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METHOD OF MOMENTS ESTIMATION FOR LÉVY-DRIVEN ORNSTEIN–UHLENBECK STOCHASTIC VOLATILITY MODELS - MaRDI portal

METHOD OF MOMENTS ESTIMATION FOR LÉVY-DRIVEN ORNSTEIN–UHLENBECK STOCHASTIC VOLATILITY MODELS (Q5051950)

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scientific article; zbMATH DE number 7620610

Language	Label	Description	Also known as
English	METHOD OF MOMENTS ESTIMATION FOR LÉVY-DRIVEN ORNSTEIN–UHLENBECK STOCHASTIC VOLATILITY MODELS	scientific article; zbMATH DE number 7620610

Statements

scholarly article

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METHOD OF MOMENTS ESTIMATION FOR LÉVY-DRIVEN ORNSTEIN–UHLENBECK STOCHASTIC VOLATILITY MODELS (English)

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Probability in the Engineering and Informational Sciences

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publication date

18 November 2022

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zbMATH Keywords

consistency and asymptotic normality

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method of moments

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parameter estimation

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stochastic volatility model

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1017/s0269964820000315

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Efficient method of moments estimation of a stochastic volatility model: A Monte Carlo study

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Computational techniques for econometrics and economic analysis

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Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics

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On the system of difference equations \(x_n=c_ny_{n-3}/(a_n+b_ny_{n-1}x_{n-2}y_{n-3})\),\(y_n=\gamma_nx_{n-3}/(\alpha_n+\beta_nx_{n-1}y_{n-2}x_{n-3})\)

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Time series: theory and methods.

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MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS

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Simulated Moments Estimation of Markov Models of Asset Prices

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Bayesian estimation of stochastic volatility models based on OU processes with marginal gamma law

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Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility

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Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes

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Multivariate Stochastic Variance Models

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Method of moment estimation in the COGARCH(1,1) model

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A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options

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Some Limit Theorems for Stationary Processes

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Inference for Lévy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo

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On multidimensional Ornstein-Uhlenbeck processes driven by a general Lévy process

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Gradient-based simulated maximum likelihood estimation for Lévy-driven Ornstein–Uhlenbeck stochastic volatility models

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Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions

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Bayesian Inference for Non-Gaussian Ornstein–Uhlenbeck Stochastic Volatility Processes

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Quasi-maximum likelihood estimation of stochastic volatility models

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Moment estimators for the parameters of Ornstein-Uhlenbeck processes driven by compound Poisson processes

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Identifiers

10.1017/S0269964820000315

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:5051950

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