June 2016
Robert J. Schoen
Co-head of Global Asset Allocation
Adrian H. Chan, CFA
Portfolio Manager, Global Asset Allocation
While the U.S. stock market has recovered in value since the 2008 global financial crisis and gone on to reach new all-time highs, equity investors have yet to fully recover psychologically from the damaging losses they incurred.
When the market was at its lows, many investors panicked and retreated to cash and fixed-income investments and, as a result, did not participate fully in the recovery. With the trauma of 2008 still on investors’ minds, and with fresh experiences of volatility in 2015 and 2016, many are looking for safer equity alternatives than traditional equity benchmarks. Investors want solutions that can pursue the equity risk premium, but with lower volatility and limited downside risk.
Accordingly, investors have become increasingly interested in low-volatility equity investment approaches, which typically involve a low beta stock selection strategy. This type of portfolio has the potential to satisfy the broad-based desire for a “better” way to invest in equities. However, there are risks and limitations in using low beta equity. In this piece, we offer ideas for a better approach.
For use with institutional investors and investment professionals.

June 2016 | Better solutions for low-volatility equity investing
A cornerstone of traditional finance theory is the idea that assets with higher non-diversifiable risk will be rewarded with higher returns. However, many decades of empirical evidence suggest that this is simply untrue. Within the
U.S. market, stocks with higher betas have not had higher returns than stocks with lower betas.
According to our study, lower beta stocks have actually had higher returns in many long historical periods. Low beta stocks have also consistently had lower volatilities.
Consequently, if we merely assume that the expected return of low beta stocks is the same as that of high beta stocks, then the risk-adjusted return of low beta stocks must be superior to that of high beta stocks.
The causes for the anomaly can be explained as a preference among investors for higher beta stocks because they have seemingly desirable characteristics like glamorous growth prospects and lottery-like payoffs. Another explanation is that high beta stocks are preferred because they can act as surrogates for leverage. Investors who are unable or unwilling to use leverage may be drawn to high beta stocks because they should outperform in rising markets, much like a levered equity investment would.
The beta anomaly results in a mispricing of securities, with lower-than-warranted valuations for low beta stocks. We expect this mispricing to persist because most investment managers are generally unable to exploit this anomaly due to their focus on outperforming capitalization-weighted benchmarks and their aversion to employing leverage. Buying stocks with higher expected risk-adjusted returns does not help managers outperform their benchmarks, and they generally do not use leverage to get higher absolute returns out of lower beta stocks.
Long-term performance data show that low beta stocks do not have lower returns than high beta stocks
Thanks to their low volatility, low beta stocks have had the best risk-adjusted returns
12% 0.5
10%
0.4
8%
0.3
6%
0.2
4%
2%
0.1
0%
Low beta Mid beta High beta
Geometric returns of cap-weighted beta terciles, U.S. large-cap stocks, 1927–2015.
Prior to 1983: betas calculated on trailing one year of daily data and returns from CRSP;
1983–present: betas from Axioma US3MH risk model and returns from IDC.
Sources: CRSP, IDC, Axioma.
0.0
Low beta Mid beta High beta
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Some investment managers attempt to take advantage of the beta anomaly by creating low beta portfolios.
However, it is important to note that if a portfolio is created simply by owning the lowest beta stocks, then the portfolio will tilt strongly toward lower beta sectors.
1 For example, the Power Shares S&P 500 Low
Volatility Portfolio ETF (as of March 31, 2016) has over
60% of its allocation to the financials, consumer staples, and industrials sectors; by comparison, these sectors represent only 36% of the S&P 500 Index. Technology comprises nearly 21% of the S&P 500 but only has a 2.9% weight in the Low Volatility ETF.
Importantly, the sectors with the lowest beta also tend to be the most interest-rate-sensitive sectors, which means low beta stocks may introduce significant duration risk to a portfolio. The consequences of this were apparent when interest rates spiked higher during the so-called
“Taper Tantrum” in the summer of 2013. The lower beta sectors all underperformed significantly and most low beta stock selection strategies struggled along with them.
