Multiscale Volatility Analysis for Noisy High-Frequency Prices

Oregon Convention Center 

We discuss a multiscale volatility analysis of high-frequency intraday prices. Our multiscale framework includes a fractional Brownian motion and microstructure noise as the building blocks. The proposed noisy fractional Brownian motion model is shown to possess a variety of volatility behaviors suitable for intraday price processes. Algorithms for numerical estimation from time series observations are presented with a new Hurst exponent estimator proposed for the noisy fractional Brownian motion model. Using real-world high-frequency price data for a collection of US stocks and ETFs, we estimate the parameters in the noisy fractional Brownian motion and illustrate how the volatility varies over different timescales. The Hurst exponent and noise level exhibit an intraday pattern whereby the noise ratio tends to be higher near market close.