Forecasting Multifractal Volatility.

This paper develops analytical methods to forecast the distribution of future returns for a new continuous-time process, the Poisson multi-fractal. The process captures the thick tails, volatility persistence and moment scaling exhibited by many financial time series. It can be interpreted as a stochastic volatility model with multiple frequencies and a Markov latent state. We assume for simplicity that the forecaster knows the true generating process with certainty but only observes past returns.