We now turn to the LP’s factor exposure. The funds we use to build the LP create an end portfolio with loadings on (or exposure to) the size and value factors of approximately 0.6. However, the exact amounts depend on which funds are used to implement the strategy because different funds in the same asset class (in this case small value) can have different exposures to the size and value factors. The smaller the weighted average market capitalization of the stocks in the fund, and the lower their weighted average price-to-book ratio, the greater the exposure to the factors will be. Like most well-diversified stock portfolios, its equity portion has a market beta of about 1.
Now consider a portfolio that uses the LP’s high-tilt, low-market-beta approach and has a 30 percent allocation to stocks. The portfolio will have a market beta of about 0.3 (1 x 0.3), a size loading of about 0.18 (0.6 x 0.3) and a value loading of about 0.18 (0.6 x 0.3). The portfolio’s bond holdings will also give it exposure to term risk, another factor. How much will depend on the maturity of the bonds used for the portfolio’s fixed income portion. The portfolio therefore has exposure to four factors, each of which has a low to negative correlation with the other factors. Contrast that with a TSM portfolio fully allocated to stocks. It has a market beta of 1, and that is the only factor to which it is exposed.
Thus, while a TSM fund is more diversified when you think about diversification across asset classes (it holds more equity asset classes/fills in more of Morningstar’s style boxes), the LP is more diversified when looking at exposure to risk factors. A TSM fund has all of its eggs in one risk basket—market beta—while the LP diversifies its risks across three stock risk baskets: market beta, size and value, as well as the term factor in its bond holdings. The LP is also just as diversified in terms of economic and geopolitical risks across countries. And it certainly holds a sufficient number of stocks. Using international small-cap value and emerging market value funds from Dimensional Fund Advisors and Bridgeway’s Omni Small Value Fund, the LP holds the stocks of about 5,100 companies from 42 countries—certainly more than enough to diversify away any idiosyncratic risks. In fact, it contains not that many fewer stocks than Vanguard’s Total World Stock Index Fund, which holds about 7,800 stocks also from 42 countries.
The bottom line is that the LP is well-diversified, just not so much when it’s thought about in terms of a traditional asset class approach. And while this leaves the investor subject to that dreaded psychological disease known as tracking error regret—the portfolio’s returns will look very different from those of the market—the benefits in terms of reduced tail risk are large in comparison.
Support for Factor Diversification
Louis Scott and Stefano Cavaglia, authors of the study “A Wealth Management Perspective on Factor Premia and the Value of Downside Protection,” published in the Spring 2017 issue of The Journal of Portfolio Management, provide support for the benefits of factor diversification. The focus of their study, which examined four factors (the Fama-French size and value factors as well as the two newer momentum and quality factors), was to determine if factor diversification improved terminal wealth and the odds of retirees in the withdrawal phase of their investment cycle not outliving their portfolios.
To test their hypothesis, Scott and Cavaglia considered a baseline investment strategy comprising a passive, fully invested exposure to global equities (the MSCI World Index) over a 20-year horizon. They then examined the effect of adding an overlay of factor premiums on the distribution of terminal wealth. They used utility functions to quantify the hedging benefits of factor premiums to the baseline investment strategy. Their dataset covers the period from November 1990 through December 2012.
Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short time. In a 1997 study, Mark Carhart was the first to use momentum, together with the Fama-French market beta, size and value factors, to explain mutual fund returns. Initial research on momentum was published in 1993.
High-quality companies have the following traits: low earnings volatility, high margins, high asset turnover (indicating the efficient use of assets), low financial leverage, low operating leverage (indicating a strong balance sheet and low macroeconomic risk), and low stock-specific risk (volatility that is unexplained by macroeconomic activity). The quality factor (QMJ) was introduced in a 2013 study.
The authors used a bootstrapping technique (rather than a Monte Carlo simulation) to simulate returns in a way that preserved the autocorrelation observed in markets. The bootstrap simulations (random sampling from the actual empirical distribution) resulted in alternative histories for the market and the four factor premiums. They then used these histories to generate terminal wealth distributions from investing $1 across alternative investment strategies. The alternative investment strategies they considered were an investment in the global equity market, an investment in the global market complemented by an overlay in a risk premium (each factor considered independently), and an investment in the market complemented by an overlay of an equal-weighted (1/N) allocation to each factor premium. In the single-factor cases, the overlay is $1 invested in the long side of the premium and $1 invested in the short side. In the case including all four factors, each factor has $0.25 invested in the long side and $0.25 invested in the short side. The portfolios were rebalanced monthly.
The following table shows the terminal wealth at various percentiles of performance. For example, while $1 invested in the global market grows to a median value of $4.17 after 20 years, the fifth percentile of terminal wealth shows a value of $1.06, the first percentile shows a loss of 44 percent, and the top percentile (the 99th) shows an increase of more than twentyfold.
