We propose a simple stochastic volatility model which is analytically tractable, very easy to simulate, and which captures some relevant stylized facts of financial assets, including scaling properties. In particular, the model displays a crossover in the log-return distribution from power-law tails (small time) to a Gaussian behavior (large time), slow decay in the volatility autocorrelation, and multiscaling of moments. Despite its few parameters, the model is able to fit several key features of the time series of financial indexes, such as the Dow Jones Industrial Average, with remarkable accuracy

Andreoli, A., Caravenna, F., Dai Pra, P., Posta, G. (2012). Scaling and multiscaling in financial series: a simple model. ADVANCES IN APPLIED PROBABILITY, 44(4), 1018-1051 [10.1239/aap/1354716588].

Scaling and multiscaling in financial series: a simple model

CARAVENNA, FRANCESCO;
2012

Abstract

We propose a simple stochastic volatility model which is analytically tractable, very easy to simulate, and which captures some relevant stylized facts of financial assets, including scaling properties. In particular, the model displays a crossover in the log-return distribution from power-law tails (small time) to a Gaussian behavior (large time), slow decay in the volatility autocorrelation, and multiscaling of moments. Despite its few parameters, the model is able to fit several key features of the time series of financial indexes, such as the Dow Jones Industrial Average, with remarkable accuracy
Articolo in rivista - Articolo scientifico
Financial index; time series; scaling; multiscaling; Brownian motion; stochastic volatility; heavy tail; multifractal model
English
2012
44
4
1018
1051
none
Andreoli, A., Caravenna, F., Dai Pra, P., Posta, G. (2012). Scaling and multiscaling in financial series: a simple model. ADVANCES IN APPLIED PROBABILITY, 44(4), 1018-1051 [10.1239/aap/1354716588].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/44606
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