Inference procedures for stable-Paretian stochastic volatility models
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Publication:1931045
DOI10.1016/j.mcm.2011.09.044zbMath1255.91308OpenAlexW2038978888MaRDI QIDQ1931045
Emanuele Taufer, Simos G. Meintanis
Publication date: 24 January 2013
Published in: Mathematical and Computer Modelling (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.mcm.2011.09.044
estimationcharacteristic functionstable-Paretian distributionfirst order stationary auto-regressive processes
Applications of statistics to actuarial sciences and financial mathematics (62P05) Stochastic models in economics (91B70) Stable stochastic processes (60G52)
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Cites Work
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- Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility
- Indirect estimation of \(\alpha \)-stable stochastic volatility models
- Simulation of Lévy-driven Ornstein-Uhlenbeck processes with given marginal distribution
- Stochastic volatility modelling in continuous time with general marginal distributions: inference, prediction and model selection
- On a continuous analogue of the stochastic difference equation \(X_ n\) = rho X//(n-1) + \(B_ n\).
- On multidimensional Ornstein-Uhlenbeck processes driven by a general Lévy process
- Characteristic function estimation of Ornstein-Uhlenbeck-based stochastic volatility models
- Long-memory stable {O}rnstein-{U}hlenbeck processes
- On the relation between GARCH and stable processes
- Characteristic function estimation of non-Gaussian Ornstein-Uhlenbeck processes
- Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics
- Empirical Characteristic Function Estimation and Its Applications
- An efficiency result for the empirical characteristic function in stationary time-series models
- On statistical transform methods and their efficiency
- Regression-Type Estimation of the Parameters of Stable Laws
- On Some Fourier Methods for Inference
- Some stationary processes in discrete and continuous time
- Theory & Methods: Estimation of the Stochastic Volatility Model by the Empirical Characteristic Function Method
- Bayesian Inference for Non-Gaussian Ornstein–Uhlenbeck Stochastic Volatility Processes
- Simulation of Estimates Using the Empirical Characteristic Function
- MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS
- EMPIRICAL CHARACTERISTIC FUNCTION IN TIME SERIES ESTIMATION
- Integrated OU Processes and Non‐Gaussian OU‐based Stochastic Volatility Models
- A PARAMETRIC BOOTSTRAP FOR HEAVY-TAILED DISTRIBUTIONS
- Short and Long Memory Fractional Ornstein–Uhlenbeck α-Stable Processes
- Simulation and inference for stochastic volatility models driven by Levy processes
