Larry Swedroe on research into how factor ETFs impact the way investors evaluate active managers.
Larry Swedroe, Director of Research, The BAM Alliance
In our book “The Incredible Shrinking Alpha: And What You Can Do to Escape Its Clutches,” my co-author Andrew Berkin, director of research for Bridgeway Capital Management, and I document the persistent decline of the ability of active managers to generate risk-adjusted alphas.
We show that while 20 years ago about 20% of actively managed funds were generating statistically significant alphas, today that figure is about 2%. As we discuss, one of the four themes behind this trend is that academics have been busy converting what was once alpha (a scarce resource for which active funds can charge high fees (what economists call “economic rent”) into beta (exposure to common factors and thus a “commodity”).
Additionally, providers of products have developed passively managed vehicles (such as index funds and what are often referred to as “smart-beta ETFs”) that allow investors to access these common factors at low cost and in tax-efficient ways. In fact, in terms of total net assets, nonmarket-tracking (factor-based) ETFs have exceeded market-tracking ETFs since 2009.
Increased Competition
These new vehicles have created much greater competition for actively managed funds, whose performance can now be judged not against the market or a single-factor CAPM, but against more appropriate risk-adjusted benchmarks, such as ETFs, that provide exposure to the desired factors.
Earlier research showed that investors rewarded actively managed funds with inflows if they generated alphas against the single-factor CAPM; investors were naive, failing to account for exposure to other factors that are included in now commonly used multifactor models, such as the Fama-French three-factor model (beta, size and value), the Carhart four-factor model (adding momentum) or the Fama-French five-factor model (beta, size, value, investment and profitability).
In other words, if an actively managed fund outperformed the market by having more exposure to value stocks during a period when value stocks outperformed, the fund was rewarded with new cash flows.
This occurred despite the outperformance being explained by exposure to the value factor—not stock selection or market timing skill—and that same exposure could have been obtained more cheaply through a low-cost index fund or ETF. In other words, investors were ignoring the fact that the Fama-French three-factor model had been the workhorse model in finance since 1993, and the Carhart model had superseded it by 2000.
Factor Fund & Investor Behavior
Jie Cao, Jason Hsu, Zhanbing Xiao and Xintong Zhan contribute to the literature with their May 2017 paper “How Do Smart Beta ETFs Affect the Asset Management Industry? Evidence from Mutual Fund Flows.” They examined the impact of factor-based equity ETFs on how investors evaluate mutual fund performance.
Their objective was to determine if the increased availability of factor-based ETFs made investors more sensitive to risk-adjusted alphas and adjusted their fund flows accordingly. Their database covered nearly 4,000 funds and the period 2000 through 2015.
Cao, Hsu, Xiao and Zhan found that, over time, flow sensitivity to the alphas increased significantly after accounting for exposure to the common factors identified in the now-prevalent asset pricing models—over the period, the dominance of the CAPM model over the multifactor models weakens and even disappears.
They also found that this change was more significant for funds with higher exposure to nonmarket risks (such as size, value and momentum) and funds with more sophisticated (institutional) investors, who are more likely to understand sophisticated models as well as risks other than market beta, and thus more likely to use factor-based ETFs as investment tools.
In summary, the authors document that ETFs, which are known for their indexing and tracking attributes, are also impacting investment flows by allowing investors to more properly benchmark the performance of active managers and providing lower-cost and more tax-efficient ways to access common factors.
They concluded: “Investors no longer reward managers for being exposed to common risk factors when ETFs, which could replicate the return to such risk factors, are actively traded.”
Because of the competition from factor-based ETFs, active managers now must demonstrate they can outperform after deducting the influence of easily measurable factor exposures. The findings gain significance when viewed in light of the fact that, according to Morningstar, active funds saw outflows of $285.2 billion in 2016, while passive funds attracted inflows of $428.7 billion.
