Tail risk

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Tail risk, sometimes called "fat tail risk", is the financial risk of an asset or portfolio of assets moving more than three standard deviations from its current price, above the risk of a normal distribution. Tail risks include low-probability events arising at both ends of a normal distribution curve, also known as tail events. [1] However, as investors are generally more concerned with unexpected losses rather than gains, a debate about tail risk is focused on the left tail. Prudent asset managers are typically cautious with the tail involving losses which could damage or ruin portfolios, and not the beneficial tail of outsized gains. [2]

Contents

The common technique of theorizing a normal distribution of price changes underestimates tail risk when market data exhibit fat tails, thus understating asset prices, stock returns and subsequent risk management strategies.

Tail risk is sometimes defined less strictly: as merely the risk (or probability) of rare events. [3] The arbitrary definition of the tail region as beyond three standard deviations may also be broadened, such as the SKEW index which uses the larger tail region starting at two standard deviations.

Although tail risk cannot be eliminated, its impact can be somewhat mitigated by a robust diversification across assets, strategies, and the use of an asymmetric hedge.

Characteristics of tail risk

Traditional portfolio strategies rely heavily upon the assumption that market returns follow a normal distribution, characterized by the bell curve, which illustrates that, given enough observations, all values in a sample will be distributed symmetrically with respect to the mean. [1] The empirical rule then states that about 99.7% of all variations following a normal distribution lies within three standard deviations of the mean. [4] Therefore, there is only a 0.3% chance of an extreme event occurring. Many financial models such as Modern Portfolio Theory and Efficient Markets assume normality.

However, financial markets are not perfect as they are largely shaped by unpredictable human behavior and an abundance of evidence suggests that the distribution of returns is in fact not normal, but skewed. Observed tails are fatter than traditionally predicted, indicating a significantly higher probability that an investment will move beyond three standard deviations. [5] This happens when a rare, unpredictable, and very important event occurs, resulting in significant fluctuations in the value of the stock. Tail risk is then the chance of a loss occurring due to such events. These tail events are often referred to as black swan events and they can produce disastrous effects on the returns of the portfolio in a very short span of time. Fat tails suggest that the likelihood of such events is in fact greater than the one predicted by traditional strategies, which subsequently tend to understate volatility and risk of the asset.

The importance of considering tail risk in portfolio management is not only theoretical. McRandal and Rozanov (2012) observe that in the period from the late 1980s to the early 2010s, there were at least seven episodes that can be viewed as tail events: equity market crash of 1987, 1994 bond market crisis, 1997 Asian financial crisis, 1998 Russian financial crisis and the Long-Term Capital Management blow-up, dot-com bubble collapse, subprime mortgage crisis, and infamous Bankruptcy of Lehman Brothers. [6]

Tail risk measures

Tail risk is very difficult to measure as tail events happen infrequently and with various impact. The most popular tail risk measures include conditional value-at-risk (CVaR) and value-at-risk (VaR). These measures are used both in finance and insurance industries, which tend to be highly volatile, as well as in highly reliable, safety-critical uncertain environments with heavy-tailed underlying probability distributions. [7]

Tail risk hedging

Role of the 2007–2008 financial crisis

The 2007–2008 financial crisis and the Great Recession, which had a dramatic material impact on investment portfolios, led to a significant increase in awareness of tail risks. Even highly sophisticated institutions such as American university endowments, long-established sovereign wealth funds, and highly experienced public pension plans, suffered large double digit percentage drops in value during the Great Recession. According to McRandal and Rozanov (2012), losses of many broadly diversified, multi-asset class portfolios ranged anywhere from 20% to 30% in the course of just a few months. [6]

Defining tail risk

If one is to implement an effective tail risk hedging program, one has to begin by carefully defining tail risk, i.e. by identifying elements of a tail event that investors are hedging against. A true tail event should exhibit the following three properties simultaneously with significant magnitude and speed: falling asset prices, increasing risk premia, and increasing correlations between asset classes. [6]

However, these statistical characteristics can be validated only after the event, and so hedging against these events is a rather challenging, though vital, task for providing the stability of a portfolio whose aim is to meet its long-term risk/return objectives.

Actively managed tail hedge strategies

Active tail risk managers with an appropriate expertise, including practical experience applying macroeconomic forecasting and quantitative modeling techniques across asset markets, are needed to devise effective tail risk hedging strategies in the complex markets. First, possible epicenters of tail events and their repercussions are identified. This is referred to as idea generation. Second, the actual process of constructing the hedge takes place. Finally, an active tail hedge manager guarantees constant effectiveness of the optimal protection by an active trading of positions and risk levels still offering significant convexity. When all these steps are combined, alpha, i.e. an investment strategy’s ability to beat the market, [8] can be generated using several different angles.

As a result, active management minimizes ‘negative carry’ (a condition in which the cost of holding an investment or security exceeds the income earned while holding it) [9] and provides sufficient ongoing security and a truly convex payoff delivered in tail events. Furthermore, it manages to mitigate counterparty risk, which is particularly relevant in case of tail events.

See also

Related Research Articles

Finance refers to monetary resources and to the study and discipline of money, currency, assets and liabilities. As a subject of study, it is related to but distinct from economics, which is the study of the production, distribution, and consumption of goods and services. Based on the scope of financial activities in financial systems, the discipline can be divided into personal, corporate, and public finance.

<span class="mw-page-title-main">Value at risk</span> Estimated potential loss for an investment under a given set of conditions

Value at risk (VaR) is a measure of the risk of loss of investment/Capital. It estimates how much a set of investments might lose, given normal market conditions, in a set time period such as a day. VaR is typically used by firms and regulators in the financial industry to gauge the amount of assets needed to cover possible losses.

