Jan Viebig

Modeling extreme returns and asymmetric dependence structures of hedge fund strategies using extreme value theory and copula theory

We use extreme value theory and copula theory to model multivariate daily return distributions of hedge fund strategy indexes. Multivariate outliers in time series of hedge fund strategies are clustered when volatilities and credit spreads increase and investors take a “flight to quality” and seek liquidity. In light of the strong “domino effect” in daily return series of hedge fund strategy indexes during the financial crisis 2008–9, the generalized Pareto distribution copula approach is an appropriate modeling choice for approximating multivariate hedge fund distributions exhibiting extreme return observations and asymmetric dependence structures. Generalized Pareto distributions are efficient approximations for the fat-tailed distributions of returns on hedge funds exceeding high thresholds. Tests for correlation symmetry show that dependence structures between several hedge fund strategies are often asymmetric. Copulas can be used to model symmetric and asymmetric dependence structures between different hedge fund strategies.

Does a Contagion Effect Exist Between EquityMarkets and Hedge Funds in Periods of ExtremeStress in Financial Markets

Previous researchers have argued that there is no empirical evidence in support of contagion between equity markets and hedge funds. Unlike previous researchers, the authors of this article assess whether extreme increases in volatility transmit from equities to hedge funds. Using kernel density estimation, they show that the volatility spillover effect between equities and hedge funds is significant at the 99% level of confidence for several hedge-fund strategies. Conducting tests for correlation asymmetry and applying Vector Autoregressive (VAR) models, they find evidence confirming that a contagion effect exists between equity markets and several hedge-fund strategies. The impact of financial crises on hedge funds varies substantially across hedge-fund styles.

Are Emerging Market Investors Overly Pessimistic in Extreme Risk-off Periods?

Motivated by Campbell and Shiller [2001], we ask if future returns and loss probabilities are predictable when markets trade at extremely low, depressed levels. In this paper we present empirical evidence that a predictable “undershooting phenomenon” exists in emerging markets. Depressed valuation ratios are a statistically significant predictor at the 99% level of confidence for future returns in most emerging markets. Overly anxious emerging market investors seem to overreact in periods of extreme stress and fear in financial markets.

Regime-Dependent Nonlinear Analysis of Hedge Funds

In this article, the authors introduce a regime-dependent nonlinear model to explain the nonlinear return and risk characteristics of hedge funds. The explanatory power of their regime-dependent nonlinear model is substantially higher than the explanatory power of simple linear regression models. Instead of applying self-constructed or option-based asset-based style (ABS) factors, the authors use readily observable market factors to attribute the returns of merger arbitrage hedge funds to three common sources of risk. Combining econometric methods for phase identification with regime-switching regressions to build a regime-dependent nonlinear model is shown to be much less time-consuming and less arbitrary in nature than using ABS factor models.