Hilbert-Huang Based Volatility Forecasts for High Frequency Data and Simulated Option Markets

In this paper we introduce a new way to estimate the spot volatility of high frequency foreign exchange data using the Hilbert-Huang Transform. We also propose and test a consistent spot volatility estimate in the presence of microstructure noise. The problem of assessing the validity of latent variable estimates is overcome by setting up a virtual options trading market in which competing volatility forecasts buy and sell straddle options to one another using real high frequency foreign exchange data