Sophisticated trading organizations rarely depend on a secret algorithm alone. Their advantage is often the discipline wrapped around prediction. Banks, broker-dealers, asset managers and professional market makers assume that forecasts can fail, data can be wrong, and software can eventually meet c

Early in 2012, a portfolio in JPMorgan Chase’s Chief Investment Office was running over its risk limits. Then the bank adopted a new value-at-risk model, and the problem seemed to go away. Under the new model, the portfolio’s reported risk fell by roughly half. Months afterward, the t