In addition, it is worth noting that backtests of low beta strategies over the past 30 years have been inflated to some extent by the benefits of the bond bull market that began in 1982. If investors are concerned that bond yields may go significantly higher from the current historically low bond yields, then they should be concerned about the duration risk added from the sector tilts in a naive low beta strategy.
Our research has shown that an inverse relationship between beta and Sharpe ratio is present within every sector, as in the following illustration, suggesting that investors do not need to take on sector risk in order to capitalize on the beta anomaly. We believe a low beta portfolio that has the same sector weight as a market portfolio, and that is tilted toward low beta stocks in each sector, can eliminate much of the duration risk associated with low beta strategies.
1 Another portfolio construction method is to build a minimum variance portfolio. Putnam research suggests that the attractiveness of minimum variance portfolios comes from their tilt toward lower beta stocks, so we believe that the present analysis of low beta portfolios also applies to minimum variance portfolios.
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June 2016 | Better solutions for low-volatility equity investing
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Energy Materials Industrials Discretionary Staples Health care Financials
Sharpe ratios of cap-weighted beta terciles within each sector, U.S. large-cap stocks, 1927–2012.
Betas calculated on trailing one year of daily data. Sector classification mapped from SIC codes.
Sources: CRSP, Ibbotson.
Technology
Low beta
Mid beta
High beta
Telecom Utilities
Another aspect of concern for low beta investing is the nature of the downside risk protection that it offers. Low beta portfolios are expected to go down less in negative markets, but not necessarily less than a blended portfolio comprising the market and cash, with an equivalent beta. For example, in 2008, the S&P 500 was down
-37%. A naive low beta portfolio constructed with the bottom beta tercile of U.S. large-cap stocks, weighted by capitalization, would have had a more modest loss, only
-25%, and would have had a 3-year trailing beta of 0.73.
A portfolio composed of weightings of 73% in the S&P and 27% in cash, which also has a 0.73 beta, would have returned -26.5%, only slightly worse than the low beta portfolio.
Managers who seek to provide a better way for investors to capture the equity risk premium might consider an approach that targets higher risk-adjusted returns and improved downside risk. For a strategy to offer genuine downside protection, it has to improve the shape of the stock return distribution so that the treacherous left tail of the distribution, where the large negative events are found, becomes less menacing. Low beta stocks do not accomplish this; in fact, historical data suggest that low beta portfolios have a more negative skew than high beta portfolios. We understand that one reason to invest in traditional low beta strategies is to pursue better riskadjusted performance. But it is important to understand that they do not provide downside risk protection.
Investors may want to consider an opportunity to achieve better downside risk protection for a low beta portfolio by adding options strategies. The purpose is to seek enhanced risk-adjusted return and also reshape the distribution of equity returns, to help provide genuine downside risk protection.
Investing in lower beta stocks can be effective strategy for reducing the volatility and improving the Sharpe ratio of an equity portfolio. However, in very turbulent markets, we think it is important to have true downside risk protection in the form of long index puts. Long put option positions reshape the distribution of equity returns, cutting off the left tail and putting a hard limit on losses that can occur in the portfolio.
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While the appeal of having downside risk protection is obvious, investors generally shun such protection because insurance can be expensive. Our research shows that, in the long run, owning puts in a portfolio lowered expected return. However, investors may want to focus on riskadjusted return. The math of Sharpe ratios says that if you can reduce the portfolio volatility by more on a percentage basis than you have reduced the expected return, the
Sharpe ratio actually goes up. Long puts can be effective at reducing the volatility of an equity portfolio because they have very negative correlations with equity returns. Our research has shown that the best value in long puts can be found in longer term puts, such as those with 12-month expiration terms, with deltas around -0.25.
In light of the long run costs that can be a part of the put-buying strategy, index call writing can be a complementary strategy that seeks to provide long run income as well as volatility management and Sharpe ratio enhancement. Call writing is a cashless strategy that has both a positive expected return and a negative correlation to equities. Adding such a strategy can be attractive because the expected return of the overall portfolio becomes higher while the volatility becomes lower due to the diversification.
