Quantitative Finance Stack Exchange is a question and answer site for finance professionals and academics. Join them; it only takes a minute:

Sign up
Here's how it works:
  1. Anybody can ask a question
  2. Anybody can answer
  3. The best answers are voted up and rise to the top

The root mean squared error (RMSE) is considered by some to be the best measure of how good a variance estimate is. You often see it quoted as:

$RMSE=\sqrt{\frac{1}{n}\sum_{i=1}^n(\hat{\sigma_i} - \sigma_i)^2}$

Where $\hat{\sigma}$ is the estimate of the volatility while $\sigma$ is the actual volatility.

My question is: what is $\sigma$ in this case? Suppose that $\hat{\sigma}$ is the prior day's realized volatility (i.e. $RV = \sum_{t=0}^N r_t$ where $r_t$ is the 5-minute return), is the actual volatility just the next day's absolute return?

share|improve this question

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.

Browse other questions tagged or ask your own question.