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Long Run Value At Risk

Author

Listed:
  • C. Bruneau

    (University of Paris-X Nanterre)

  • M. El Archi

    (Trader, Credit Lyonnais, Paris)

  • J.P. Nicola

    (Chief Investment Officer, Ecureuil Gestion, Paris)

Abstract

In this paper, we aim at computing a long run Value at Risk for a portfolio of different assets and derivatives. The main innovation of the computation is to take into account a modelling of the systematic risk, which is shared by the different components of the portfolio. More precisely, we argue that the systematic risk can be summarized by a limited number of stochastic trends identified in the framework developped for analysing the Common Trends of multivariate dynamics. The data are monthly so that cointegration relationships, identified by using relevant statistical tools and by referrinfg to reliable structural models, allow to improve forecasts of the future returns of the portfolio. For example, we identify fundamental levels for stock indexes, characterized as functions of the growth and well-chosen interest rates, by referring to the Present Value model. We focus on different countries, the US, Japan, UK, France and German over the last decade and summarize the financial dynamics of each country by y a stock index, three domestic interest rates, and, eventually, an exchange rate. The fundamental variables characterize, among others, the growth, the unemployment rate, and so on. Common trends are identified separately for the different countries. Based on the Error Correction representation of the dynamics , computations of the VaR are implemented by using Monte-Carlo simulations for different horizons. We show that the modelling of the systematic risk we propose reduces significantly the medium or long run VaR of the portfolio.

Suggested Citation

  • C. Bruneau & M. El Archi & J.P. Nicola, 2000. "Long Run Value At Risk," Computing in Economics and Finance 2000 77, Society for Computational Economics.
    • Handle: RePEc:sce:scecf0:77
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