Tail-Risk Parity: The Quest for a Crash-Proof Portfolio

by Ashwin Alankar (pictured) and Michael DePalma, AllianceBernstein

By any name—Black Swan, three-standard-deviation event or negative tail event—the risk of unexpected heavy losses is a major concern for investors. The question is how best to protect against these low-probability, high-impact market moves.

“Well-behaved” vs. “Bad-state” markets

As the 2008 crisis and all those before it have illustrated, the rules of the game under normal conditions are not the same as they are at times of market stress. The portfolio that investors want to hold when asset volatility and correlations are at their long-run averages is not the portfolio they want when volatility is spiking and assets that are usually weakly correlated are all nose-diving together.

That’s why, as history has shown, the old-fashioned static approach to diversification—typified by a permanent 60% in stocks and 40% in  bonds—works well enough in “well-behaved” markets but offers little protection in “bad-state” markets.

This is because bad-state correlations are dramatically higher than “normal” correlations. When correlations spike a “diversified” stock portfolio is not very diversified, nor is any other portfolio that relies on “normal” correlations. In addition, many assets have “fat-tailed” return distributions, in other words, they tend to produce more extreme outcomes on the downside than they do on the upside.

One way to address tail risk is to buy insurance via the options markets. But this costs money—a lot of money. The drag on performance in non-crisis markets can be difficult to bear.

When talking to clients we sometimes offer the example of someone who owns a house in an area that is known to suffer disastrous storms a couple of times a decade. They can pay for insurance every month, or they can opt not to insure, and instead develop an accurate weather warning system that tells them when to set out the sand bags and board up the windows. The question is how to design that warning system.

Volatility vs. Expected Tail Risk

One idea that has caught on is the notion of balancing risks via Risk Parity (RP). RP will adjust the weightings in a portfolio such that each asset class contributes equally to overall portfolio volatility. So at times of crisis the allocation to more volatile assets like equities would be dialled back. This is a significant improvement to the static approach. And in normal times RP works pretty well. The key words here are “normal times”.

Our view—and one in which we differ from many of our peers—is that market volatility is not the best indicator to use in an early warning system. For one thing, not all volatility is bad.  Think back to the build-up of the internet bubble or, the impact of “Abenomics” on Japanese equities earlier this year.  In both cases, rising equity volatility was associated with upside gains rather than down-side risk. So an approach that limits volatility is likely to act as a drag on performance by capping the upside as well as the downside.  More importantly, history shows that we live in a “fat-tailed” world characterized by tail risk: a risk that volatility cannot fully capture.

Our research suggests there’s a better alternative: measuring expected tail loss (ETL). We use a proprietary forward-looking “implied expected tail loss” measure distilled from options-market information and use “bad-state” (tail) correlations to assess diversification benefits.

One of the primary uses of options markets is to allow investors to protect their portfolios from large negative price moves.  Option prices represent the cost of this insurance:  the higher the price, the greater the expectation that the asset will suffer a large loss. This is the key intuition behind our implied ETL calculation.

The “Goldilocks” period of 2006 to 2007 illustrates how volatility and ETL differ as measures of risk. In our simulations, during this period the TRP approach was registering very high levels of equity tail loss risk, whereas volatility was close to historic lows. Options were pricing in the risk of the painful deleveraging process that ultimately contributed to the credit crisis. So, unlike a volatility-based approach that would have been giving the all-clear to take on more equity risk, TRP was signalling a need to reduce equity exposure.

Today, we are facing another correction process as the imbalances created by the US Federal Reserve are re-equilibrating. Amid talks of monetary stimulus tapering off, assets are re-pricing to a new equilibrium. In this environment, tail risk is a very real concern. Premature withdrawal by the Fed could cause a painful downward spiral.

Tail Risk Parity in Practise

To recap, whereas Risk Parity focuses on volatility, Tail Risk Parity defines risk as expected tail loss. In practice, the two portfolios would look very similar in normal times, but different in “bad state” scenarios where the risk of market meltdown is higher.

Tail Risk Parity seeks to reduce tail losses significantly while retaining more upside than Risk Parity or other mean-variance optimization techniques. Our research suggests that a Tail Risk Parity approach hedges the risk of large losses less expensively than using the options market (historically, we estimate savings of about 75% for an equivalent amount of protection).

We believe that Tail Risk Parity offers an attractive solution for investors seeking balanced investment portfolios that can cost-effectively reduce exposures to tail losses.

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AllianceBernstein portfolio-management teams.

Ashwin Alankar and Michael DePalma are Co-Chief Investment Officers of Quantitative Investment Strategies at AllianceBernstein.

Copyright © AllianceBernstein