Market risk is the risk of losses in positions arising from movements in market variables like prices and volatility. There is no unique classification as each classification may refer to different aspects of market risk. Nevertheless, the most commonly used types of market risk are:

In finance, the Sharpe ratio measures the performance of an investment such as a security or portfolio compared to a risk-free asset, after adjusting for its risk. It is defined as the difference between the returns of the investment and the risk-free return, divided by the standard deviation of the investment returns. It represents the additional amount of return that an investor receives per unit of increase in risk.

The Sortino ratio measures the risk-adjusted return of an investment asset, portfolio, or strategy. It is a modification of the Sharpe ratio but penalizes only those returns falling below a user-specified target or required rate of return, while the Sharpe ratio penalizes both upside and downside volatility equally. Though both ratios measure an investment's risk-adjusted return, they do so in significantly different ways that will frequently lead to differing conclusions as to the true nature of the investment's return-generating efficiency.

Financial risk management is the practice of protecting economic value in a firm by managing exposure to financial risk - principally operational risk, credit risk and market risk, with more specific variants as listed aside. As for risk management more generally, financial risk management requires identifying the sources of risk, measuring these, and crafting plans to mitigate them. See Finance § Risk management for an overview.

Alpha is a measure of the active return on an investment, the performance of that investment compared with a suitable market index. An alpha of 1% means the investment's return on investment over a selected period of time was 1% better than the market during that same period; a negative alpha means the investment underperformed the market.

Financial risk is any of various types of risk associated with financing, including financial transactions that include company loans in risk of default. Often it is understood to include only downside risk, meaning the potential for financial loss and uncertainty about its extent.

A fat-tailed distribution is a probability distribution that exhibits a large skewness or kurtosis, relative to that of either a normal distribution or an exponential distribution. In common usage, the terms fat-tailed and heavy-tailed are sometimes synonymous; fat-tailed is sometimes also defined as a subset of heavy-tailed. Different research communities favor one or the other largely for historical reasons, and may have differences in the precise definition of either.

Foreign exchange risk is a financial risk that exists when a financial transaction is denominated in a currency other than the domestic currency of the company. The exchange risk arises when there is a risk of an unfavourable change in exchange rate between the domestic currency and the denominated currency before the date when the transaction is completed.

The following outline is provided as an overview of and topical guide to finance:

In statistics and decision theory, kurtosis risk is the risk that results when a statistical model assumes the normal distribution, but is applied to observations that have a tendency to occasionally be much farther from the average than is expected for a normal distribution.

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<span class="mw-page-title-main">Taleb distribution</span> Type of probability distribution in economics

In economics and finance, a Taleb distribution is the statistical profile of an investment which normally provides a payoff of small positive returns, while carrying a small but significant risk of catastrophic losses. The term was coined by journalist Martin Wolf and economist John Kay to describe investments with a "high probability of a modest gain and a low probability of huge losses in any period."

The bias ratio is an indicator used in finance to analyze the returns of investment portfolios, and in performing due diligence.

<span class="mw-page-title-main">Portfolio optimization</span> Process of selecting a portfolio

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Downside risk is the financial risk associated with losses. That is, it is the risk of the actual return being below the expected return, or the uncertainty about the magnitude of that difference.

Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling in the financial field.

Risk of ruin is a concept in gambling, insurance, and finance relating to the likelihood of losing all one's investment capital or extinguishing one's bankroll below the minimum for further play. For instance, if someone bets all their money on a simple coin toss, the risk of ruin is 50%. In a multiple-bet scenario, risk of ruin accumulates with the number of bets: each play increases the risk, and persistent play ultimately yields the stochastic certainty of gambler's ruin.

<span class="mw-page-title-main">Holy grail distribution</span> Probability distribution with a positive mean and a right fat tail

In economics and finance, a holy grail distribution is a probability distribution with positive mean and right fat tail — a returns profile of a hypothetical investment vehicle that produces small returns centered on zero and occasionally exhibits outsized positive returns.

References

  1. 1 2 Hayes, Adam. "Tail Risk in Investments". Investopedia. Retrieved 2021-04-24.
  2. Vineer Bhansali (December 2008). "Tail Risk Management: Why Investors Should Be Chasing Their Tails". PIMCO . Retrieved 30 March 2017.
  3. Ken Akoundi; John Haugh. "Tail Risk Hedging: A Roadmap for Asset Owners" (PDF). Deutsche Bank . Retrieved June 16, 2012.
  4. Hayes, Adam. "Empirical Rule". Investopedia. Retrieved 2021-04-24.
  5. Nguyen, Linh Hoang; Lambe, Brendan John (2021). "International tail risk connectedness: Network and determinants". Journal of International Financial Markets, Institutions and Money. 72: 101332. doi:10.1016/j.intfin.2021.101332. ISSN   1042-4431. S2CID   233618877.
  6. 1 2 3 McRandal, Ryan; Rozanov, Andrew (2012). "A primer on tail risk hedging". Journal of Securities Operations & Custody. 5: 29–36. ISSN   1753-1802.
  7. Agrawal, Shubhada; Koolen, Wouter M.; Juneja, Sandeep (2020). "Optimal Best-Arm Identification Methods for Tail-Risk Measures". arXiv: 2008.07606 [cs.LG].
  8. Chen, James. "Alpha". Investopedia. Retrieved 2021-04-22.
  9. Scott, Gordon. "Negative Carry Definition". Investopedia. Retrieved 2021-04-22.