Filtered historical simulation provides the general framework to our backtests of portfolios of derivative securities held by a large sample of financial institutions. We allow for stochastic volatility and exchange rates. ...

Filtered historical simulation provides the general framework to our backtests of portfolios of derivative securities held by a large sample of financial institutions. We allow for stochastic volatility and exchange rates. ...

Value at risk is becoming increasingly popular as a management and regulatory tool. But before this acceptance goes much further, we need to assess its reliability under financial market conditions. Most VAR models deal ...

This paper we backtest the FHS VaR model on three types of portfolios invested over a period of two years. The first set of backtests consists of LIFFE financial futures and options contracts traded on LIFFE. In the second ...

VaR (value-at-risk) estimates are currently based on two main techniques: the variance-covariance approach or simulation. Statistical and computational problems affect the reliability of these techniques. We illustrate a ...

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 ...

We propose filtering historical simulation by GARCH processes to model the future distribution of assets and swap values. Options’ price changes are computed by full reevaluation on the changing prices of underlying assets. ...