Conclusions
The bottom line is that investors are becoming more sophisticated in how they evaluate the performance of active managers. That’s good news for investors and bad news for active fund sponsors, including hedge funds, many of which rely on factor-based strategies, but charge much higher fees than their competitor ETFs. This increasing sophistication increases the already-high hurdle for active managers to overcome.
The reason is that it allows investors to differentiate between those active funds that beat the market because of either skill or luck, and those that beat the market simply because they had exposure to common factors, which could be obtained more cheaply. As investors exit funds without sufficient skill to outperform, those funds will be sent to the mutual fund graveyard.
The result will be that the remaining competition will have a higher level of skill, increasing the hurdle for active managers to overcome—there will be fewer suckers at the poker table that can be exploited in the zero-sum game that is the quest for alpha, even before fund expenses, and a negative sum game after expenses.
This persistently increasing level of skill is another of the four themes explored in our book “The Incredible Shrinking Alpha.”
This commentary originally appeared June 5 on ETF.com
By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party Web sites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them.
The opinions expressed by featured authors are their own and may not accurately reflect those of the BAM ALLIANCE. This article is for general information only and is not intended to serve as specific financial, accounting or tax advice.
© 2017, The BAM ALLIANCE
Bill Kaiser explores some financial tasks to consider before sending your child off to college.
Bill Kaiser, Wealth Advisor, Bland Garvey Wealth Advisors
As the high school graduation parties wind down and your child begins counting up their gift money, now is the time to get a few things in order before they head off for their first year of college. Consider the following shortlist:
Begin Building Credit
If you haven’t already done so, have your child establish a checking account for their summer job paychecks and graduation gifts. Most banks have accounts that can be linked (or “householded”) to your own to help avoid larger minimum balances or costly monthly fees. If your child is working this summer, have them set up direct deposit with their employer so their pay goes directly into their own account.
Next, have them apply for a credit card. It is never too early to begin building a credit score, and now is the perfect time to do it. Many times, the financial institution at which you set up their checking account will also offer a credit card. There are many different types of credit cards, and some companies offer cards with terms designed specifically for college students. However, such credit cards don’t always go directly toward building a credit score. Before applying for a card, be sure to ask if it will count toward building your college-bound child’s credit.
Then, have your child use their credit card (not their debit card) for all of their purchases. You can set up the card payment to be automatically withdrawn from their checking account a few days before the due date every month (to avoid racking up any interest) and in such a way that the balance is paid in full. This will give them the responsibility of learning how to use a credit card while keeping track of what they are charging and making sure that they have the money in the bank to cover their monthly bill. It also (hopefully) teaches them that it is best to pay their bill in full each month and never to incur debt that they can’t pay off. By the time they graduate, they will have four full years of credit history.
In addition, credit cards are a much safer way to make payments than using a debit card. The credit card company is liable for the purchase, so if fraud occurs, most card companies will back the card holder and cancel the charge. If you are using a debit card, the cash is automatically withdrawn from your account and it can be much harder to recover in the case of fraud or an erroneous transaction on your account.
Another benefit of credit cards is that you can set up fraud alerts and be notified of purchases over a certain dollar threshold. I actually set up this feature on my daughter’s credit card account to notify me of any purchase she makes over $1. In effect, I receive a text message each time she uses her card. So I know not only when she is using it, but where she is spending her money. One might say that is “over-parenting” a little. Perhaps that’s true, but if I am contributing to her cost of college, I think it is a fair trade-off to know where her money is being spent.
Monitor Social Media Accounts
If you haven’t already done so, you should become a follower of all of your child’s social media accounts. That includes Facebook, Twitter, Instagram, etc. We just recently saw how the use of social media got out of control for a few Harvard applicants. Don’t let it happen to your child. You can always create an anonymous account with no followers of your own and use it solely to follow your child. That way their friends won’t even know you are following and so won’t feel inhibited. Again, one might argue that this is “over-parenting.” But I say that it’s your child, and even though they are no longer a minor, you should know what they are doing. As I stated before, if I’m paying the bill, it seems like a fair trade off.
