Towards a Bayesian Method to Estimate Future Realized Volatility

Lucas Krishan Ryan Hornby (Vassar College)

Estimation of ex-ante or future realized volatility is crucial to the financial industry. In this paper we explore the use of a Bayesian method to estimate the implied volatility on stock options which in turn will allow us to estimate the future realized volatility on the underlying. We find that this method is more accurate in estimating the implied volatility than estimates using historical volatility. Thus this method might be helpful in estimating ex-ante volatility for the underlying stock and will therefore be useful in pricing derivatives which does not have any implied volatility data on them.