Low-volatility strategies have quickly become the darling of many investors, thanks largely to trauma caused by the bear market that arose from the 2008-2009 financial crisis combined with academic research showing that the low-volatility anomaly exists in equity markets around the globe.
Earlier this week, we took a detailed look at a 2016 study from David Blitz, “The Value of Low Volatility,” which explored whether low volatility was a unique investment factor or if its performance could be explained by other well-known factors (specifically, value). Today we’ll review some additional research on this issue.
A Deeper Dive Into Low Volatility
Ronnie Shah, author of the 2011 study “Understanding Low Volatility Strategies: Minimum Variance,” found that for the period 1963 through June 2010, the low-beta strategy had exposure to term risk. Its “loading factor” (degree of exposure) on term risk was a statistically significant 0.09 (with a t-stat of 2.6). As further evidence, Tzee-man Chow, Jason Hsu, Li-lan Kuo and Feifei Li, authors of “A Study of Low-Volatility Portfolio Construction Methods,” which appears in the Summer 2014 issue of The Journal of Portfolio Management, found a correlation of 0.2 between the betting-against-beta factor and the duration factor.
Given their positive exposure to term risk, low-volatility stocks have benefited from the cyclical bull market in bonds we have experienced since 1982. That rally can’t be repeated now, with interest rates at historic lows. In addition, the low-volatility factor may not be as unique as Blitz found.
Robert Novy-Marx has also examined the low-volatility factor. His 2016 study, “Understanding Defensive Equity,” covered the period 1968 through 2015. Novy-Marx found that when ranking stocks by quintiles of either volatility or beta, the highest-quintile stocks dramatically underperform, while the performance of the other four quintiles are very similar and marketlike.
In fact, the second-highest-volatility quintile (the fourth quintile) posted the highest returns, followed by the third, second and, finally, the first quintile. This nonlinear relationship is quite different from what we typically find with other common factors, where the returns across deciles, quintiles or quartiles tend to be linear.
Novy-Marx also found that high-volatility and high-beta stocks tilt strongly to small, unprofitable and growth firms. These tilts can explain the poor absolute performance of the most aggressive stocks; stocks that are often referred to as “jackpots” or “lottery tickets.” These stocks make up a very small percentage of total market capitalization. But it is the underperformance of these high-risk (small, unprofitable and growth) stocks that drives the abnormal performance of defensive equity. Novy-Marx also found that a stock’s profitability is a significant negative predictor of its volatility, and it is the single most significant predictor of low volatility.
Adding In Profitability
Novy-Marx found that by including profitability as a factor, the performance of the defensive (low-volatility) strategy is well explained by controlling for the common factors of size, profitability and relative valuations. Novy-Marx also found that defensive strategies tilt strongly toward large stocks (they are 30 times as large at the end of his sample, and the long-short portfolio has a size factor loading of -1.12), value stocks (the long-short portfolio has a value loading of 0.42) and profitable stocks.
The profitability tilt obscures the extent to which defensive strategies tilt toward value, because value and profitability tend to be strongly negatively correlated. Unless you control for profitability, the value loadings of defensive strategies will be lowered (an important insight).
Novy-Marx also found that five-sixths of the Fama-French three-factor alpha (57 out of 68 basis points per month) was delivered through the aggressive stocks on the short side of the strategy with only one-sixth, or 12 basis points per month, coming from the actual defensive stocks. And he found similar results when looking at a low-beta strategy.
A second important consideration is that, while the low-volatility factor may well be somewhat unique, and in the past it has provided a premium, the dramatic inflows into the strategy have altered the very nature of the strategy’s valuation characteristics.
Have Low-Volatility Strategies Become Overgrazed?
As is the case with so many well-known anomalies and factors, the problem of potential overgrazing does exist. Findings regarding the premium, combined with the bear market caused by the financial crisis of 2008, led to the aforementioned dramatic increase in the popularity of low-volatility strategies.
The cash inflows have raised the valuations of defensive (low-volatility/low-beta) stocks, reducing their exposure to the value premium and thus lowering expected returns. Specifically, as low-volatility stocks are bid up in price, low-volatility portfolios become more “growthy” (which reduces their forward-looking returns).
