A couple of weeks ago, I wrote a column about the growing tribe of people who value experiences over security in their lives. But there is something that I didn’t say then that I want to emphasize: You don’t necessarily have to trade experience and financial security off against each other.
One of my main inspirations for writing this follow-up column was my friend, Brett Davidson. A few years ago, Brett and his wife, Debbie, lived in Britain. They were running the successful consulting firmFP Advance with the goal of helping financial advisers live the lives they so often help their clients achieve. Brett and his wife, who have no children, had a nice home with beautiful furniture, and everything was going about as well as anyone could hope for.
Except they weren’t exactly happy with the way they were living their lives. So they decided to visit a life coach, Kerri Richardson.
“The very first conversation I had with Kerri,” Brett recalled, “I had just read a book, and one of the key questions in the book was, ‘If you lived without fear, what would you do?’” Eventually, they chose to take a turn toward the unconventional.
Here’s a portion of my conversation with Brett after he and Debbie made their decision:
“We began with just taking more time off. However, about a year before we left London, we decided that working around a quarterly schedule for our face-to-face work would be O.K. for our clients and for us. At Kerri’s insistence, we started investigating what would be involved with renting our home out. We got an auctioneer around to see if we might sell our furniture via auction (as we’d decided that anything you ever put in storage never comes back out, so let’s bite the bullet and let it go). The auctioneer guy turns up in late April or early May and says, ‘I love your stuff, but I need it now so we can photograph it and get it in our catalog for June.’ We looked at each other and said, ‘Take it.’ That forced our hand. Two days later, we had no furniture, and so we got serious about renting our place out. Four weeks later, we’d found tenants who moved in, and we left.”
Since leaving the comfort and security of their ordinary existence in London, the Davidsons now have a pretty nice life. Their itinerary over the last year has included time in Amsterdam, Iceland, Canada and Spain, with intermittent trips back to Britain for work. They’ve made time for a ski instructor course and yoga retreat.
The point is not to make you jealous. Instead, ask yourself the same question that Brett and Debbie have asked themselves: “Why not?” What if you really did follow the advice of Henry David Thoreau and “live the life you’ve imagined?” Given all the tools and opportunities we have to work remotely (especially if you’re part of free agent nation), I’m beginning to suspect that this is more a problem of imagination than actual constraints.
Even if you don’t own your own company, the opportunities exist. According to Flex Jobs, an online service devoted to helping people find positions that allow for remote work, there was a 36 percent increase from 2014 to 2015 in listings for such jobs, including some for writers, engineers, health care consultants and marketing professionals. Companies like Amazon, American Express, Apple and General Electric were included in the listings.
Worried about flexibility? The Davidsons are financially successful. Not having children makes a big difference, too (though not as big as you may think, which is something I’ll address in a future column).
Worried about money? The Davidsons are not spending significantly more money to live this way. Between the money they earn renting out their home in London and being smart about airline miles or buying cheap flights, they are close to breaking even compared with their previous life.
So it’s not a change in expenses that has allowed the Davidsons to make this shift. They are able to live in this remarkable way because they restructured their lives in a way that would allow it. It’s simply because they had the courage to ask, “Why not?”
And if you’re wondering how this radical shift affected their income, here’s what the Davidsons have to say: “Since we’ve left home, we believe we’ve become more creative in our business and are doing some of the best work we’ve ever done. We’re thinking bigger, but also eliminating the ‘fake busy’ stuff and only doing things that will really make a difference. We didn’t know any of this would happen before we left.”
Consider that for a moment. Not only are Brett and Debbie living closer to their dream, they also say they are doing better work professionally. Experience? Check. Security? Check. Winning? Checkmate.
Experiences and security don’t have to be mutually exclusive. And the surprising fact that the Davidsons’ business has improved with this radical shift, even though that wasn’t their main intention, has at least made me wonder something. What if experience and security might be connected in a way that goes against the grain of the story society typically likes to tell? What if putting experience first makes us happier, more fulfilled, more creative and more memorable people? There’s a lot of research to suggest that this might be the case.
None of this is to suggest you drop everything and live like the Davidsons. Maybe you don’t want to travel. Maybe your dream is to work at home in your pajamas and walk the dog an extra two miles each day with the time you’ve saved from your old commute. That’s great.
It doesn’t matter what your dream is, in particular. What does matter is that whatever you want to do, you start asking yourself a simple question: “Why not?”
This commentary originally appeared May 24 on NYTimes.com
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© 2016, The BAM ALLIANCE
Many investors and advisors who implement multifactor portfolios tend to focus on capturing the value premium over the size premium, often for the simple reason that, historically, the value premium has been larger.
Others have even challenged the size premium’s very existence, citing a weak and varying historical record. In both situations, it may be that the size premium—and specifically the construction of the size factor—is not fully understood.
