Alliance Bernstein: An Introduction To Tail Risk Parity

Alliance Bernstein: An Introduction To Tail Risk Parity

An Introduction To Tail Risk Parity: Balancing Risk To Achieve Downside Protection by Ashwin Alankar, Michael DePalma, Myron Scholes, AllianceBernstein

Executive Summary

  • Tail Risk Parity (TRP) adapts the risk-balancing techniques of Risk Parity in an attempt to protect the portfolio at times of economic crisis and reduce the cost of the protection in the absence of a crisis.
  • In measuring expected tail loss we use a proprietary “implied expected tail loss (ETL)” measure distilled from options-market information.
  • Whereas Risk Parity focuses on volatility, Tail Risk Parity defines risk as expected tail loss—something that hurts investors more than volatility. Risk Parity is a subset of Tail Risk Parity when asset returns are normally distributed and/or volatility adequately captures tail-loss risk. Hence, when the risk of tail events is negligible, Tail Risk Parity allocations will resemble Risk Parity allocations.
  • Tail Risk Parity seeks to reduce tail losses significantly while retaining more upside than Risk Parity or other mean-variance optimization techniques. It is very difficult to construct portfolios under symmetric risk measures (such as volatility as used in Risk Parity) that don’t penalize both large losses and, unfortunately, large gains.
  • Tail Risk Parity aims to protect investments against large losses when investors can least afford them, when systemic crises unfold and correlations spike unexpectedly. This is exactly when the marginal utility of an extra dollar is highest.
  • Our research suggests that a Tail Risk Parity approach hedges the risk of large losses more cheaply than using the options market (historically we estimate savings of about 50%).
  • 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.


It is often said that the most important decision an investor will ever make is choosing a portfolio’s asset mix—more so than which individual stocks or bonds to hold. As a result, the marketplace is inundated with asset allocation products. Some are passive, maintaining a static asset mix (such as the traditional 60/40 equity/bond portfolio), while others are active. A shortcoming of passive strategies is that they fail to incorporate recent information such as changes in risks and correlations among asset classes. Hence, they pose the danger of assuming concentrated risks from time to time. Although active strategies aim to address these deficiencies, they historically take on parametric forms, such as mean-variance optimization, leading to a new set of shortcomings stemming from the difficulties in forecasting input parameters such as expected returns and correlations.

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As a result of these shortcomings, investors are increasingly gravitating toward more robust risk-weighted allocation approaches that are less prone to calibration errors. In deciding what risks to weight in making portfolio allocation decisions, investors are becoming more interested in tail-loss risks. Extreme losses during crises, no matter how rare, often pose the greatest investment risk. Correlation structures change dramatically at times of shock: during the 2008 crisis, most investors experienced severe losses on multiple asset classes that were not offset with gains on other asset classes in their portfolios. That pattern has emerged during other crises too—in each case leading to potential extreme investment losses unless addressed directly.

Moreover, at times of stress, investors are often forced to incur dead-weight costs to adjust the risks of their portfolios. Often this adjustment takes the form of reducing risks first by liquidating the most liquid assets held to minimize transaction costs. This leaves the portfolio with illiquid assets and, if the crisis worsens, the liquidity of these assets all but dries up, leading investors to suffer very significant costs to reduce risks further. By exhausting the supply of liquid assets early on, the dead-weight adjustment costs are amplified if stress continues as the price of liquidity soars. Mitigation of risks in anticipation of crises would reduce these adjustment costs but might reduce returns in “normal times.” We believe these alternatives—to react to crises or to plan for crises—must be part of the investment decision-making process. Currently, few investment strategies explicitly incorporate these adjustment costs into the allocation decision.

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With this in mind, we developed and tested an asset allocation technology that reduces these dead-weight adjustment costs. It does this by combining the best elements of risk diversification offered by risk-weighted strategies with the loss insurance protection offered by tail-protection products. We call this innovative asset allocation technology “Tail Risk Parity” (TRP).

TRP should be thought of as an alternative to purchasing tail insurance. It provides a form of implicit insurance via its asset allocations, moving away from assets that pose greater tail risk in the future. This differs from tail insurance, which provides explicit protection, though at a potentially very high and unknown cost. We believe that Tail Risk Parity portfolios can offer a solution for price-sensitive investors seeking a balanced investment portfolio with materially smaller exposure to tail losses.

In this paper we will first briefly discuss traditional static asset allocation methods and some of their shortcomings. Second, we will introduce the concept of Risk Parity (RP), which addresses many of the key shortcomings of static asset allocation but, because it makes the crucial assumption of “normal markets,” leaves portfolios vulnerable during stress environments. When the risk of experiencing a stress environment fades, TRP and RP are equivalent and hence RP can be thought of as a special case of TRP. Finally, we will describe TRP and its ability to address the shortcomings of Risk Parity.

Tail Risk Parity

Tail Risk Parity

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