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New Research On Performance Chasing

Re-posted from New Research On Performance Chasing

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This article originally appeared on ETF.COM here.

There is a considerable body of evidence demonstrating that the post-hire performance of active managers tends to be disappointing relative to their pre-hire performance. Specifically, managers’ performance tends to regress toward zero after adjusting for expenses, risk, exposure to common factors and survivorship bias. For example, the research has found that:

  • While 20 years ago, about 20% of actively managed funds were generating statistically significant alpha, that figure is now about 2% as the market has become more efficient, the competition has gotten tougher and, as described in my book, “The Incredible Shrinking Alpha,” academics have been converting what was once alpha (a source of outperformance) into beta (a common factor that can easily be replicated).
  • There is little evidence of performance persistence among hedge funds and actively managed mutual funds.

Problems with performance chasing

Despite the evidence, strong past performance is the prerequisite for manager selection by individuals as well as institutional investors. Robert Ferguson, Anna Agapova, Dean Leistikow and Joel Rentzler contribute to the literature on the persistence of performance among active managers with the paper, “Chasing Performance and Identifying Talented Investment Managers,” which appears in the Spring 2018 issue of The Journal of Investing. Their focus is on explaining why investors are likely to get poor results from performance-chasing.

The authors begin by noting that while choosing managers on the basis of historical performance might make intuitive sense, “it takes an impractically long time to differentiate talented from untalented managers – far longer than the five years or so that many investors believe is sufficient.”

They provide a mathematical example involving a world that contains 20 untalented managers (who have a normal distribution of returns with a mean alpha of 0 and a standard deviation of 2.68%) and one talented manager (who generates 3% alpha, which is very large, with a 3% tracking error).

Ferguson, Agapova, Leistikow and Rentzler demonstrate that we should expect, randomly (purely by luck), one of the 20 untalented managers will generate an alpha about 50% greater than 3% over the next 20 years. In fact, they write, “the probability that the talented manager beats all 20 untalented managers over the five-year period is only about 14.8%.”

Thus, performance-chasers end up with the untalented manager 85.2% of the time. And that is using a five-year horizon. Many institutions use three-year horizons, in which case the odds of hiring the talented manager would be even worse. Even at 10 years, the odds are just 36% that the talented manager will outperform all the untalented ones.

Making matters worse is that the probability the talented manager will beat all 20 untalented managers is surprisingly small for all lengths of measurement period. Even after 15 years, it only rises to about 55%. To achieve a 95% (99%) probability that the talented manager will outperform, you need a 38-year (54-year) historical performance record.

Such lengthy records are rare. Even if they existed, the likelihood is that the manager would have received so much cash flow that the hurdles to generating alpha would have become virtually insurmountable. That’s the curse of success – it sows the seeds of its own destruction.

Summary

The authors illustrated how the probability that a talented manager’s performance will exceed the best in a pool of untalented managers can be surprisingly small, even over long periods. It helps explain why performance-chasing has produced such poor results for individual and institutional investors alike. A better use of historical performance relegates it to a secondary role, the primary focus being an a priori analysis of a manager’s investment process (security selection and trading strategy).

Larry Swedroe is the director of research for The BAM Alliance, a community of more than 140 independent registered investment advisors throughout the country.

Larry Swedro at Computer Monitors

Swedroe: Irrelevance Of Dividends

Swedroe: Irrelevance Of Dividends | ETF.com

Research has established that dividend policy should be irrelevant to stock returns, yet investors have long demonstrated an irrational preference for them. Mutual fund providers are well-aware of this fact.

Earlier this week, we reviewed a pair of studies showing that mutual fund managers exploit investors’ well-documented preference for cash dividends to attract assets by artificially “juicing” the dividend yield, and that they use dividend-chasing behavior strategically to benefit themselves at the expense of fund investors. Today we’ll tackle some possible explanations for investors’ anomalous behavior.

Attempting To Explain The Preference For Dividends

Hersh Shefrin and Meir Statman, two leaders in the field of behavioral finance, attempted to explain the preference for the cash dividends anomaly in their 1984 paper, “Explaining Investor Preference for Cash Dividends.” They offered the following explanations.