Note that with the sole exception of the first percentile of the portfolio that includes the global market plus the size factor overlay, the outcomes are improved over just the global market portfolio. That particular outcome is due to the procyclical nature of the size factor. However, results are quite different when we look at the portfolio with the quality factor overlay. This should not be surprising because the quality factor tends to outperform in negative market environments. With that said, the downside protection did not come with an offsetting reduction in terminal wealth at any percentile. In all cases, relative to the global market portfolio, the 1/N diversified portfolio containing all four factors produced dramatically superior results, enhancing both downside protection and terminal wealth in good environments.
What if Factor Premiums Decline?
Given that research has shown factor premiums tend, on average, to shrink by about one-third post-publication, Scott and Cavaglia next considered what would happen if the factor premiums shrunk to half their historical levels. As the following table shows, the portfolio of factor premiums continues to mitigate most of the unfortunate tail (the lower 5 percent of cases) in which the investor’s terminal wealth is lower than at the starting point while simultaneously improving terminal wealth in almost all other cases. The 1/N overlay portfolio has higher terminal wealth in all percentiles, and avoids a loss even at the first percentile.
Scott and Cavaglia also performed an interesting test. They compared the performance of a portfolio fully invested in global equities and managed by an investor with market-timing skill set at 10 percent (meaning the investor could accurately forecast 10 percent of bear markets, a high hurdle given the lack of evidence supporting the view that bear markets can be forecasted) with the performance of a strategy fully invested in global equities and with an overlay of equally weighted factor premiums. They found that the distribution of terminal wealth across all percentiles is greater for the factor premiums strategy than for the skill-based strategy. In other words, the factor premiums strategy dominates the skill-based one, creating a very high hurdle for active management in terms of the ability to time markets.
Does Factor Diversification Make the Road Less Bumpy?
In addition, Scot
t and Cavaglia tested to see if the factor portfolio allowed investors to “sleep better,” perhaps improving their ability to stay disciplined and avoid panicked selling. They noted that the median value of the drawdowns for a strategy fully invested in the global market was 0.43 (a loss of 43 percent), suggesting that investors will be exposed to at least one sizable and very nasty event on their journey toward achieving their retirement goals. The authors found that the overlay portfolio can smooth the ride, providing smaller drawdowns at every percentile, even with the 50 percent haircut to the premiums applied.
Scott and Cavaglia also considered the utility of downside protection. The research shows that investors are, on average, risk-averse. Therefore, they are willing to “buy insurance” (that is, to accept lower expected returns) to protect themselves against downside losses. Using utility functions, along with varying degrees of risk aversion, they found that in all cases the value of downside protection offered by the factor overlay portfolio (benchmarked against the global market portfolio’s profit and loss) is economically large and significant, emphasizing the factor overlay portfolio’s protection against individuals’ aversion to losses.
The authors showed that the distribution of terminal wealth of a global market portfolio strategy can be significantly enhanced via an overlay that allocates capital equally across the four premiums they studied. In particular, the factor exposures help mitigate downside risk. Importantly, their simulations demonstrated that, even if the average premiums were halved, their drawdown mitigation properties would still be preserved. Finally, they showed that active asset allocation strategies require significant market-timing skill to outperform a passive factor-premium-based overlay strategy.
In summary, the “secret sauce” that produced more efficient portfolios with less tail risk was the addition of unique sources of risk (factors) that carry premiums whose returns have low to negative correlation with traditional stock and bond portfolios. These same concepts can be applied to alternative investments.
As you will recall from our recurring illustration, when shown the two bell curves representing the distribution of potential returns for Portfolios A and B, investors prefer Portfolio B with its narrower distribution. In other words, they prefer the one with more of the weight of the distribution closer to the mean (the expected return). Adding exposure to the size and value factors while reducing exposure to market beta enabled us to develop a portfolio in which the distribution of returns was more like Portfolio B. But what if you could create a portfolio with an even more favorable distribution of returns? Perhaps one whose distribution of returns looks more like Portfolio C as depicted in the following graph?
In Part II, we discuss five alternative investments that further shift the potential distribution of returns in a favorable way. The five alternatives are alternative lending, reinsurance, the variance risk premium, AQR Capital Management’s Style Premia Alternative Fund and AQR Capital Management’s Managed Futures Fund. While the addition of each individual alternative would improve the efficiency of a portfolio, combining them further enhances efficiency because, in each case, the correlation of their returns to each other, as well as to the other assets in the portfolio, is low. The result is like Portfolio C, whose distribution of returns is even more favorable than that of Portfolio B.
1 Past performance is not a guarantee of future results.
Part II:
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Alternative Investments
Chapter 5:
Alternative Lending
Over the past several years, we have witnessed a fundamental shift in the fixed income landscape. Traditionally, banks have been central to the creation of credit, driven by their ability to take in low-cost deposits and loan out money at higher rates. While non-bank loan channels have always existed parallel to traditional banking, historically these channels were small niches in the overall economy. However, a new breed of lender has emerged to become a significant presence in the market. Initially, they were known as “peer-to-peer lenders” or “marketplace lenders.”
