Abstract—In this work, assuming as a model the Multifractional Processes with Random Exponent (MPRE), we propose a simulation algorithm able to replicate financial time series, specifically pertaining to the FX market. We show how, properly choosing the functional parameter of the MPRE, the simulated series fit with significant accuracy the actual ones. It is worthwhile to underline that the sole knowledge of the functional parameter ensures by itself that the surrogates succeed in replicating the empirical data. The results can be used in scenario analysis as well as in forecasting.
Index Terms—Financial modeling, goodness of fit, multifractional processes, simulation.
S. B. Author is with the Department of Economics and Law, University of Cassino, (FR), Italy, (e-mail: sbianchi@eco.unicas.it).
A. P. Author is with the Department of Economics and Law, University of Cassino, (FR), Italy, (e-mail: a.pantanella@eco.unicas.it).
A. P. Author is with the Department of Economics and Law, University of Cassino, (FR), Italy, (e-mail: pianese@unicas.it).
Cite: Sergio Bianchi, Alexandre Pantanella, and Augusto Pianese, "Modeling and Simulation of Currency Exchange Rate Using Multifractional Process with Random Exponent," International Journal of Modeling and Optimization vol. 2, no. 3, pp. 309-314, 2012.
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