First, in terms of their ability to control spending, investors may recognize they have problems with the inability to delay gratification. To address this problem, they adapt a “cash flow” approach to spending, meaning they limit their spending only to the interest and dividends from their investment portfolio.

A “total return” approach that used self-created dividends would not address the conflict created by the individual who wishes to deny himself or herself a present indulgence, yet is unable to resist the temptation. While the preference for dividends might not be optimal (for tax reasons), by addressing the behavioral issue, it could be said to be rational. In other words, the investor has a desire to defer spending, but knows he doesn’t have the will, so he creates a situation that limits his opportunities and, thus, reduces the temptations.

The second explanation is based on “prospect theory” (also referred to as loss aversion), which states that investors value gains and losses differently. As such, they will base decisions on perceived gains rather than on perceived losses.

So, if someone were given two equal choices, one expressed in terms of possible gains and the other in terms of possible losses, people would choose the former. Because taking dividends doesn’t involve the sale of stock, it’s preferred to a total-return approach that may require self-created dividends through sales. Sales might involve the realization of losses, which are too painful for people to accept (they exhibit loss aversion).

What they fail to realize is that a cash dividend is the perfect substitute for the sale of an equal amount of stock, whether the market is up or down, or whether the stock is sold at a gain or a loss. It makes absolutely no difference. It’s just a matter of how the problem is framed. It’s essentially form over substance.

Whether you take the cash dividend or sell the equivalent dollar amount of the company’s stock, you’ll end up with the same amount invested in the stock. With the dividend, you own more shares but at a lower price (by the amount of the dividend), while with the self-dividend, you own fewer shares but at a higher price (because no dividend was paid).

Consolation Prizes
Shefrin and Statman write: “By purchasing shares that pay good dividends, most investors persuade themselves of their prudence, based on the expected income. They feel the gain potential is a super added benefit. Should the stock fall in value from their purchase level, they console themselves that the dividend provides a return on their cost.”

They point out that if the sale involves a gain, the investor frames it as “super added benefit.” However, if the investor incurs a loss, he frames it as a silver lining with which he can “console himself.” Because losses loom much larger in investors’ minds, and because they wish to avoid them, they prefer to take the cash dividend, avoiding the realization of a loss.

Shefrin and Statman offer yet a third explanation: regret avoidance. They ask you to consider two cases:

1) You take $600 received as dividends and use it to buy a television set.

2) You sell $600 worth of stock and use it to buy a television set.

After the purchase, the price of the stock increases significantly. Would you feel more regret in case one or in case two? Since cash dividends and self-dividends are substitutes for each other, you should feel no more regret in the second case than in the first case. However, evidence from studies on behavior demonstrates that, for many people, the sale of stock causes more regret. Thus, investors who exhibit aversion to regret have a preference for cash dividends.

Shefrin and Statman go on to explain that people suffer more regret when behaviors are taken than when behaviors are avoided. When selling stock to create the homemade dividend, a decision must be made to raise the cash. When spending comes from the dividend, no action is taken; thus, less regret is felt. Again, this helps explain the preference for cash dividends.

The authors also explain how a preference for dividends might change over an investor’s life cycle. As mentioned previously, a theory incorporating self-control is used to justify spending only from a portfolio’s cash flow, never touching the principal.

Younger investors, who generate income from their labor capital, might prefer a portfolio with low dividends, as a high-dividend strategy might encourage dis-savings (spending from capital). On the other hand, retired investors with no labor income would prefer a high-dividend strategy for the same reasons, to discourage dis-savings. A study of brokerage accounts found that a strong and positive relationship between age and the preference for dividends did in fact exist.

While the preference for cash dividends is an anomaly that cannot be explained by classical economic theory (which is based on investors making “rational” decisions), investors who face self-control issues (such as a weakness for impulse buying) may find that, while there are some costs involved, the benefits provided by avoiding behavioral problems may make a cash dividend strategy a rational one.

Before summarizing, we have one more important point to cover. It involves how popularity drives down returns.

