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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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Publisher Info
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

References listed on IDEAS
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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. 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:
  2. Luc, BAUWENS & G., STORTI, 2007. "A Component GARCH Model with Time Varying Weights," Université catholique de Louvain, Département des Sciences Economiques Working Paper 2007012, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
    Other versions:
  3. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics. [Downloadable!]
  4. Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Swedish School of Economics and Business Administration. [Downloadable!]
  5. 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!]
    Other versions:
  6. 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!]
  7. Francois-Éric Racicot & Raymond Théoret, 2006. "La Value-at-Risk: Modèles de la VaR, simulations en Visual Basic (Excel) et autres mesures récentes du risque de marché," RePAd Working Paper Series UQO-DSA-wp022006, Département des sciences administratives, UQO. [Downloadable!]
  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. Neri, Breno de Andrade Pinheiro & Lima, Luiz Renato Regis de Oliveira, 2006. "Comparing Value-at-Risk Methodologies," Economics Working Papers (Ensaios Economicos da EPGE) 629, Graduate School of Economics, Getulio Vargas Foundation (Brazil). [Downloadable!]
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  10. 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!]
  11. 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!]
  12. Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor and Francis Journals, vol. 16(11), pages 835-851, July. [Downloadable!] (restricted)
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  16. Boudt, Kris & Peterson, Brian & Croux, Christophe, 2007. "Estimation and decomposition of downside risk for portfolios with non-normal returns," MPRA Paper 5427, University Library of Munich, Germany, revised 23 Oct 2007. [Downloadable!]
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