The value-at-risk is the maximum loss that a portfolio might suffer over a given holding period with a certain confidence level. In recent years, value-at-risk has become a benchmark for measuring financial risk used by both practitioners and regulators. We present an efficient algorithm for computing value-at-risk and the value-at-risk gradient for portfolios of derivative securities. In particular, we discuss dimensional reduction of the model and applications to hedging of derivatives portfolios.