Specifically, we’ll take a look at the valuation metrics of the two largest low-volatility ETFs, the iShares Edge MSCI USA Minimum Volatility ETF (USMV), with $15.1 billion in AUM; and the PowerShares S&P 500 Low Volatility Portfolio (SPLV), with $7.9 billion in AUM. We will then compare their value metrics to those of the iShares Russell 1000 ETF (IWB), which is a market-oriented fund, and the iShares Russell 1000 Value ETF (IWD).
The table here is based on Morningstar data as of July 7, 2016.
What is clear from the data is that the demand for these strategies has altered their nature. The valuation metrics of USMV and SPLV certainly don’t look like a value-oriented fund. Their price-to-earnings, book-to-market, price-to-sales and price-to-cash flow ratios are all quite a bit higher than those of IWD. In fact, their metrics indicate that both are now more “growthy” than the marketlike IWB. What’s more, the price-to-earnings ratios of both USMV and SPLV were even higher than the iShares Russell 1000 Growth ETF’s (IWF) ratio of 20.7.
Another Look At Exposure To Value Factor
We can also see how the increased popularity of low-volatility strategies has changed their very nature by looking at how the loading factors have shifted over time. Using the tool provided by Portfolio Visualizer, we’ll take a look at the results of regression analysis on the largest ETF, USMV.
The first full month since the inception date of this ETF was November 2011. Data is available for the fund through April 2016. We’ll split the period into two equal parts, November 2011 through January 2014; and February 2014 through April 2016. The regressions include the Fama-French factors of beta, size, value and momentum, and the two bond factors of term and default. In the first half of the period, USMV had a loading on the value factor of 0.21. For the second half of the period, the value loading was -0.04. In other words, USMV moved from loading positively on the value factor to now having a slight loading on growth.
Results from the regression analysis confirm what a simple look at the valuation metrics told us. In addition, the regressions show that the fund has statistically significant exposures to the term premium. The loading on the term premium in the first half of the period was 0.29 and in the second half it was 0.25. At the very least, with interest rates at historical lows, investors should be aware of this exposure to term risk.
There’s a cliché in finance that success can sow the seeds of its own destruction. The flow of cash into the low-volatility strategy has changed the very nature of the funds. While they may still be low volatility, they no longer look like value funds. The lower exposure to the value premium means that they now have lower expected returns.
In other words, since there is an ex-ante value premium, what low volatility is predicting at this point in time is not higher returns, just low future volatility. In addition, it doesn’t seem likely that low-volatility strategies will benefit as much in the future as they have in the past from their exposure to term risk.
The bottom line is that the evidence suggests you would be better served by investing in vehicles that screen out the high-volatility (or high-beta), high-risk stocks. In other words, invest directly in size, value and profitability rather than doing so in the indirect way characteristic of defensive strategies.
This commentary originally appeared August 10 on ETF.com
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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
Among the most important decisions investors make is their choice of location for assets within the various alternatives available for retirement (tax-advantaged) accounts. Allocating between a traditional IRA (a pretax, tax-deferred account) and a Roth IRA (a post-tax, tax-free account) can have a pronounced impact on retirement outcomes, given the $14 trillion in tax-advantaged retirement account assets at the end of 2015.
David Brown, Scott Cederburg and Michael O’Doherty contribute to the literature on retirement asset location with their June 2016 paper, “Tax Uncertainty and Retirement Savings Diversification.”
The modeling approach they adopt accounted for investor age, current income and taxable income from outside sources in retirement, as well as the highly progressive income tax regime now in place. The authors point out that “the marginal rate for a single taxpayer with inflation-adjusted income of $100,000, for example, has changed 39 times since the introduction of income taxes in 1913 and has ranged from 1% to 43%.” This creates considerable uncertainty.
Because risk-averse investors (and most investors are risk averse; it’s generally only a matter of degree) dislike uncertainty, this should create a preference for Roth accounts, as they “lock in” the current rate, eliminating the uncertainty associated with future changes.
On the other hand, a traditional account, which offers retirement savers the benefit of deducting current contributions, allows investors to “manage their current taxable income around tax-bracket cutoffs, which is valuable under a progressive structure.”
Another benefit of traditional accounts, the authors write, is that “the progressive tax rates faced in retirement provide a natural hedge against investment performance. Investors with poor investment results and little wealth in retirement will pay a relatively low marginal tax rate, whereas larger tax burdens are borne by investors who become wealthy as a result of good investment performance.” This creates tension between the traditional and Roth options.
Who Should Use The Roth Structure?