The first was Zopa, a U.K.-based platform founded in 2004. Zopa matched consumers who wanted to borrow money directly with individuals who wanted to lend money. It was soon followed by many others, focused across a wide variety of geographies and borrower types. Growth in the space hit an inflection point after the 2008-2009 global financial crisis, driven by a severe contraction in bank lending, an acceleration of online financial services, and an increasing mistrust of, and dislike for, traditional banks.
Today, these technology-based lending platforms, such as Lending Club (consumer loans), Square (small business loans) and SoFi (student loans) are broadly recognized as “alternative lenders.” What’s more, they are disrupting lending markets and have taken significant market share from traditional banks.
Structural Cost Advantage
Because alternative lenders generally are not burdened with the substantial infrastructure costs of traditional banks (they don’t have physical branches) or the same level of regulatory oversight (banks are typically regulated by the full spectrum of state bank examiners, the FDIC, the SEC, the Federal Reserve and consumer credit agencies), they are able to extend loans at significantly lower rates. It is also important to note that, while interest rates have fallen dramatically since 2008, the average revolving credit card rate actually has risen. Alternative lenders have been able to leverage their superior operating efficiency to offer more attractive pricing to consumer and small business borrowers while also delivering a seemingly superior service experience.
The increasing cost structure at banks in the post-Dodd-Frank Act era (after 2010) makes it increasingly uneconomic to originate smaller business loans. Even though, following the financial crisis, U.S. banks significantly expanded their portfolio of business loans of over $1 million, at the same time they have pulled away from making smaller loans. With few viable alternatives, many small business owners have resorted to borrowing on credit cards, taking on debt that often has a punitively high, variable rate. For instance, The Wall Street Journal reported in November 2015 that, at one of the largest U.S. banks, small-business credit cards accounted for more than 90 percent of lending to businesses with less than $1 million in revenue. As a result, alternative lending platforms have been steadily taking market share by catering to this underserved segment and cost-effectively originating smaller loans.
The biggest impact has been on small banks and, thus, on small businesses, because small banks make the vast majority of small business loans. For example, the number of banks with less than $100 million in assets declined by 85 percent from 1985 to 2013. And the trend continues unabated. Not only do alternative lenders have a cost structure advantage, but, as mentioned previously, their technology enables them to provide arguably better service, including faster turnaround times.
It is important to note the difference between consumer loans, which are often uncollateralized, and small business loans, which typically are secured either by business assets, the business owner personally, or both.
Worldwide Phenomenon
Alternative lending is not just a U.S. phenomenon. There now are hundreds of alternative lending platforms around the world. In the United States alone, alternative lenders originated an estimated $30 billion in loans in 2016, and are expected to generate $150 billion in loans by 2020. The opportunity is enormous, as those figures remain just a small fraction of the nearly $900 billion in revolving U.S. consumer credits now outstanding. In addition, the market for small business loans in the United States is about $300 billion.
Student loans present another area of opportunity for alternative lenders, with the U.S. market totaling about $1.4 trillion. Student loans historically have been “one-size-fits-all.” The result is that high-credit-quality borrowers pay the same rate as low-credit-quality borrowers. Alternative lending platforms can target borrowing students with high credit ratings (thus lowering expected losses from defaults), providing meaningful
cost savings.
Furthermore, just as U.S. prime consumer borrowers frequently pay very high rates on revolving credit loans, borrowers in other parts of the developed world also often pay interest of more than 20 percent for bank credit. That has fueled the global expansion of alternative lending in the consumer market.
Sources of Demand: Consumer Loans
Though each alternative lending platform has a slightly different niche in the market, consumers often view these loans as an alternative to credit card debt. Credit cards can carry high interest rates, and the average cost of credit card debt has risen in recent years even as interest rates in the broader economy generally have fallen. Consumers who take loans from platforms like Lending Club and SoFi are often attracted to lower interest rates, at least relative to credit cards, as well as their reputation for enhanced customer service. Also, unlike credit card debt, loans originated by alternative lending platforms generally are fixed rate and fully amortizing.
Sources of Demand: Business Loans
Alternative lenders are filling a gap left by traditional banks as they have, in many cases, pulled away from small businesses term loans. According to the same November 2015 Wall Street Journal article, it costs one large U.S. bank roughly the same to originate a $100,000 small business loan as it did for it to originate a loan of $1 million. Small business credit cards cost the bank a lot less to issue. But credit cards are a relatively expensive way for businesses to finance growth. Alternative lenders have figured out how to originate smaller-sized loans to small businesses in an operationally efficient way.
Reducing the Risk of Black Swans Page 5