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Value-At-Risk For Long And Short Trading Positions

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Author Info
Pierre Giot and S»bastien Laurent

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Abstract

In this paper we model Value-at-Risk (VaR) for daily stock index returns using a collection of parametric models of the ARCH family based on the skewed Student distribution. We show that models that rely on a symmetric density distribution for the error term underperform with respect to skewed density models when the left and right tails of the distribution of returns must be modelled. Thus, VaR for traders having both long {and short} positions is not adequately modelled using usual Normal or Student distributions. We suggest using an APARCH model based on the skewed Student distribution to fully take into account the fat left and right tails of the returns distribution. This allows for an adequate modelling of large returns defined on long and short trading positions. The performances of all models are assessed on daily data for the CAC40, DAX, NASDAQ, NIKKEI and SMI stock indexes. We also compute the expected short-fall and the average multiple of tail event to risk measure for the new model.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 94.

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Date of creation: 01 Apr 2001
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Handle: RePEc:sce:scecf1:94

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Related research
Keywords: Value-at-Risk; Expected short-fall; Skewed Student distribution; APARCH; short trading;

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Find related papers by JEL classification:
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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  1. Maria Rosa Nieto & Esther Ruiz, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," Statistics and Econometrics Working Papers ws087326, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
  2. Marno Verbeek & Jeroen VK Rombouts, 2005. "Evaluating Portfolio Value-at-Risk using Semi-Parametric GARCH Models," Computing in Economics and Finance 2005 40, Society for Computational Economics. [Downloadable!]
    Other versions:
  3. Luc, BAUWENS & G., STORTI, 2007. "A Component GARCH Model with Time Varying Weights," Discussion Papers (ECON - Département des Sciences Economiques) 2007012, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
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  4. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics. [Downloadable!]
  5. Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Hanken School of Economics. [Downloadable!]
  6. Giot,Pierre & Laurent,Sebastien, 2001. "Modelling daily value-at-risk using realized volatility and arch type models," Research Memoranda 014, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization. [Downloadable!]
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  7. Jeroen Rombouts & E.W. Rengifo, 2004. "Dynamic Optimal Portfolio Selection in a VaR Framework," Cahiers de recherche 04-05, HEC Montréal, Institut d'économie appliquée. [Downloadable!]
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  8. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Assessing the performance of a prediction error criterion model selection algorithm in the context of ARCH models," Applied Financial Economics, Taylor and Francis Journals, vol. 17(2), pages 149-171, January. [Downloadable!] (restricted)
  9. Wong, Woon K & Copeland, Laurence, 2008. "Risk Measurement and Management in a Crisis-Prone World," Cardiff Economics Working Papers E2008/14, Cardiff University, Cardiff Business School, Economics Section. [Downloadable!]
  10. Panayiotis Diamandis & Georgios Kouretas & Leonidas Zarangas, 2006. "Value-at-Risk for long and short trading positions: The case of the Athens Stock Exchange," Working Papers 0601, University of Crete, Department of Economics. [Downloadable!]
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