The authors state: “Roth accounts are primarily useful for low-income investors who can lock in a low marginal rate by paying taxes in the current period.” They add that because “future tax rates are more uncertain over longer retirement horizons” and their analysis of historical tax changes suggests “that the rates associated with higher incomes are more variable,” eliminating “exposure to tax risk is particularly attractive for younger investors with relatively high incomes and correspondingly high savings.”
The authors continue: “Despite high current marginal tax rates, and contrary to conventional financial advice, these investors benefit the most from the tax-strategy diversification offered by Roth accounts.”
Brown, Cederburg and O’Doherty concluded: “Whereas conventional wisdom largely supports choosing between traditional and Roth accounts by comparing current tax rates to expected future tax rates, the hedging benefits of traditional accounts and the usefulness of Roth accounts in managing tax-schedule uncertainty are important considerations in the optimal savings decision.” They note that, for wealthy investors, their analysis shows “tax-strategy diversification is particularly attractive, despite their high current marginal tax rates.”
The authors also examined their findings’ economic implications: “Our results are of practical importance to employers and regulators who determine the retirement savings options available to employees. In particular, broadening access to Roth versions of workplace accounts would provide investors with important tools for managing their exposures to tax risk. Given that these accounts are available under current regulations, encouraging the widespread adoption of, and education about, employer-sponsored Roth plans could substantially improve investors’ welfare.”
What the authors found provides investors with the proper framework to make informed decisions regarding the asset location of their retirement savings and the diversification of tax risk.
This commentary originally appeared July 27 on ETF.com
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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
As someone who has long made a living as a financial advisor, I have an inherent bias toward retaining one. I even have one myself, because I believe personal finance is more personal than it is finance.
However, paradoxically, I fear that the vast majority of those who retain the services of a financial advisor experience little to no benefit from the relationship. They may even see deterioration in their financial security as a result of the engagement.
To put yourself (hopefully) among the minority of investors who experience great benefits from working with a financial advisor, consider the following framework for discerning the optimal co-pilot: firm ethos, relational fit and investment/planning strategy.
Firm Ethos:
The ethos or grounding philosophy of a financial advisory firm—how they’re compensated, how they’re regulated and whether they have a record of disciplinary action—says a great deal about the values and priorities of the environment in which your financial advisor operates.
Compensation and regulatory oversight are largely connected. Commission-only firms receive compensation solely from the sale of financial products and are typically regulated by FINRA and/or your state’s insurance commissioner. Making a living based primarily on commissions doesn’t make someone a bad person, but it does make them a salesperson.
Financial salespeople are held to a lesser regulatory standard than “financial advisers” regulated by the SEC, who must uphold a fiduciary standard of care requiring them to put your interests ahead of theirs. “Fee-only” advisors receive compensation directly from their clients and must be fiduciaries at all times. “Fee-based” advisors may receive commissions and act as part-time fiduciaries.
While no compensation method is perfect or conflict-free, consider limiting your search solely to advisors who are fee-only, full-time fiduciaries. Be sure to review your prospective firm and individual advisor’s disciplinary record on the FINRA and SEC websites to ensure they’re clean.
Relational Fit:
Relational fit likely will require careful contemplation on your part. The best financial advisory relationships are long-term, so you want to be sure that you connect with both your advisor and their firm on a human level.
This will largely be driven by your “gut feeling,” but look especially for someone who seems more concerned with you, your values and your goals than their own. Look for someone who listens twice as much as they talk. If you don’t trust the person you consider your advisor, you’ll likely not follow their recommendations and stick with the plan you co-create.
Investment/Planning Strategy:
It’s been said that there are no bad investment or insurance products—just bad uses for them. This statement is utter hogwash, surely penned by a salesperson. There are plenty of crappy products out there and, similarly, there is an abundance of poor advice.
First, ensure that your advisor employs a strategy that’s well-supported by their firm, because no one can do this alone (well). Regarding investments, I recommend an evidence-based strategy that holds up to academic rigor, not the latest buy/sell/hold Wall Street opinion. While complexity will underlie any cohesive investment strategy, it should be distilled to an elegant simplicity you understand well enough to teach to a fifth-grader.
Investments (or insurance) are merely elements of a holistic financial plan. Consider, therefore, working with someone knowledgeable in the broad discipline of financial planning, including tax, estate, education and retirement planning.
You could compromise in the ethos, fit or strategy categories, but why settle for anything less than optimal?
This commentary originally appeared Aug. 1 on Forbes.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