A Simplified Approach to the Conditional Estimation of Value at Risk (VAR)

Abstract

Emerging risk-management techniques use Value at Risk (VAR) to assess the market risk of a portfolio. We propose a relative simple method to estimate VAR conditionally to reflect new information about the volatility of securities held in a portfolio with changing weights. While portfolio holdings might aim at diversifying risk, this risk is subject to continuos changes. The GARCH methodology allows us to estimate past and current and predict future risk levels of our current position. The use of historical returns of portfolio components and current weights can produce accurate estimates of current risk for a portfolio of traded securities. Information on the time series properties of the returns of the portfolio components is transformed into a conditional estimate of the current portfolio volatility with no need of using complex time series procedures. Stress testing and correlation stability are discussed in this framework.