Title: Hedge funds portfolio optimisation using a vine copula-GARCH-EVT-CVaR model

Authors: Rihab Bedoui; Sameh Noiali; Haykel Hamdi

Addresses: LaREMFiQ, IHEC of Sousse, B.P. 40, Route de la Ceinture, Sahloul III 4054 Sousse, Tunisia ' STB Bank, Tunisia ' Laboratory for Research on Quantitative Development Economics, Faculty of Economics and Management of Tunis, B.P. 248 El Manar II 2092 Tunis, Tunisia

Abstract: This paper investigates the conditional value-at-risk (CVaR) hedge funds portfolio optimisation approach using a univariate GARCH type model, extreme value theory (EVT) and the vine copula to determine the optimal allocation for hedge funds portfolio. First, we apply the generalised pareto distribution (GPD) to model the tails of the innovation of each hedge funds strategy return. Second, we capture the interdependence structure between hedge funds strategies and construct vine copula-GARCH-EVT model. Then, we combine it with Monte Carlo simulation and mean-CVaR model to optimise hedge funds portfolio, in order to estimate the risk more accurately. The empirical results of five Hedge funds indexes show that the C-vine copula can better characterise the interdependence structure between the different hedge funds strategies and the performance of C-vine copula-GARCH-EVT-CVaR model is better that of multivariate copulas-GARCH-EVT-CVaR models in portfolio optimisation.

Keywords: hedge funds; vine copula; GARCH; extreme value theory; EVT; conditional value-at-risk; CVaR; portfolio optimisation.

DOI: 10.1504/IJESB.2020.104247

International Journal of Entrepreneurship and Small Business, 2020 Vol.39 No.1/2, pp.121 - 148

Received: 05 Jan 2018
Accepted: 11 Apr 2018
Published online: 23 Dec 2019 *

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