Moving from a theoretical framework to implementing a risk premia strategy involves considerable challenges. In many instances, particularly within the equity market, returns are often expressed on a long/short basis, adding a significant amount of cost and complexity. Theoretical portfolios are often rebalanced to such a degree that annual turnover rates not only eat into returns, but also involve a considerable amount of portfolio management, putting them out of reach of many investors. Capacity constraints are also a concern of many market practitioners. All types of trades risk over-crowding and of course if expected returns fall, action may need to be taken. But just because behemoth funds cannot readily trade in and out of risk premia without overly impacting the underlying price does not necessarily negate their worth. Many corporate bonds, for example, lack secondary market liquidity. But we should also remind ourselves that the reason many of these risk premia exist is precisely because of these limits to arbitrage.

That said many strategies do encounter considerable implementation challenges. Running a long/short equity price momentum strategy not only involves an understanding of borrowing costs, but given the strategy turns over 65% of the portfolio each month, to exclude trading costs is nonsensical. Importantly, as the short leg is the key driver of equity momentum profits, running the strategy long whilst simply shorting the benchmark is not particularly viable. That is not to say long/short risk premia is an impossibility, it just means that it takes more work and the costs associated can leave them inaccessible to many investors.

Still, many risk premia strategies are now available in index form and investable via swaps or options. We therefore further try to demonstrate how risk premia investing can not only deliver an interesting return profile, but also to show how many of these ideas have been taken up and moved beyond the mere theoretical.

Understanding the risk profile of each strategy

In this section we take a look at how we might combine risk premia strategies across different assets into a multi-asset portfolio. To do so we need to understand the risk profile of each strategy and how they correspond with each other. To assist us we classify our strategies into groups based on these return characteristics. This helps give us a better understanding of their usefulness and also possible downside risk. We then ask the important questions: How do these risk premia work in combination and is their inclusion into a traditional asset allocation beneficial? Our strategies can be broadly classified into three main styles:

Risk premia strategies – an historical analysis

To allow for a fair comparison of our risk premia strategies across different asset classes, we have removed some risk management strategies, such as volatility targeting, filtering, etc. These techniques make sense when using the strategy on a standalone basis but are not appropriate within this analysis as they tend to disguise the true nature of the underlying risk premium.

We utilize standard performance ratios and statistics commonly used in asset management including the Sharpe ratio (returns divided by volatility), the Sortino ratio (returns divided by downside volatility), maximum drawdown and time to recovery (or the length of the maximum drawdown) and take a look at a variety of risk metrics based on past returns (i.e. volatility, skew and kurtosis) and also use measures designed to evaluate extreme risks such as value-at-risk at 95% and expected shortfall. A strategy with a positive skew is more likely to make large gains than suffer large losses. A high kurtosis indicates potential fat-tails, i.e. a tendency to post unusually large returns, whether either on the upside or the downside.

The best strategies in terms of Sharpe ratio are income strategies. The Sharpe ratio for the aggregated strategy stands above 1.0 in both cases. The equity value, equity dividend and FX carry strategies delivered the strongest returns. Momentum strategies tend to deliver lower Sharpe ratios. Yet, over a shorter time periods, income strategies are more likely to suffer large losses than make large gains. The skewness is a measure of the symmetry of a distribution and a negative skew means that the most extreme movements are on the downside. It would appear that income strategies monetize a premium that comes in compensation for possibly large losses in certain circumstances. Conversely, the skew of momentum and relative value strategies is close to zero, or in some cases positive. Kurtosis (fat tails) is also high for income strategies, especially so for volatility strategies (VIX contango, short variance swaps, volatility risk premium and tail event risk premium strategies). Kurtosis is a measure of extreme risk and, in periods of market stress when volatility rises rapidly, strategies that sell options tend to lose more than most other strategies.