After enduring the (40%) global equity market collapse of 2008, investors large and small are eager to reexamine the perils posed by equity market “tail risk” events.

For our examination into this topic, we studied 50 years of historical S&P 500 Index data and compared the actual tail risk frequency and magnitude to the expectations of a typical investor operating under the assumptions of modern portfolio theory. The difference between the two is surprising, and it suggests that investors have significantly underestimated tail risk frequency and severity.

What is tail risk?
“Tail risk” or “left-tail risk” refers to an investment’s most extreme downside performance periods. Most notably, these events exceed expectations of frequency, duration, and/or magnitude of losses for which an investor has planned, or for which the investor is being compensated. These events are responsible for significant wealth destruction, and so it is vital that investors develop a realistic assessment of an investment’s true tail risk probabilities.

All tail risk events, whether in equities or other asset classes, are the result of excessively fast and/or consistent capital flows, which themselves are the result of significant asymmetries in investor demand. Under normal circumstances, investor supply and demand gently rises and falls in relative equilibrium, much like waves on a vast economic ocean. Under extreme tail event periods, however, these investor demand asymmetries are so large that they are often described as a flight, such as flight to quality, flight from sovereignty, or credit flight.

The resulting capital flows may move from one asset class to another, from one sector within an asset classto another, from one economy to another, or to some degree all of the above simultaneously. Examples are many. Capital may leave equities and run to the safety of bonds, triggering an excessive fall in stock prices. Capital may run from low quality credit to high, from long duration to short, or from the euro to the dollar in a serial or momentum-driven fashion. Importantly, while predictions make good theatre, investors should acknowledge that the magnitude and timing of these events is difficult to predict, while simultaneously designing better compensations for the realistic risks they have assumed.

Why examine S&P 500 distributions?
For our analysis, we examined not only actual S&P 500 tail risk events over the past half-century, but we also modelled investors’ expectations as well. Why?

Many investors assume equity market returns conform to a symmetric, bell-shaped (or “normal”) distribution curve. In fact, many commercially available asset allocation software packages make a similar assumption. This assumption translates into a sense that equity markets reliably drift higher over time, and that extreme highs and lows generally balance out because they occur with equal frequency. Given this assumption’s prevalence, we modelled this scenario as well. To do this, we created an expected return distribution for the S&P 500 Index using standard Monte Carlo simulation methods based on a normal distribution assumption with inputs derived from actual S&P 500 data for the previous 50 years.

We also plotted the actual distribution of returns for the S&P 500 over the same period, and as the chart reveals, equity returns do not conform to the expected bell-shaped return distribution. Instead, the S&P 500’s returns are asymmetrically weighted to the left-tail side – in other words, the frequency and magnitude of severe downside periods is significantly higher than investors may expect.

It is worth noting that the equity market’s tail risk signature is both well-known and persistent over time. Our analysis is not anomalous, and is easily replicated using any reasonably long period of historical return data. Second, it is also worth noting that this tail risk effect is not just confined to the S&P 500, nor is it confined to equities exclusively. Rather, this phenomenon is seen widely across capital markets and real assets.

Failing to mitigate equity tail risk
Even those investors who are familiar with the notion of excess left-tail risk almost always underestimate its frequency and severity. For example, in the presence of realistic volatility and tail risk, investors expecting 8% returns per year could very easily achieve compound returns of only 4-5% per year after decades of real world experience. The compounded difference between these ranges is staggering, as are the shortfall implications.

Our analysis suggests that the average investor encountered severe rolling quarterly losses 5.3x more frequently on average than they would have expected. Viewed over the course of an average decade, investors would have expected about 6.5 such tail events, whereas the actual S&P 500 delivered 34. These results suggest that the average investor, or the software code embedded within their asset allocation software, may be harboring unrealistically favorable expectations about the true nature of equity market tail risk probability.

How can investors mitigate equity tail risk?
There are at least three actionable remedies that investors can consider to mitigate equity tail risk. We will call them pay, refine, and harness.

Pay – hedge to counter tail risk
One approach is to pursue an active hedging strategy to surgically mitigate the risk inherent with long-only equity beta. For example, investors may choose to: buy insurance in the form of a VIX index or other volatility-based product; purchase puts in an ongoing overlay; or engage in customised swaps. These and other active hedging techniques act to transfer excess risk to a counterparty willing to charge the investor for accepting this risk.

Because there is no free lunch with risk transfer to sophisticated counterparties, the obvious downside is that this is expensive, not only because of profit margins on the hedges but because the risks themselves are significant. Other downsides to the active hedging option include complexity, the introduction of exogenous counterparty and calculation risks, and the fact that these strategies have a long-term cost, especially during benign market conditions.

Refine – diversify
A second approach is to exchange long/only equity exposure for “active equity” hedge fund exposure. Here, we define “active equity” hedge fund exposure as the composite performance of most broad hedge fund indices, or as the composite performance of those styles with historically high equity betas such as long/short equity or event driven. The merits of diversifying among “active equity” managers can be seen by reviewing the performance of historical hedge fund indices which reveals that over the long-term these strategies have delivered equity-equivalent returns, but with approximately half the volatility and drawdown of the broader markets.

These managers are still drawing much of their performance from underlying equity beta, but they are doing so in a more refined and risk controlled fashion. One reason for this ability is because these managers are not rigidly bound to equity market benchmarks, granting them useful discretion to both mitigate risk and capitalise on opportunities. By comparison, long/only equity fund managers too often bear the burden of dual objectives: benchmark adherence, and performance. This conflict imposes perverse incentives, such as being fully invested in markets with few opportunities for fear of style drift, while rarely demonstrating the requisite manager alpha to overcome their management fees.

Harness – add multi-asset strategies
The two remedies above share a common focus on mitigating equity tail risk by either countering or refining equity beta. The unspoken premise in both is that equity beta remains the cornerstone of portfolio construction for capital appreciation. However, another actionable remedy is to broaden one’s sources of capital appreciation to include investment strategies that generate returns differently, strategies capable of harnessing the excessive and extended capital flows themselves, the same recurrent capital flow mechanism that, in excess, creates “tail risk” periods.

A handful of investment strategies, including managed futures and global macro, specialise in capturing returns from excessively strong, fast or sustained capital flows, whether moving between asset classes or among segments within asset classes. These two strategies are uniquely suited to this task because they are multi-asset strategies, i.e. they invest across all major asset classes where capital flows: equity indices, commodities, interest rates and currencies.

These strategies are well suited to mitigating tail risk because during periods of severe or prolonged equity market stress, these strategies demonstrate increasingly negative correlations to the wider markets. In addition, unlike the active hedging techniques previously described (i.e., pay scenario), these strategies have strong positive and risk-adjusted return expectations. Unlike the “active equity” remedy (i.e., refine scenario), these strategies have no underlying correlation or reliance on equity beta, making them true portfolio diversifiers.

Patrick Welton is the CEO of Welton Investment Corporation. He has been an active investor since 1981 and an investment manager since 1989. Welton has served on committees for the Managed Funds Association (MFA) and as a member of the Board of Directors of the National Futures Association (NFA) from 1997-2000.He currently serves as an investment committee member of a foundation, a California pension plan and an endowment.

Christopher Keenan oversees Welton’s strategic marketing initiatives and is a member of the firm’s management operating committee. Keenan previously worked in investment banking with Bear Stearns, and with Intel’s internal venture capital group, Intel Capital. Prior to Intel, he was a management consultant with GeoPartners Research, which is now part of CSMG Adventis, serving Fortune 1000 clients.