We live in the age of the quant. Mathematics drives an increasingly large number of investment portfolios. In many ways, this is an improvement over the less evidence-based approaches that often relied on instinct and gut feeling. But as we learned during the financial crisis, models are imperfect and they can and do break down.
There are many reasons for this: noisy data series are subject to revision. Sometimes the assumptions underlying models are wrong. Occasionally, time simply moves forward, and events occur that are unanticipated by a model’s designer.