Prepare Legal Documents
While we are on the topic of your child no longer being a minor, it is imperative to have certain legal documents in place before they leave for school. Because they are of majority age, they do have their own right of privacy and protection under the law. Thanks to the Health Insurance Portability and Accountability Act (HIPAA), that includes what can be released in a medical situation.
Consider the following: Your child is in an automobile accident and is brought unconscious to the hospital. You are notified by their friends and rush to the emergency room in hopes of speaking to the doctors. Unfortunately, by law, they cannot disclose any information to you unless your child has appointed you as an authorized party through a HIPAA release form.
Be sure to have the following legal documents drawn up and executed prior to your child’s departure for college:
The first year of college is a very exciting time, but with it can come anxiety for both the student and the parent. Think about using this summer as an opportunity to take the steps necessary to mitigate some of that angst through the preceding tips, and to help ensure a smooth transition for your child from parental dependence to greater autonomy.
Learn more about Bland Garvey Wealth Advisors
By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party Web sites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them.
The opinions expressed by featured authors are their own and may not accurately reflect those of the BAM ALLIANCE. This article is for general information only and is not intended to serve as specific financial, accounting or tax advice.
© 2017, The BAM ALLIANCE
Larry Swedroe explores research into data-mined anomalies and how to reduce "p-hacking" risk.
Larry Swedroe, Director of Research, The BAM Alliance
Since the mid-1990s, factor-based exchange-traded funds have experienced spectacular growth. By mid-2016, these funds had about $1.35 trillion under management, accounting for about 10% of the market capitalization of U.S. traded securities.
At its most basic level, factor-based investing is simply about defining, and then systematically following, a set of rules that produce diversified portfolios. An example of factor-based investing is a value strategy: buying cheap (low valuation) assets and selling expensive (high valuation) assets.
A problem with factor-based investing is that smart people with even smarter computers can find factors that have worked in the past but are not real—they are the product of randomness and selection bias (referred to as data snooping, or data mining).
The problem of data mining is compounded when researchers snoop without first having a theory to explain the finding they expect—or hope—to find. Without a logical explanation for an outcome, one should not have confidence in its predictive ability.
The Problem Of P-Hacking
“P-hacking” refers to the practice of reanalyzing data in many different ways until you get a desired result. For most studies, statistical significance is defined as a “p-value” less than 0.05—the difference observed between two groups would not be seen even 1 in 20 times by chance. That may seem like a high hurdle to clear to prove that a difference is real. However, what if 20 comparisons are done and only the one that “looks” significant is presented?
The problem of data mining, or p-hacking, is so acute that professor John Cochrane famously said that financial academics and practitioners have created a “zoo of factors.” For example, a May 11, 2017, article in the Wall Street Journal states: “Most of the supposed market anomalies academics have identified don’t exist, or are too small to matter.”
In their 2014 paper “Long-Term Capital Budgeting,” authors Yaron Levi and Ivo Welch examined 600 factors from both the academic and practitioner literature. And authors Campbell Harvey (past editor of The Journal of Finance), Yan Liu and Heqing Zhu, in their paper “…and the Cross-Section of Expected Returns,” which was published in the January 2016 issue of the Review of Financial Studies, reported that 59 new factors were discovered between 2010 and 2012 alone.
Kewei Hou, Chen Xue and Lu Zhang contribute to the literature on anomalies and market efficiency with their May 2017 paper “Replicating Anomalies.” They conducted the largest replication of the entire anomalies literature, compiling a data library with 447 anomaly variables.
The list includes 57, 68, 38, 79, 103 and 102 variables from the momentum, value-versus-growth, investment, profitability, intangibles and trading frictions categories, respectively. To control for microcaps that are smaller than the 20th percentile of market equity for New York Stock Exchange (NYSE) stocks, they formed testing deciles with NYSE breakpoints and value-weighted returns. They treated an anomaly as a replication success if the average return of its high-minus-low decile is significant at the 5% level (t ≥ 1.96).
