Modeling financial asset returns with shot noise processes

We introduce a new class of continuous time processes for modeling the rate of returns of financial assets. The statistical characterization is based on the so-called shot noise processes. The probabilistic structure of the shot noise process provides a very realistic framework for asset returns modeling of the stock price processes. Our class of processes exhibits the natural phenomena well known in empirical financial studies: 1. t-tail distribution function for the asset returns, pendence of the returns, nstationarity in time. ial asset returns in new emerging markets such as those of Eastern European countries exhibit a highly volatile behavior. Statistical investigations of the unconditional distribution of returns of stocks, commodities, exchange rates, etc., show extremely heavy tails and steep peaks around the expectation. We use a class of shot noise processes with Poissonian times and Brownian magnitudes for modeling this phenomenon.