My colleague Sean Grover, a member of the investment strategy team at Buckingham and The BAM Alliance, put together the following analysis of size factor construction to help address and clarify this issue. He begins with some basic definitions.
Defining The Size Factor
The size factor, as defined by Eugene Fama and Kenneth French, is constructed by sorting all stocks by market capitalization, as determined by market capitalizations of NYSE stocks, into deciles and then taking the weighted average annual return of deciles 6-10 (small stocks) minus the weighted average annual return of deciles 1-5 (large stocks). In other words, it’s the top 50% of stocks ranked by size minus the bottom 50%.
Contrast this with the value factor, which is constructed by sorting stocks on book-to-market ratio and then taking the weighted average annual return from deciles 1-3 (value stocks) minus the weighted average annual return from deciles 8-10 (growth stocks). In other words, it’s the top 30% of stocks ranked by valuation metric minus the bottom 30%.
In this construct, deciles 4-7 are considered core stocks. The 30/30 construction is also used for other established risk factors, such as momentum, profitability, quality and low beta/low volatility. The size factor is the only exception.
Using data from the University of Chicago’s Center for Research in Securities Prices (CRSP), Figure 1 presents historical returns for grouped market-capitalization deciles.
As illustrated with these market-capitalization deciles, if there’s a premium in some category of stocks over another, then that premium will be larger, the more strictly that category is defined.
As we can see with the more narrow size grouping, as stocks get smaller, their returns get higher.
In addition, the more strictly the category is defined, the more difficult it should be to capture. So in trying to understand the size premium, we ask: How does the construction of the size factor affect the amount of the premium that a portfolio can capture?
Different Perspectives On Size
Kenneth French’s data library provides returns for a variety of percentile sorts on market capitalization. Using these, we are able to build several different versions of the size factor in an attempt to answer our question.
The standard size factor—defined above as the weighted average return of the smallest 50% of stocks less that of the largest 50%—will be designated 50/50. We then construct size factors using the smallest (largest) 30%, 20% and 10% of stocks, which we’ll call 30/30, 20/20 and 10/10, respectively.
Figure 2 shows the historical annual premium for these various definitions of the size factor.
As expected, the more narrowly we define “small cap” versus “large cap,” the larger the annual premium. The standard 50/50 size factor has the smallest annual premium and, notably, the premium resulting from the 30/30 construction is actually larger than the value premium (which is 4.83%). Furthermore, all the annual premiums are statistically significant (meaning they have a t-statistic of greater than two).
To measure how much of a given premium a portfolio is able to capture, multifactor investors turn to estimated factor loadings from a factor model regression. For three small-cap indexes, Figure 3 shows the estimated size factor loadings from a four-factor model for our various size factor constructions.
Again, we find that the more narrowly we define the construction of the size factor, the more difficult it is to capture the premium. For each index, the more narrowly the size factor is defined, the smaller the estimated loading. Note that all the estimates shown in Figure 3 are statistically significant.
Real-World Examples
We can perform the same exercise for live funds as well. Consider Figure 4, which shows the results for the same exercise as Figure 3 but using three small-cap funds. (In the interest of full disclosure, my firm, Buckingham, recommends DFA funds in constructing client portfolios.)
Again, we find that the more narrowly the size factor is defined, the smaller the estimated loading. In this case, consider that even though there is significant variation between funds for a given size factor construction, each fund still shows a decrease in estimated loadings with stricter size factor definitions.
We have now fleshed out our hypotheses concerning the effect the construction of the size factor has on the magnitude of the size premium, and on a portfolio’s ability to capture it.
Using two funds, the DFA U.S. Micro Cap Fund from Figure 4 and the DFA Large Cap Value Fund, we can take a look at how the differences in construction between the size factor and the value factor affects the amount of the premium a portfolio is able to capture. This is measured simply by multiplying a portfolio’s estimated factor loading by the respective annual premium. Figure 5 shows this calculation for the two funds.
Despite the value premium being larger than the size premium, the portfolio targeting the size factor, the DFA U.S. Micro Cap Fund, actually captures more factor premium. This is due to the higher factor loading, which, we have shown, results directly from the less strict construction of the size factor.
Although brief, this example pretty clearly shows that the magnitude of factor premia should not be the sole consideration for multifactor investors choosing their allocation to risk factors. The important takeaway is that size factor construction—and thus portfolios’ increased ability to capture the size premium—needs to be considered when evaluating the size premium. The investor who ignores the size premium may very well be missing out on sizable factor premia.
If you’re interested in further discussion about the size premium, an article I wrote last year on a paper by Cliff Asness, Andrea Frazzini, Ronen Israel, Tobias Moskowitz and Lasse Pedersen, “Size Matters, If You Control Your Junk,” examines the problem of a disappearing size premium by controlling for the quality factor.
