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. In this seminar, we discuss value-at-risk from a modeling and simulation perspective. We present a new 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 present some recent results on perturbation theory and applications to hedging of derivatives portfolios.