The Curse Of Popularity

The Federal Reserve’s zero-rate policy has led many investors to search for incremental yield, replacing safe bonds with riskier assets. Dividend-paying stocks are among the beneficiaries of these cash flows. That increased demand has impacted valuations, which are the best predictors of future returns. Higher valuations predict lower future returns. Until recently, dividend-paying strategies—specifically high-dividend strategies—called for the purchase of value stocks. Increased demand, however, has changed that.

The table below shows three value metrics—price-to-earnings (P/E), price-to-book value (P/B) and price-to-cash flow (P/CF)—for two of the market’s most popular dividend strategies: the SPDR S&P Dividend ETF (SDY), with more than $14 billion in assets under management (AUM), and the Vanguard Dividend Appreciation ETF (VIG), with more than $22 billion in AUM. Data is as of July 13, 2016. VIG buys the stocks of companies with rapid growth in their dividends.

The table also shows the two large-cap value ETFs with the most AUM, the iShares Russell 1000 Value ETF (IWD) and the Vanguard Value ETF (VTV). Finally, I’ll compare the value metrics of these funds with that of the SPDR S&P 500 ETF (SPY). As you review the data, remember that the lower the price metric, the higher the expected return. Data is from Morningstar.

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The above data makes clear that the popularity of the two dividend strategies (SDY and VIG) has led to a rise in the prices of these stocks and reduced their expected returns. No matter which value metric we look at, the expected returns for both SDY and VIG are now well below the expected returns of the two large value strategies, and also below that of the S&P 500 ETF. It’s an example of the curse of popularity, and what happens when a trade gets “crowded.” Forewarned is forearmed.

Summary

It seems that investors all over the world are prone to the same behavioral mistakes, mistakes that lead them into a preference for dividends. While Shefrin and Statman showed that at least some investors may derive some benefit (such as help in controlling spending), the preference is irrational from a financial economist’s perspective. It can lead to reduced diversification benefits and higher tax costs. And it can lead at least some investors to fall prey to mutual funds seeking to exploit the typical retail investor’s lack of financial knowledge.

For the past 20 years, the workhorse model in finance has been the Fama-French four-factor model—the four factors being beta, size, value and momentum. The model explains the vast majority (about 95%) of the differences in returns of diversified portfolios.

Newer asset pricing models, which include the profitability, quality and investment factors, have added further explanatory power. Yet none of them include dividends as a factor. If dividends played an important role in determining returns, these models wouldn’t work as well as they do.

In other words, if dividends added explanatory power beyond that of the factors I just mentioned, we would have a model that included dividends as one of the factors. But we don’t. The reason is that stocks with the same “loading,” or exposure, to these common factors have the same expected return regardless of the dividend policy. This has important implications, because about 60% of U.S. stocks and about 40% of international stocks don’t pay dividends.

Any screen for dividend stocks results in portfolios that are far less diversified than they could be if dividends were not included in the portfolio design. Less diversified portfolios are less efficient, as they have a higher potential dispersion of returns without any compensation in the form of higher expected returns (assuming exposures to the factors are the same).

Additionally, you have seen how the preference for dividend stocks has driven dividend strategy valuations to levels well above the valuations of value strategies and the overall market. This should raise concerns about future returns.

Larry Swedroe is the director of research for The BAM Alliance, a community of more than 140 independent registered investment advisors throughout the country.

Market Volatility

Learning to Ignore Short-Term Fund Performance Relative to Indexes

Our clients generally understand that focusing on the short-term performance of a fund relative to another fund or an index is a waste of time. These differences rarely tell you anything important about long-term performance and, in fact, can lead to counterproductive behavior if you are prone to selling funds that underperform to move into funds that have outperformed. These performance differences, after all, tend to reverse more often than not. We call this “returns-chasing behavior” and it is one of the surest paths to poor long-term performance. Jared Kizer, chief investment officer for the BAM ALLIANCE, frequently receives questions about performance differences — from clients and advisors alike. He shares his insights below.

I have spent years thinking about this issue and analyzing hundreds of performance cases and performance attribution analyses. I find that there are two areas that drive a lot of these questions, and I hope to clarify both:

  • What do you mean by “short term”?
  • How big can performance differences be over short-term periods of time?

Before digging in, let’s talk about the structure of the funds we use in client portfolios relative to index funds.

