Integrated OU Processes and Non‐Gaussian OU‐based Stochastic Volatility Models
Copyright policy )Integrated OU Processes and Non‐Gaussian OU‐based Stochastic Volatility Models
Abstract. In this paper, we study the detailed distributional properties of integrated non‐Gaussian Ornstein–Uhlenbeck (intOU) processes. Both exact and approximate results are given. We emphasize the study of the tail behaviour of the intOU process. Our results have many potential applications in financial economics, as OU processes are used as models of instantaneous variance in stochastic volatility (SV) models. In this case, an intOU process can be regarded as a model of integrated variance. Hence, the tail behaviour of the intOU process will determine the tail behaviour of returns generated by SV models.
- University of Oxford United Kingdom
- Aarhus University Denmark
- Nuffield College United Kingdom
background driving Lévy process, Lévy process, Economics, cumulant function, Lévy density, Processes with independent increments; Lévy processes, econometrics, Stochastic ordinary differential equations (aspects of stochastic analysis), Derivative securities (option pricing, hedging, etc.), Background driving Levy process; Chronometer; Co-break; Econometrics; Intergrated volatility; Kumulant function; Levy density; Levy process; Option pricing; OU processes; Stochastic volatility, Stationary stochastic processes, integrated variance, Econometrics, Ornstein-Uhlenbeck process, stochastic volatility, Applications of statistics to economics, chronometer, option pricing, Statistical methods; risk measures
background driving Lévy process, Lévy process, Economics, cumulant function, Lévy density, Processes with independent increments; Lévy processes, econometrics, Stochastic ordinary differential equations (aspects of stochastic analysis), Derivative securities (option pricing, hedging, etc.), Background driving Levy process; Chronometer; Co-break; Econometrics; Intergrated volatility; Kumulant function; Levy density; Levy process; Option pricing; OU processes; Stochastic volatility, Stationary stochastic processes, integrated variance, Econometrics, Ornstein-Uhlenbeck process, stochastic volatility, Applications of statistics to economics, chronometer, option pricing, Statistical methods; risk measures
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