Following is a summary of their findings:
Microcaps Skew Results
Hou, Xue and Zhang ask: “Why does our replication differ so much from original studies?” Their answer is in one word—microcaps—which represent only about 3% of the total market capitalization of the NYSE-AMEX-Nasdaq universe, but account for about 60% of the number of stocks. They note that “microcaps not only have the highest equal-weighted returns, but also the largest cross-sectional standard deviations in returns and anomaly variables among microcaps, small stocks, and big stocks.”
Many studies overweight microcaps with equal-weighted returns, and often together with NYSE-AMEX-Nasdaq breakpoints, in portfolio sorts. Further, the authors add: “Due to high transaction costs and illiquidity, anomalies in microcaps are unlikely to be exploitable in practice.”
I would add that this doesn’t necessarily make the information useless, as long-only investors can improve their outcomes by avoiding (screening out) the short legs of anomalies. In that manner, they avoid both the high trading costs and the high costs of shorting.
Hou, Xue and Zhang concluded that their evidence suggests that capital markets are more efficient than previously reported. Their findings also help explain why many anomalies documented in the academic literature seem to disappear, reverse or weaken post-publication. Another explanation is that if there is no logical reason for the anomaly to exist, and there are no limits to arbitrage, sophisticated investors trade to correct mispricings, eliminating the anomaly.
Avoiding P-Hacking
Hou, Xue and Zhang offered suggestions to reduce the risk of p-hacking, including more out-of-sample testing (many studies examine only U.S. data) and the providing of economic explanations (either risk- or behavioral-based) for the presence of a factor’s premium.
These are among the issues Andrew Berkin, director of research at Bridgeway Capital Management, and I address in “Your Complete Guide to Factor-Based Investing: The Way Smart Money Invests Today,” which was published in October 2016.
To address the issues raised in “Replicating Anomalies” and to bring clarity out of complexity and opaqueness, we provide the evidence demonstrating that, within the “factor zoo,” you need only a handful of factors to invest in the same fashion as legendary investors like Warren Buffett. And we show you how to do it in a low-cost, tax-efficient way.
To minimize the risk of p-hacking and to address the concerns we have been discussing, for a factor to be considered, we provide specific criteria, each of which must be met. To start, the factor must provide explanatory power to portfolio returns and have delivered a premium (higher returns). Additionally, it must be:
The good news is that, among all the factors in the zoo, we show that you need to focus only on the eight that meet our criteria: beta, size, value, momentum, profitability, quality, term and carry.
What about all those other factors?
Some have not passed the test of time, fading away after their discovery, perhaps because of data mining or random outcomes. Or perhaps the factors worked only for a special period, regime or narrow band of securities. And many factors have explanatory power that is already well captured by the factors we recommend. In other words, they are variations on a common theme (e.g., the many definitions of value).
If you are considering or are already engaged in factor-based investing, I offer these words of caution from the conclusion of our book:
“First, as we have discussed, all factors—including the ones we have recommended—have experienced long periods of underperformance. So, before investing, be sure that you believe strongly in the rationale behind the factor and the reasons why you trust it will persist in the long run. Without this strong belief, it is unlikely that you will be able to maintain discipline during the inevitable long periods of underperformance. And discipline is one of the keys to being a successful investor. Finally, because there is no way to know which factors will deliver premiums in the future, we recommend that you build a portfolio broadly diversified across them. Remember, it has been said that diversification is the only free lunch in investing. Thus, we suggest you eat as much of it as you can!”
This commentary originally appeared May 19 on ETF.com
By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party Web sites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them.
The opinions expressed by featured authors are their own and may not accurately reflect those of the BAM ALLIANCE. This article is for general information only and is not intended to serve as specific financial, accounting or tax advice.
© 2017, The BAM ALLIANCE