Evidence-Based Funds Vs. Index Funds

The funds we use are rarely index funds, meaning by definition they will not precisely track well-known indexes. In fact, most of the funds we use have significantly different compositions from the indexes they are most frequently compared to. This is not an accident. We purposefully use funds that do not explicitly track indexes.

Going into all the details behind this is beyond the scope of this piece. In short, we want to maximize the benefits of indexing — low costs, generally low turnover of holdings, broad diversification and tax efficiency — and minimize the negatives. As great as index funds are, published research has shown they can have negatives. For example, some indexes rebalance in a way where other managers know the stocks (or bonds) that are likely to enter and leave the index on the rebalancing date. This degree of transparency can allow these managers to take advantage of index funds, which reduces long-term performance. This effect is most frequently documented in Russell’s indexes and some of the larger indexes like the S&P 500. Indexes also frequently do not target specific styles like size, value and momentum in ways we think make the most sense given what academic research shows.

Evidence-based funds can alleviate these problems, but that does not guarantee these funds will always outperform an index strategy or outperform similarly constructed evidence-based funds. In fact, they can underperform for long periods of time without offering an indication that the fund is designed poorly or managed poorly. Investors in these funds must remain disciplined during these periods to realize the expected benefits.

What Is “Short Term” and How Big Can Differences Be?

Investors are not always happy with my answer to the time horizon question. In truth, anything is possible for periods of less than five years — and by no means does even five years guarantee the expected result. I want to illustrate this point using performance comparisons over months, quarters and years. In the first figure on the next page, I take the month-by-month differences in return between the stock funds that compose our Risk Target 3 model and the indexes they are most frequently compared to. I then find the pair with the largest amount of underperformance (meaning underperformance of the fund relative to the index) for that particular month and plot that result over time. My analysis starts in October 2005 since that was the first full quarter where five of the seven stock funds in our Risk Target 3 strategy had live returns data.

Figure 1: Differences in Monthly Performance

Figure 1 Differences in Monthly Performance

This analysis shows that in virtually every month at least one of the funds in our model portfolio has underperformed the index by 1 percent or more. In fact, there are multiple months where one of the funds underperformed the index by 2 percent or more. We also see that there are very few months where all the funds outperform their indexes. Let’s now move to quarterly returns.

 Figure 2: Differences in Quarterly Performance

Figure 2 Differences in Quarterly Performance

Here we see that the differences generally get larger, not smaller. There are now a decent number of periods where at least one of the funds underperformed the index by 4 percent or more. Keep in mind, this same concept holds true if we were comparing a particular fund to another fund (e.g., comparing DFA Small Value to DFA Targeted Value). We now move to annual returns.

Figure 3: Differences in Annual Performance

Figure 3 Differences in Annual Performance

The first full year of annual returns data is 2006. While we have limited data to analyze, we generally see again that the differences get larger, not smaller. In fact, in 2008 one of the funds we use underperformed the index by about 13 percent. That does not mean the fund is bad and should be replaced. This is just the nature of shorter-term performance comparisons. We also now see that at least one fund underperformed its index over the full year in every period.

So, this analysis tells us that in periods going out to one year we can expect to see that some funds have underperformed their index by 4 percent or more. It also tells us there will be periods where a fund underperforms its index by even more. We expect and know this will happen with the funds we use.

If this degree of underperformance continues over even longer periods, our Investment Policy Committee has processes to evaluate results and determine whether anything is materially wrong with the fund’s strategy. Most frequently, we find that even longer periods of performance are completely explainable and not a reason to replace the fund. For example, for periods ending in 2015, many of the funds we use had underperformed indexes over longer periods of time because value stocks had done poorly relative to growth stocks. Many of our funds are deeply tilted toward value stocks when compared with indexes, so this was the main explanatory factor behind the performance result. In these cases, the funds did exactly what they were intended to do. It just happened to be a bad period for value stocks.

In summary, acting on short-term performance results is usually detrimental to long-term performance. By the nature of financial markets, the funds we use will periodically underperform indexes and other funds over longer periods of time. The key to seeing the expected benefits — as with many areas of evidence-based investing — is realizing this, not reacting to it, and having the discipline to stick with your strategy and the funds within it over the very long-term.

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