcome.

Markets incorporate all these pieces of information—economic variables, credit ratings, risk perceptions, willingness to pay—and put a price on them.

And that is why, in Dimensional’s case, our first point of reference is always the market itself, not economic variables or the credit rating agencies.

1. Incremental total return for a specific country and maturity range is defined as the total return of the country and maturity range minus the total return of the corresponding German maturity range.

I also find the titles bestowed on brokers interesting. They refer to themselves as “financial consultants” and “Vice-President.” Mutual funds play the same game. “Absolute return fund” implies a fund that always has positive returns. According to an article in The Wall Street Journal, while most (but not all) of these funds posted positive returns in the 2008-2009 time frame, “many were lackluster in comparison with the index returns and just two funds outpaced the SP 500′s gains.”

The clever name game is part of a larger strategy geared to get your business. It includes massive advertising (often using celebrities to enhance credibility), the availability of “trading programs” and niche marketing, like hosting seminars for women investors.

While these pitches for your business are fairly subtle, the gloves come off when brokers or advisers are competing for your business. It gets really ugly when one of the contenders is recommending an index based portfolio, which is what I believe should be the strategy followed by all investors. Here are some of the dirty tricks some brokers and advisers use to dissuade investors from index based investing:

Hiding Expenses

Since expenses are deducted from returns, it makes sense to be aware of the expenses of the funds in your portfolio. A study by Morningstar found the management fee charged by mutual funds (called “expense ratios”) are “strong predictors” of performance.

It is important to understand wrap fees, transaction costs, adviser fees, brokerage commissions and account management fees when computing the real cost of your investments. Transaction costs are easy to hide. Ask for the “turnover ratio” of the funds you are considering. A high turnover means higher trading costs. Index funds typically have lower turnover ratios than actively managed funds.

To get an overall understanding of expenses, ask for the “weighted expense ratio” of the recommended investments.

Higher Taxes

The returns of actively managed funds are typically reported pre-tax, which can be very misleading. One study (discussed here) looked at the 10 year pre-tax and after-tax returns of index funds and actively managed funds. It found that, on an after-tax basis, index funds outperformed 86% of active mutual funds.

Ask for the after-tax returns of the recommend funds.

Misleading tilt

There is significant research supporting the value of tilting the stock portion of a portfolio towards small and value stocks. Tilting towards these riskier asset classes can increase expected returns, albeit with increased risk. However, there are periods of time when large and growth stocks outperform small and value. For example, in 2011, large cap stocks outperformed small cap stocks.

By tilting the stock portion of a portfolio towards the asset class that outperformed in the past year or two, advisers can make it appear they have the ability to increase returns in the future. Don’t be fooled. If your adviser is recommending a tilt towards any asset class, ask to see long term data supporting this recommendation.

Using long term and lower quality bonds

By using long term (maturity dates more than 5 years) bonds, and bonds with ratings below investment grade, brokers and advisers can make it appear they are generating higher returns. Many investors don’t understand these returns come with higher risk. Historically, according to research done by Dimensional Fund Advisors, long term bonds are more volatile than shorter term bonds, but have not provided consistently greater returns. The same research indicated that bonds lower in credit quality have earned higher returns, but there is a greater risk of default.

You would be better advised to limit your bond holdings to maturities of five years or less and to insist that all of these holdings be rated investment grade or higher. You can increase your expected return (and your risk) by allocating a greater portion of your portfolio to stocks, assuming that would be suitable for you.

Using short term returns

Short term data can be extremely misleading. Some brokers and advisers cherry pick funds for inclusion in a recommended portfolio that have impressive three year returns. The implied message is that these funds are likely to outperform in the future. You can find a discussion of the benefit of longer term data here.

You should insist on seeing at least a 10-year history of returns and preferably longer.

There’s an old Chinese Proverb that says: “If you must play, decide upon three things at the start: the rules of the game, the stakes, and the quitting time.”

You now know some of the rules of the game.

Dan Solin is a senior vice president of Index Funds Advisors. He is the New York Times bestselling author of The Smartest Investment Book You’ll Ever Read, The Smartest 401(k) Book You’ll Ever Read, The Smartest Retirement Book You’ll Ever Read and The Smartest Portfolio You’ll Ever Own. His new book, The Smartest Money Book You’ll Ever Read, was published December 27, 2011.The views set forth in this blog are the opinions of the author alone and may not represent the views of any firm or entity with whom he is affiliated. The data, information, and content on this blog are for information, education, and non-commercial purposes only. Returns from index funds do not represent the performance of any investment advisory firm. The information on this blog does not involve the rendering of personalized investment advice and is limited to the dissemination of opinions on investing. No reader should construe these opinions as an offer of advisory services. Readers who require investment advice should retain the services of a competent investment professional. The information on this blog is not an offer to buy or sell, or a solicitation of any offer to buy or sell any securities or class of securities mentioned herein. Furthermore, the information on this blog should not be construed as an offer of advisory services. Please note that the author does not recommend specific securities nor is he responsible for comments made by persons posting on this blog.

