Estimating Financial Risk with Apache Spark | Cloudera Engineering Blog
Learn how Spark facilitates the calculation of computationally-intensive statistics such as VaR via the Monte Carlo method. Under reasonable circumstances, how much money can you expect to lose? The financial statistic value at risk (VaR) seeks to answer this question. Since its development on Wall Street soon after the stock market crash of 1987, VaR has been widely adopted across the financial services industry. Some organizations report the statistic to satisfy regulations, some use it to better understand the risk characteristics of large portfolios, and others compute it before executing trades to help make informed and immediate decisions. For reasons that we will delve into later, reaching an accurate estimate of VaR can be a computationally expensive process. The most advanced approaches involve Monte Carlo simulations , a class of algorithms that seek to compute quantities through repeated random sampling.Read full article from Estimating Financial Risk with Apache Spark | Cloudera Engineering Blog
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