On Estimation of Volatility of Financial Time Series for Pricing Derivatives

Estimation of volatility of financial time series plays a crucial role in pricing derivatives. Volatility is often estimated from historical data; however, it is well known that volatility varies in time. We propose a method to choose a suitable length of historical data to estimate contemporary volatility. The method is based on adaptation of a procedure used in statistical quality control - a hypothesis, that data contains a changepoint of volatility, is tested and if the test gives a positive answer, the changepoint is estimated. Then, a period of data where no changepoint is statistically significant is used to estimate contemporary volatility. The approach is illustrated on an analysis of CZK/EUR exchange rates.