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The international and domestic stock markets were negative or flat in 2011. The S&P 500 Index had a paltry return of 2.11 percent, which made it a standout performer among major markets. There were some big winners in the stocks making up the Dow Jones Industrial Average. McDonald’s gained 34 percent, Pfizer was up 28.6 percent, and IBM gained 27.3 percent.

[See The 10 Best Places to Retire in 2012.]

Brokers are on their phones calling their clients with recommendations for next year’s winners. They are also dispensing their views about where the market is headed in 2012.

Here’s my advice: Don’t listen to them. They have no more ability to pick winning stocks than a chimpanzee tossing a dart at a board. If they really knew where the market was headed, they would have predicted the biggest recession since the Great Depression and the ensuing rapid recovery.

Instead of engaging in the discredited notions of stock picking and market timing, you should be eschewing all individual stocks and bonds and limiting your investments to a globally diversified portfolio of low management fee stock and bond index funds in an asset allocation (the division of your portfolio between stocks and bonds) appropriate for you.

While you may understand the importance of globally diversifying your stock holdings, doing the same with your bonds is just as important. Few investors appreciate that almost 75 percent of the global government bond market is composed of non-U.S. bonds. While average returns of U.S. and non-U.S. bonds may not differ significantly, there can be meaningful differences in annual performance. By adding non-U.S. bonds to your portfolio (assuming the currency risk is hedged), you can reduce overall volatility, which is one of the primary benefits of diversification.

[See top-rated funds by category ranked by U.S. News Mutual Fund Score.]

It used to be quite difficult for investors to obtain international diversification of the bond portion of their portfolio in a cost effective manner. That’s about to change. Vanguard recently announced the Vanguard Total International Bond Index Fund, which will be available early this year. The fund will have a low expense ratio of 0.4 percent for the investor share class. Vanguard recommends an allocation to international bonds ranging from 20 percent to 40 percent for the bond portion of your portfolio.

Another option for those seeking international bond diversification is SPDR Barclays Capital Short Term Fund (BWZ). This fund tracks the Barclays Capital 1-3 year Global Treasury ex-U.S. Capped Index, which consists of fixed rate, investment grade debt issued by foreign governments of investment grade countries. It has an expense ratio of only 0.36 percent.

[See The Best and Worst Sources of Financial Advice.]

The next time your broker calls and wants to discuss how the international monetary crisis could affect your investments, stop him in his tracts. Tell him you want to focus on broadly diversifying both the stock and bond portion of your investments. Ask him to recommend an international bond index fund or exchange-traded fund. Don’t be surprised by the stunned silence at the other end of the line.

The situation in Europe is even more dire.  The euro is on life support.  Greece, Italy and Spain all have troubled economies.  Even China is experiencing an economic slowdown.

The securities industry and the financial media have gone into overdrive in an effort to “explain” this uncertainty.  A typical observation is this one from J.D. Steinhilber in a blog on Seeking Alpha: “I think the environment in 2012 will remain challenging and highly uncertain.”  Mr. Steinhilber advises investors  “…that when you don’t really know what lies ahead, but you know there are major potential hazards, it is wise to proceed with caution.”  I believe this advice is dead wrong.

It is precisely because of the uncertainty in the market that investors are rewarded.  If there were no risk, there would be little reward.  Treasury Bills are perceived by investors to carry very little risk because they are backed by the full faith and credit of the US. Treasury. The latest return on a one year Treasury Bill is 0.12 percent.  Little risk.  Little return.

Higher risk investments (like stocks) have a greater uncertainty of outcome and wider ranges of short term volatility. The opposite is true for low risk investments.  They have narrower ranges of short term volatility. You can find a chart illustrating the relationship between risk and reward here.

Current  prices for stocks and bonds are fair.  They are determined by millions of willing buyers and sellers who are fully informed about news and forecasts of future events.  Efforts to find mispricings in stocks and bonds are unlikely to be successful.

Based upon the assumption that prices are fair, you can expect a risk-appropriate fair return over time. I am not suggesting that you will always get a fair return on your investments.  All we know is that the further the actual future return is from a fair return, the less likely it will be.

You can find a helpful chart showing probability distributions of investments at various risk levels here.

It is the uncertainty of returns that creates the expectation of a future positive return.  If there were no uncertainty, there would be little or no return.

The proper way to invest is not to “proceed with caution.”  It is to avoid emotions by being prepared for the random outcome associated with the risk of your investments. Well educated investors don’t try to predict the impact of future events on their portfolios.  Instead, they understand the trade-off between risk and return.  They invest in a globally diversified portfolio of low management fee index funds in an asset allocation appropriate for them.  They don’t fear uncertainty.  They expect it and embrace it as the source of their returns.