Weighted-indexed semi-Markov models for modeling financial returns

In this paper we propose a new stochastic model based on a generalization of semi-Markov chains to study the high frequency price dynamics of traded stocks. We assume that the financial returns are described by a weighted indexed semi-Markov chain model. We show, through Monte Carlo simulations, that the model is able to reproduce important stylized facts of financial time series as the first passage time distributions and the persistence of volatility. The model is applied to data from Italian and German stock market from first of January 2007 until end of December 2010.Comment: arXiv admin note: substantial text overlap with arXiv:1109.425

Wind speed and energy forecasting at different time scales: a non parametric approach

The prediction of wind speed is one of the most important aspects when dealing with renewable energy. In this paper we show a new nonparametric model, based on semi-Markov chains, to predict wind speed and the energy produced by a commercial blade. Particularly, we use an indexed semi-Markov model, that reproduces accurately the statistical behavior of wind speed. The model is used to forecast future wind speed and the energy produced through a 10 kW Aircon wind turbine. We forecast one step ahead and for different time scales. In order to check the main features of the model we show, as indicator of goodness, the root mean square error between real data and predicted ones. We compare our forecasting results with those of a persistence model and of an autoregressive model

Performability analysis of the second order semi-Markov chains: an application to wind energy production

In this paper a general second order semi-Markov reward model is presented. Equations for the higher order moments of the reward process are presented for the first time and applied to wind energy production. The application is executed by considering a database, freely available from the web, that includes wind speed data taken from L.S.I. - Lastem station (Italy) and sampled every 10 minutes. We compute the expectation, the variance, the skewness and the kurtosis of the total energy produced by using the commercial blade Aircon HAWT - 10 kW