A Fractionally Integrated Wishart Stochastic Volatility Model

Arbeitspapier

There has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous timefractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of the FIWSV model in order to obtain a closed form expression of moments. We conduct a two-step procedure, namely estimating the parameter of fractional integration via log-periodgram regression in the first step, and estimating the remaining parameters via the generalized method of moments in the second step. Monte Carlo results for the procedure shows reasonable performances in finite samples. The empirical results for the bivariate data of the S&P 500 and FTSE100 indexes show that the data favor the new FIWSV processes rather than one-factor and two-factor models of Wishart autoregressive processes for the covariance structure.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Tinbergen Institute Discussion Paper ; No. 13-025/III

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Model Construction and Estimation ; Contingent Pricing; Futures Pricing; option pricing
• Subject: Diffusion process ; Multivariate stochastic volatility ; Long memory ; Fractional Brownian motion ; Generalized method of moments ; Stochastischer Prozess ; Volatilität ; Momentenmethode ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Asai, Manabu ; McAleer, Michael
• Event: Veröffentlichung
• (who): Tinbergen Institute
• (where): Amsterdam and Rotterdam
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/87261
• Last update: 10.03.2025, 11:42 AM CET