Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes

DOI10.1016/j.csda.2011.01.014zbMath1255.62322OpenAlexW2052870242MaRDI QIDQ1927109

Arvid Raknerud, Øivind Skare

Publication date: 30 December 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.01.014

zbMATH Keywords

Ornstein-Uhlenbeck processquasi-likelihood estimationasymptotic variancesimulation study\texttt{R}stochastic volatility modelexchange rate data

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Applications of statistics to actuarial sciences and financial mathematics (62P05) Markov processes: estimation; hidden Markov models (62M05) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70)

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Uses Software

• R
• Armadillo
• RcppArmadillo
• BRENT

Cites Work

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• Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility
• Financial modeling under non-Gaussian distributions.
• Simulation of Lévy-driven Ornstein-Uhlenbeck processes with given marginal distribution
• Empirical modeling of exchange rate dynamics
• Estimating continuous-time stochastic volatility models of the short-term interest rate
• On the Lévy measure of the lognormal and the logCauchy distributions
• Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes
• Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics
• Temporal Aggregation of Garch Processes
• Handbook of Financial Time Series
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Multivariate Stochastic Variance Models
• Estimating stochastic differential equations efficiently by minimum chi-squared
• Estimating Functions in Indirect Inference
• Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
• The Distribution of Realized Exchange Rate Volatility
• Option Pricing in Stochastic Volatility Models of the Ornstein‐Uhlenbeck type
• Integrated OU Processes and Non‐Gaussian OU‐based Stochastic Volatility Models
• State Space and Unobserved Component Models
• Control variates for variance reduction in indirect inference: Interest rate models in continuous time

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