Risk Premia Strategies - Equity Markets
The Art of Selectively Harvesting Attractive Risk Premia
The value risk premium:
We define value using the equal-weighted quintile score of a set of five traditional value factors, which have all been associated with positive returns in academic literature. All factors are taken relative to the median value of the sector, plus where the metric is not applicable (i.e. free cash flow to price for financial companies), we exclude it from the calculation:
After the average score is calculated, we rank all companies in the FTSE World universe and define the top quintile as the long portfolio and the bottom quintile as the short portfolio.
The goal of value strategies is obviously to buy undervalued stocks, although the profile of those undervalued stocks can vary significantly. A value portfolio might invest in companies that have suffered significant price declines and are having difficulties. These difficulties can be company-specific or related to the macro situation at the time. In both cases, the success of the value strategy will be determined by the ability of these companies (and the investor) to sustain losses and eventually fix their problems. Market sentiment is also very important as it affects the degree to which the market is discounting the ability of these companies to bounce back.
Therefore, it is not surprising that we typically see the best performance from value strategies during periods of improving sentiment and economic recovery. For example, from March to November 2009 value strategies gained north of 40% (on a long-short basis). On the other hand, during a downswing the returns of the strategy suffer significant drawdown, with value strategies usually losing more than 20% during 2007/2008. Potential mechanisms for timing entry and exit points for value strategies would warrant a book in themselves but ideas might include valuation dispersion, absolute valuation, levels of equity volatility and an overall view on the macro cycle.
Value portfolios might also include companies that are simply out-of-favour, as seemingly they do not offer the same excitement and growth opportunities which investors think they can get elsewhere. Unlike more cyclical value opportunities, these companies are not necessarily riskier but are quite often very well run businesses that have been left undervalued courtesy of their ‚non-glamour‛ status or are just classified as dull.
For example, during the dot-com bubble, value strategies (again on a long-short basis) suffered a -20% drawdown as the strategy avoided most TMT stocks (a loss that put many value-managers out of work at the time), but then they rallied 70% the first 12 months after the bubble collapsed. Understanding the exposures of a value portfolio for different types of company is clearly important when assessing the risks (and potential rewards) of the strategy.
THE MOMENTUM RISK PREMIUM:
As with the value effect, there is a continuing debate about possible explanations of the momentum effect. With efficient market hypothesis supporters failing to convincingly tie momentum profits to some sort of compensation for additional risk, behavioural finance explanations have been more prominent. The most popular ones draw from behavioural biases such as overconfidence and loss aversion and link momentum profits to under- or over-reactions to company-specific news.
Momentum investing came under pressure after the great momentum crash of 2009, when a traditional momentum strategy (12-month lagged by one-month) lost more than 60% in the space of a few months. Whilst this clearly provided some ammunition in favour of a risk-based explanation, momentum stock selection during that period was mainly driven by the macro environment rather than capturing any reaction to company-specific news. As we have discussed before, during periods when macro conditions influence stock performance, momentum becomes a bet on the underlying macro story. As a result, if the macro direction changes abruptly (as it has a tendency to do), momentum will incur heavy losses.
Since 2009 researchers have been proposing risk/macro adjusted momentum metrics to mitigate the impact of macro and better isolate momentum effects. Whilst we recognise that it is always easier to go back and fix a problem after the event, not learning from past mistakes is unwise. QMS Advisors utilizes residual momentum approaches to investing, as it mitigates some of the macro effects and offers a far more appealing risk/return profile than adjusted momentum returns.
rit = αi + βitrmt + ϵit
where rit is the total return of stock i, rmt is the total return of the stock's local market index and αi , βi the parameters to be estimated from the regression.
We have also found that avoiding shorting stocks that have fallen too much can further improve the profile of momentum strategies. We utilize a "drawdown filter" using the drawdown of the stock’s price (i.e. the percentage from its prior one-year peak) and exclude stocks that have fallen by more than 70%. After excluding these stocks, we rank companies in quintiles based on their residual momentum and define the long and short portfolios using the top and bottom quintiles.
