Separating the alpha from the beta - savvy investors know they need to separate the alpha, or investment gains made from decisions made by manager, from the beta, or returns attributable to the market. Traditionally this has meant seeing how individual funds or managers do compared with an index or other baseline. But these simple measurements have led to underestimating the effects of beta and giving too much credit to active managers.

Increasingly sophisticated risk models are allowing investors to see what gains are due to other replicable factors such implied exposure to asset classes outside the direct investments of the fund. As the hunt for alpha gets ever more difficult, these tools are becoming de rigueur for major institutional investors as they look to out ‘hidden beta’.

The most commonly understood beta is the exposure to an equity market, as in “S&P500 beta”, but in fact there are many other exposures – quants call them “systematic risk factor exposures” which can be shown to drive the return and risk for many funds. 

However these betas are not necessarily obvious or explicit – we may have a big exposure to oil without owning any WTI futures contracts, just by owning common stock in an airline.  Calculating the “implicit” or “hidden” betas is a delicate and complex exercise which combines advanced macro-economics and statistical methods as well as conventional finance theory.

Investors who want to be sure that they are paying for the right kind of skill, need to see exactly how the fund construction methodology employed by their money manager is leading to a host of hidden betas (we could also call them “implied bets”) on these other risk factors.  To make things more complicated, some of these risk factors are not easily described by indices – the prevalence of new trading strategies can provide systematic return to factors such as liquidity and volatility in certain markets for which no indices exist.

What is required is a risk model which captures the effects of systematic risk factors globally across all asset classes.  When we do that we find that there are ways of capturing implied bets to a host of factors which the investor may not have been aware of, but are actually the major drivers of return for many strategies.  A good deal of what has been presented as “alpha” may disappear once this more sophisticated risk analysis has been performed – and crucially the downside risk associated with shocks to the hidden risk factors can come into focus.  Many investors have been disappointed to find that the return they attributed to manager skill can disappear instantly when an economic shock creates a change to a previously hidden risk factor.

In recent years policymakers and central bankers have become ever more powerful generators of shocks to macro risk factors – but the question remains: how can investors get a handle on their exposure to policy shocks?  The answer depends almost entirely on their asset allocation, and far less on “manager skill” than investors might suppose.