Challet, Damien and Peirano, Pier Paolo (2008): The Ups and Downs of Modeling Financial Time Series with Wiener Process Mixtures.
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Abstract
Starting from inhomogeneous time scaling and linear decorrelation between successive price returns, Baldovin and Stella recently proposed a way to build a model describing the time evolution of a financial index. We first make it fully explicit by using Student distributions instead of power lawtruncated Lévy distributions; we also show that the analytic tractability of the model extends to the larger class of symmetric generalized hyperbolic distributions and provide a full computation of their multivariate characteristic functions; more generally, the stochastic processes arising in this framework are representable as mixtures of Wiener processes. The Baldovin and Stella model, while mimicking well volatility relaxation phenomena such as the Omori law, fails to reproduce other stylized facts such as the leverage effect or some time reversal asymmetries. We discuss how to modify the dynamics of this process in order to reproduce real data more accurately.
Item Type:  MPRA Paper 

Original Title:  The Ups and Downs of Modeling Financial Time Series with Wiener Process Mixtures 
Language:  English 
Keywords:  Stylized Facts; Student Processes; Hyperbolic Distributions; Wiener Process Mixtures 
Subjects:  C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C40  General G  Financial Economics > G1  General Financial Markets > G10  General 
Item ID:  16358 
Depositing User:  Pier Paolo Peirano 
Date Deposited:  27 Jul 2009 07:10 
Last Modified:  04 Oct 2019 16:24 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/16358 
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The ups and downs of the renormalization group applied to financial time series. (deposited 30 Jul 2008 10:30)
 The Ups and Downs of Modeling Financial Time Series with Wiener Process Mixtures. (deposited 27 Jul 2009 07:10) [Currently Displayed]