A hypothetical 1-month put strategy (1995–2015) reduced S&P 500 returns and losses
15%
10%
5%
-10%
-15%
0%
-5%
Trend line
Put strategy reduces losses
0%
Put strategy reduces returns
-5%
-10%
-15%
15%
10%
5%
-20%
-20% -15% -10% -5% 0%
S&P 500 return
5% 10% 15% -20% -15% -10% -5% 0%
S&P 500 return
5%
-20%
10% 15%
Sources: Bloomberg, Credit Suisse LOCUS, Putnam Investments, S&P.
The illustration assumes a portfolio that is long stocks and buys 12-month, 25-delta puts. The Black-Scholes model is used to calculate the theoretical price of the put options; option prices were derived by applying the Black-Scholes model to implied volatility surface data provided by Credit Suisse. The put strategy assumes 12-month 25-delta S&P 500 puts were purchased each month and held until expiration. Puts were staggered each month so that one twelfth of the puts expire each month. Sufficient options data prior to 1995 was not available. In the backtest, low beta portfolios are rebalanced monthly, investing only in the stocks that are in the bottom third of the Russell 1000 Index by predicted beta. These stocks are then weighted using pro-rated benchmark weights.
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June 2016 | Better solutions for low-volatility equity investing
1-month volatility risk premium was greater than realized volatility by an average of 4%
30%
VIX — Forward realized volatility spread
Average
20%
10%
0%
-10%
-20%
-30%
9/30/94 Dec ’96 Dec ’98 Dec ’00 Dec ’02 Dec ’04 Dec ’06 Dec ’08 Dec ’10 Dec ’12 Dec ’14 9/30/15
Sources: Bloomberg, Putnam Investments.
The CBOE Volatility Index (VIX) is a key measure of market expectations of near-term volatility conveyed by S&P 500 stock index option prices.
The index is an up-to-the-minute market estimate of implied (expected) volatility that is calculated by using the midpoint of real-time S&P 500 Index option bid/ask quotes.
VIX — Forward realized volatility spread represents the difference between the value of the VIX and realized volatility of 1-month S&P 500 Index call options.
Average represents the average difference between the value of the VIX and realized volatility of 1-month S&P 500 Index call options over the entire time period.
In our study, we analyzed systematically selling of onemonth out-of-the-money index calls with deltas that are typically between 0.15 and 0.25. This strategy is based on academic research investigating the volatility risk premium, which describes the fact that implied volatilities are generally higher than realized volatilities. Our research suggests that short-term (one-month) out-of-the-money index calls are overvalued and that the volatility risk premium can be captured by shorting these options.
For example, from 1995 to 2015, a hypothetical strategy that shorted one-month S&P 500 calls with 20-delta would have had an IR of about 0.43 before transaction costs as well as a correlation of about -0.40 to the S&P
500. Because we use index calls and not options on the individual stocks in the portfolio, in theory there is some risk that both the options and the equity portfolio could lose money at the same time. In reality, however, this risk is minimal due to the high correlation of the sectorneutral equity portfolio and the benchmark indexes.
For example, in the U.S. equity portfolio the correlation between the equity portfolio (without options) and the
S&P 500 is nearly 0.99.
Timing risk (also known as strike risk) is the notion that a systematic option strategy can vary depending upon the specific timing of rebalances. This is because different schedules lead to different option strikes. For example, a
12-month put strategy that is rebalanced every December could behave very differently from one that is rebalanced every June, depending on when market peaks and troughs occur. To reduce these risks, investors should diversify both the put and call strategies with a staggered strike approach.
In our study, we chose to examine a call option strategy that could overcome a weakness identified in empirical research on monthly options. This research shows that a typical monthly call overwriting strategy that rebalances at traditional option expirations on the third
Friday of each month structurally underperforms other call over-writing strategies with different rebalancing endpoints. The approach we considered would avoid this structural underperformance. Instead, it involves selling a combination of 4-week call options weekly and selling monthly options every month-end.
