Risk measures have been around for decades and remain a fundamental tool of many investors and large financial institutions. Why? Because they distill a lot of information down into a single number. They have significant pitfalls, but they are by far the simplest tool in a quant's toolbox.
The development of risk measures coincided with the theory of portfolio optimization. In Harry Markowitz's Nobel winning research, he proposed a measure that is still widely used today. He computed the portfolio's expected return over its variance. This led to a key insight: investors can reduce their exposure to a single asset by diversifying their portfolio.
Our measure is very similar to Markowitz's mean-variance model, but simply takes the average annual percent return over the average annual correlation coefficient. We omit variance and focus purely on correlation.