Volatility Estimation on the Basis of Price Intensities

This paper investigates the use of price intensities, i.e. the time between price changes of a given size, to estimate volatilities based on high-frequency data. We interpret the conditional probability for the occurrence of a price event within a certain time horizon as a risk measure which allows us to obtain an estimator of the conditional volatility per time. To consider censoring effects caused by nontrading periods, we use a proportional hazard model. Seasonalities are taken into account by including regressors based on a flexible Fourier form capturing intraday and time-to-maturity seasonalities. Testing for serial correlation and controlling for unobservable heterogeneity permits us to check for misspecification on different aggregation levels. Empirical results are based on intraday transaction data of Bund future trading at the LIFFE, London