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At any given point in time, this call strategy holds five options in varying weights — four weekly call options and one month-end call option — requiring five rebalancing trades in a typical month. For the weekly options, one of the four call options expires and is replaced by a new
4-week call option on the same amount of notional principal. Interspersed with this weekly rebalancing, at the end of each month the month-end call option expires and is replaced by a new call option expiring the following month-end, on the same amount of notional principal.
This staggering of the call option portfolio allows for setting new strikes at least every week as opposed to every month, which we believe creates a more stable and consistent delta profile for the call option strategy as a whole.
Timing risk is also a consideration for the put option strategy that seeks to provide downside protection.
For the put option strategy, the goal is to provide more consistent protection by staggering the positions on a regular monthly basis rather than using longer-term options that all expire at the same time. This approach can be executed by buying new 12-month put options on one sixth of the portfolio every month and selling any current put options that are six months from expiration.
As a result, every month put options on one sixth of the portfolio are sold (with six months to expiration) and are replaced by new 12-month put options on that same one sixth of the portfolio.
This staggering of the put option portfolio achieves the timeliness of having new strikes every month as opposed to every year, which we believe creates a more stable and consistent delta profile for the put option strategy as a whole. Tail risks, after all, are unpredictable, with the consequence that for downside protection to be truly effective, it must be on at all times. Hence, rebalancing the put options systematically every month can offer more consistent protection for a portfolio.
Our study seeks to find better ways for investors to capture the equity risk premium, an approach that targets higher risk-adjusted returns and improved downside risk.
We are excited about the growing interest in low- volatility equity investing but also recognize some of the potential risks and limitations of low beta stocks. Based on our research, we believe an effective approach would be to use sector neutrality to mitigate the duration risk of low beta stocks and to complement low beta stock selection with option strategies that can further enhance the portfolio’s risk-adjusted return potential while helping to provide genuine downside protection
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This material is prepared for use by institutional investors and investment professionals. It is not intended as an offer or solicitation for the purchase or sale of any financial instrument, or any Putnam product or strategy. References to specific asset classes and financial markets are for illustrative purposes only and are not intended to be, and should not be interpreted as, recommendations or investment advice. The opinions expressed in this article represent the current, good-faith views of the author(s) at the time of publication. The views are provided for informational purposes only and are subject to change. This material does not take into account any investor’s particular investment objectives, strategies, tax status, or investment horizon. Investors should consult a financial advisor for advice suited to their individual financial needs. Putnam Investments cannot guarantee the accuracy or completeness of any statements or data contained in the article. Any forward-looking statements speak only as of the date they are made, and Putnam assumes no duty to update them.
Forward-looking statements are subject to numerous assumptions, risks, and uncertainties. Actual results could differ materially from those anticipated. Past performance is not a guarantee of future results. As with any investment, there is a potential for profit as well as the possibility of loss.
Hypothetical performance is for illustrative purposes only and does not reflect actual client trading or the impact of material economic and market factors on Putnam’s decision-making process for an actual Putnam client account. The options strategy simulations are based on certain assumptions, which are based on the current view of Putnam Investments and could change without notice or prove to be incorrect. Different assumptions would produce different results. Performance results were prepared with the benefit of hindsight. Hypothetical options strategy data are shown before fees, transaction costs, and taxes. Management fees would reduce returns, and therefore the probabilities shown. Additional advisory fees, transaction costs, and other potential expenses are not considered and would also reduce returns. Actual results experienced by clients may vary significantly from the hypothetical illustrations shown.
Options strategies that consist of writing (selling) call options and buying put options on individual portfolio securities and on equity indexes have many associated risks. There is no guarantee that an options strategy will produce premium income or reduce portfolio volatility to the extent desired. A transaction in options may be unsuccessful because of market behavior or unexpected events.
For example, unusual market conditions or the lack of a ready market for any particular option at a specific time may impair a portfolio’s ability to enter into new positions or close out existing positions, which may reduce the effectiveness of the options strategy. A portfolio also risks losing all or part of the cash paid for purchasing call and put options if the portfolio does not exercise the options before they expire. Options trading is extremely risky and is not suitable for everyone, and substantial losses may occur.
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