Our backtested momentum factor has averaged 9% per year since 1995. Nevertheless, the strategy has still suffered significant losses during the period following the dot-com bubble (2000/2001) and post March 2009. During the latter, our momentum strategy has seen its worst performance, with an 18% drawdown (which would have been more than 60% without controlling the macro risk). When comparing the performance of momentum to that of value during those periods, we see that they followed contrasting patterns with momentum doing well before 2000 and 2009 and falling afterwards whilst value was struggling before 2000 and 2009 but strongly recovered thereafter. The negative correlation of value and momentum during such volatile periods is the main reason why this combination has been so commonly applied in the quant world and why many include momentum in a risk premia portfolio.
THE HIGH YIELD RISK PREMIUM:
Historically, dividends have represented the greatest component of returns, and dividend yield is the more consistent component of returns through time.
Whilst we favor including quality characteristics in a high yield strategy _to avoid investing in stocks with unrealistic or unsustainable dividends_ here we analyze the dividend yield strategy by simply considering the trailing dividend yield. We define the long portfolio as the top quintile of stocks with the highest dividend yield and the short portfolio as the bottom quintile (excluding stocks with a zero dividend yield).
Like the value and momentum strategies above, the yield strategy has also outperformed significantly since 1995, averaging 9.8% per year on a long/short basis. Although it is highly correlated (+0.74) with the value strategy, and sharing the same periods of underperformance, dividend yield has seen more severe drawdowns during these periods and, as such, has underperformed our value index. Without the quality controls that QMS Advisors normally include in a high yield portfolio, the profile of the yield strategy is a lot riskier and certainly a lot less appealing than that of value strategies.
THE QUALITY OR LOW VOLATILITY RISK PREMIUM:
That said, with equities suffering two heavy drawdowns since 2000, investors have been reducing equity allocations and looking for ways to manage the risk of their equity portfolios.
Explanations of the low volatility anomaly are mainly focused around behaviour biases, like the lottery effect, representativeness and over-confidence. These biases lead investors to overpay for the more exciting/higher upside, lower quality stocks whilst undervaluing the less exciting/limited upside, high quality companies. Several have again highlighted benchmark and business restrictions to also be important and we have also found that analyst overoptimism and an under estimation of the dangers of leverage are key drivers of the anomaly. Most define quality by simply looking at historical price volatility of the stock or the sensitivity of the stock to market movements (i.e. beta). QMS Advisors utilizes a combination of the volatility of the stock and its leverage, and using the Merton model we find that it is the combination of high volatility and high leverage that compounds problems.
There is also the option to define quality using company fundamentals, as suggested by Joseph Piotroski, which we believe can add value on top of market implied quality measures. As the Piotroski score can range from 0 to 9 (depending on how many of the binary fundamental tests a company passes), QMS Advisors combines it with the Merton quintile score using a weighted average. The top quintile of stocks with the highest weighted scores within the FTSE World universe comprises our high quality portfolio and, similarly, the bottom quintile makes up the low quality portfolio. Unfortunately, neither the Merton nor the Piotroski models can be applied to the complicated capital structures of financial companies, which are therefore excluded from our quality portfolios.
THE SMALL-CAP RISK PREMIUM:
To be consistent with the construction of the previous strategies, we have again used the FTSE World index to define our size benchmark. We use the free float market cap of each stock and define the long portfolio as the bottom quintile and the short portfolio as the top quintile. Obviously, by focusing on a large/mid cap universe, like FTSE World, to define the size portfolios we expect to find weaker effects than those reported in academic literature.
In our study small cap companies have, on average, outperformed large caps by 2.5% since 1995 with the positive return mainly being generated during two periods, 1997-2005 and the strong market recovery post March 2009. The higher return of small caps is proportional to their higher risk, as measured by volatility, and so risk-adjusted returns are similar.
Risk Premia - Equities
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