This commentary originally appeared May 20 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.
© 2016, The BAM ALLIANCE
One of the questions I’m most often asked by reporters covering finance is: “What are the biggest risks facing investors?” My usual response is that the biggest risk confronting most investors is staring right back at them when they look in the mirror. And there’s plenty of academic research to support that view.
Much of that research comes from the field of behavioral finance, which is the study of human behavior and how that behavior leads to investment errors, including the mispricing of assets, thus demonstrating investors aren’t always fully rational, and that markets aren’t perfectly efficient.
Kent Daniel and David Hirshleifer, authors of the paper “Overconfident Investors, Predictable Returns, and Excessive Trading,” which was published in the fall 2015 issue of the Journal of Economic Perspectives, discuss the role of overconfidence—having mistaken valuations and believing in them too strongly—as an explanation for pricing errors, otherwise known as anomalies.
Findings
In their study, Daniel and Hirshleifer cite a wealth of literature that demonstrates:
People tend to be overoptimistic about their life prospects, and this optimism directly affects their financial decisions.
Overconfidence has been documented among experts and professionals, including corporate financial officers as well as professional traders and investment bankers.
Overconfidence includes overplacement (overestimation of one’s rank in a population on some positive dimension) and overprecision (overestimation of the accuracy of one’s beliefs). An example is the overestimation of one’s ability to predict future stock market returns.
A cognitive process that helps support overconfident beliefs is self-attribution bias, in which people credit their own talents and abilities for past successes while blaming their failures on bad luck. Self-attribution bias allows overconfidence to persist. When investors “get it right,” they upgrade their confidence in their beliefs; but when they “get it wrong,” they fail to downgrade it.
Individual investors trade individual stocks actively, and on average, lose money by doing so. The more actively investors trade (due to overconfidence), the more they typically lose.
The stocks that individual investors buy tend to subsequently underperform, and the stocks they sell tend to subsequently outperform.
Actively managed funds that charge high fees without delivering correspondingly high performance provide evidence that most individual investors in active funds are overconfident about their ability to select high-performing managers.
Men are more overconfident than women in decision domains traditionally perceived as masculine, such as financial matters. Overconfidence leads to more trading. One study found that, consistent with higher confidence on the part of men, the average turnover for accounts opened by men is about 1.5 times higher than for accounts opened by women, and as a result, men pay almost 1% per year more in higher transaction costs, and their net-of-fee returns are far lower.
Individual investors tend to trade more after they experience high stock returns.
Overconfidence is likely to be especially important when security markets are less liquid and when short-selling is difficult or costly (i.e., there are limits to arbitrage at work). When short-selling becomes constrained, pessimists find it harder to trade on their views than optimists, resulting in overpricing. Thus, when overconfidence is combined with constraints on short sales, we expect the security to become overpriced.
Overconfidence plays a greater role when analysts disagree more, as measured by the dispersion in their forecasts of a firm’s future earnings. Firms with the largest dispersion of forecasted earnings tend to become overpriced, because the more pessimistic investors don’t express their views through trading. Thus, on average, these stocks earn lower returns.
Because volatility creates a greater scope for disagreement, the overpricing of more volatile stocks is more prevalent—high-idiosyncratic-volatility stocks earn lower subsequent returns than low-volatility stocks.
Overconfidence Explains A Lot
Daniel and Hirshleifer explain: “Overconfidence provides a natural explanation for the irrational tendency for investors to be too insistent in disagreeing, and for optimists to fail to fully adjust for the fact that there are pessimists who have been sidelined by short-sale constraints. High-risk firms have greater scope for overconfidence and disagreement, so we expect this source of overpricing to be greatest for high-risk firms. In these ways, overconfidence provides a natural explanation for the idiosyncratic volatility and betting-against-beta effects” (high-beta stocks underperform low-beta stocks).
They also show how overconfidence can explain the accrual anomaly, in which stocks with high accruals tend to underperform stocks with low accruals. The authors note the well-documented tendency of people to be overconfident about fast heuristic judgments, which signals them that they don’t need to dig deeper and pay attention to details such as accruals.
Daniel and Hirshleifer conclude that “1) there are anomalies in financial markets—unprofitable active trading, and patterns of return predictability—that are puzzling from the perspective of traditional purely rational models; and 2) models of overconfidence, and of the dynamic psychological processes that underlie overconfidence, can plausibly explain why these patterns exist and persist…. Overconfidence provides a natural explanation for why investors who process the same public information end up disagreeing so much.”
As legendary comic strip character Pogo said: “We have met the enemy, and he is us.”
This commentary originally appeared May 18 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.
© 2016, The BAM ALLIANCE