Hedge Fund Systemic Risk Signals

47 Pages Posted: 2 Apr 2011

See all articles by Roberto Savona

Roberto Savona

University of Brescia - Department of Economics and Management

Date Written: November 1, 2010

Abstract

In this paper we realize an early warning system for hedge funds based on specific red flags that help to detect symptoms of impending extreme negative returns and contagion effect. To do this we rely on regression trees analysis identifying a series of splitting rules which act as risk signals. The empirical findings prove that contagion, crowded-trade, leverage commonality and liquidity concerns are the leading indicators to be used to predict worst returns. We do not only provide a variable selection among potential predictors, but we also assign the values for such predictors that should be considered as excessively risky. Out-of-sample analysis documents that such an approach would have been able to predict more than 90 per cent of the total worst returns occurred over the period 2007-2008. Yet, an in depth analysis of contagion reveals a changing and complex nature of hedge fund systemic risk which reflects on poor forecasting ability.

Keywords: Hedge Funds, Dynamic Conditional Correlations, Time-varying beta, Regression Trees

JEL Classification: C11, C13, G12, G13

Suggested Citation

Savona, Roberto, Hedge Fund Systemic Risk Signals (November 1, 2010). CAREFIN Research Paper No. 19/2010, Available at SSRN: https://ssrn.com/abstract=1799852

Roberto Savona (Contact Author)

University of Brescia - Department of Economics and Management ( email )

Contrada Santa Chiara, 50
BRESCIA, BS 25122
Italy

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
238
Abstract Views
1,650
Rank
232,465
PlumX Metrics