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Value-at-Risk for long and short trading positions: The case of the Athens Stock Exchange

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Author Info

  • Panayiotis Diamandis

    (Department of Business Administration, Athens University of Economics and Business)

  • Georgios Kouretas

    () (Department of Economics, University of Crete)

  • Leonidas Zarangas

    (Department of Finance and Auditing, Technological Educational Institute of Epirus)

Abstract

This paper provides Value-at-Risk estimates for daily stock returns with the application of various parametric univariate models that belong to the class of ARCH models which are based on the skewed Student distribution. We use daily data for three stock indexes of the Athens Stock Exchange (ASE) and three stocks of Greek companies listed in the ASE. We conduct our analysis with the adoption of the methodology suggested by Giot and Laurent (2003). Therefore, we estimate an APARCH model based on the skewed Student distribution to fully take into account the fat left and right tails of the returns distribution. We show that the estimated VaR for traders having both long and short positions in the Athens Stock Exchange is more accurately modeled by a skewed Student APARCH model that by a normal or Student distributions.

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File URL: http://economics.soc.uoc.gr/wpa/docs/VaRLSTP.pdf
File Function: First version, 2006
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Bibliographic Info

Paper provided by University of Crete, Department of Economics in its series Working Papers with number 0601.

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Length: 34 pages
Date of creation: Jan 2006
Date of revision:
Handle: RePEc:crt:wpaper:0601

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Keywords: Value-at-Risk; risk management; APARCH models; skewed Student distribution;

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References

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  1. Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-080, New York University, Leonard N. Stern School of Business-.
  2. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
  3. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
  4. Simone Manganelli & Robert F. Engle, 2001. "Value at risk models in finance," Working Paper Series 075, European Central Bank.
  5. Pierre Giot and S»bastien Laurent, 2001. "Value-At-Risk For Long And Short Trading Positions," Computing in Economics and Finance 2001 94, Society for Computational Economics.
  6. Laurent, Sebastien & Peters, Jean-Philippe, 2002. " G@RCH 2.2: An Ox Package for Estimating and Forecasting Various ARCH Models," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 447-85, July.
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Cited by:
  1. Stavros Degiannakis & Christos Floros & Alexandra Livada, 2012. "Evaluating value-at-risk models before and after the financial crisis of 2008: International evidence," Managerial Finance, Emerald Group Publishing, vol. 38(3), pages 436-452, March.

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