2005/01/26 by Jaume Masoliver, Josep Perelló, Josep Perello · 61 citations
Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Autocorrelation #Complex Systems and Time Series Analysis #Constant elasticity of variance model #Econometrics #Economics #Exponential function #Finance #Financial Risk and Volatility Modeling #Financial economics #Financial market #Kurtosis #Leverage (statistics) #Mathematics #Ornstein–Uhlenbeck process #Physics #SABR volatility model #Skewness #Statistical physics #Statistics #Stochastic modelling #Stochastic process #Stochastic processes and financial applications #Stochastic volatility #Volatility (finance) #cond-mat.other #physics.soc-ph #q-fin.ST
paper · pdf · doi:10.1080/14697680600727547
published in Quantitative Finance 6(5), 423-433 (Taylor & Francis) · 24 pages, 9 colored figures, Workshop Volatility of Financial Markets (Leiden 18-29 October 2004)
arxiv created 2005/01/26 · openalex publication_date 2006/09/21 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We study the exponential Ornstein–Uhlenbeck stochastic volatility model and observe that the model shows a multiscale behaviour in the volatility autocorrelation. It also exhibits a leverage correlation and a probability profile for the stationary volatility which are consistent with market observations. All these features make the model quite appealing since it appears to be more complete than other stochastic volatility models also based on a two-dimensional diffusion. We finally present an approximate solution for the return probability density designed to capture the kurtosis and skewness effects.