方法对比

	Importance Sampling	VaR（风险价值）
领域	仿真	金融学
方法族	Process / pipeline	Regression model
起源年份	1951	2007
提出者	Herman Kahn & Theodore Harris (RAND Corporation, 1951)	Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan
类型	Monte Carlo variance-reduction technique	Financial risk measure
开创性文献	Rubinstein, R.Y. & Kroese, D.P. (2016). Simulation and the Monte Carlo Method (3rd ed.). Wiley.	Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed.). McGraw-Hill. ISBN: 978-0071464956
别名	IS, weighted Monte Carlo, Önem Örneklemesi	VaR, value-at-risk, delta-normal VaR, historical simulation VaR
相关	5	5
摘要	Importance sampling is a Monte Carlo variance-reduction technique that shifts the sampling distribution toward the region of interest — typically a rare or extreme event — so that informative samples are drawn far more often than under the original distribution. Developed at the RAND Corporation by Herman Kahn and Theodore Harris around 1951, it makes tail-probability estimation (such as Value-at-Risk or system-failure probability) tractable where standard Monte Carlo would require an astronomically large number of runs.	Value at Risk is a financial risk measure that estimates the maximum loss a position or portfolio could suffer over a fixed holding period at a given confidence level. It is the standard benchmark in risk management and regulatory capital calculations, developed in the textbook tradition of Jorion (2007) and the Basel market-risk framework.