2013 was not the first year when a solid start turned into a “risk-off” environment during the second half, with investors fast shying away from riskier assets. Investors, marked with rather bad experiences over the last years, are increasingly looking for ways to shield their portfolios against volatile markets. So let's analyse some different risk-management approaches for equity portfolios, starting with “tail risk”.
After Lehman Brothers went bust five years ago, triggering one of the worst financial crises in contemporary history, investors became increasingly concerned about so-called tail risks. Tail risk measures the probability of rare events occurring; something that needs careful assessment when constructing portfolios.
Tail Risk Explained
First and foremost, we shall define tail risk as an important statistical term, especially within the asset management industry. No need to panic!, “statistics” doesn't necessarily mean "overly complicated". Tails refer to the small ends of a normal distribution of returns, i.e. when the line on your graph of returns plotted over time tails off. Generally, it is assumed that returns are “normal” distributed and symmetric, respectively. A normal distribution of data is referred to as a statistical distribution model. For an investment, a normal distribution refers to the probability of how much return will be generated over a specific period of time and how these returns are distributed.
The below graph shows that in a normal distribution most of the investment returns will centre around the average. Extreme events, which have a much lower probability of occurring, are located to the far right and left in the distribution – the so-called “tails”.
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Ideally, a portfolio is constructed in such a way that the returns occur as infrequent as possible in the left tail without simultaneously reducing the upside potential, meaning the returns in the right tail. The problem, however, is that risk models usually assume a normal distribution of returns of portfolios or financial instruments. But theory and reality don't always go hand in hand. Theory would have us believe that severe financial crises rarely occur. Reality shows the opposite to be quite often the case, though. So far this century we have witnessed the tech-bubble burst; Argentina defaulting on its debt; and of course, the collapse of Lehman Brothers triggering a global financial crisis with particularly damaging effects for the eurozone sovereign debt market. Last but not least, let's not forget the Japanese tsunami and the subsequent Fukushima nuclear crisis.
To put it bluntly: extreme events, or so-called tail risk events, happen more often than the “normal” statistical framework would suggest. In fact, during the last three decades, we have witnessed a market shock every three to five years, according to some estimates. Any of those shocks would lead us to the fat tails of the distribution. As such, when constructing portfolios, investors would probably be better served by granting a higher probability to them. In other words; the ideal curve (i.e. the normal distribution) needs to be adjusted to account for much higher probabilities of big losses, as represented by the green curve of the above graph.
As no one has a crystal ball, anyone wishing to protect their portfolio against extreme events should have a closer look at systematic strategies that might serve that purpose. There are several such strategies, each with their own pros and cons. Here we've dipped into tail risk; stay tuned for more articles in which we will discuss the most important risk-management strategies in detail.
