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Methods for estimating discrete-time stochastic volatility models

Liu, Xiaobin - In: Financial econometrics : theory and applications, (pp. 271-305). 2025

Persistent link: https://www.econbiz.de/10015426500

Multivariate stochastic volatility with co-heteroscedasticity

Chan, Joshua; Doucet, Arnaud; León-González, Roberto; … - In: Studies in nonlinear dynamics and econometrics : SNDE ; … 29 (2025) 3, pp. 265-300

Persistent link: https://www.econbiz.de/10015438126

Multivariate Stochastic Volatility Models with Correlated Errors

Chan, David X. - 2008

stochastic volatility model. Since the number of parameters in the joint correlation matrix of the return and volatility errors …

Persistent link: https://www.econbiz.de/10012727256

Parameter learning and change detection using a particle filter with accelerated adaptation

Gellert, Karol; Schlögl, Erik - In: Risks : open access journal 9 (2021) 12, pp. 1-18

shifts and stochastic volatility. The filter adapts to regime shifts extremely rapidly and delivers a clear heuristic for … distinguishing between regime shifts and stochastic volatility, even though the model dynamics assumed by the filter exhibit neither …

Persistent link: https://www.econbiz.de/10012794245

Empirical analysis of affine versus nonaffine variance specifications in jump-diffusion models for equity indices

Ignatieva, Ekaterina; Rodrigues, Paulo Jorge Maurício; … - In: Journal of business & economic statistics : JBES ; a … 33 (2015) 1, pp. 68-75

Persistent link: https://www.econbiz.de/10011389699

Dynamic price jumps : the performance of high frequency tests and measures, and the robustness of inference

Maneesoonthorn, Worapree; Martin, Gael M.; Forbes, … - 2018

Persistent link: https://www.econbiz.de/10012583570

Markov-Chain Approximation and Estimation of Nonlinear, Non-Gaussian State Space Models

Farmer, Leland - 2014

I develop a new method for approximating and estimating nonlinear, non-Gaussian state space models. I show that any such model can be well approximated by a discrete-state Markov process and estimated using techniques developed in Hamilton (1989). Through Monte Carlo simulations, I demonstrate...

Persistent link: https://www.econbiz.de/10013048908

Using a mean changing stochastic processes exit-entry model for stock market longshort prediction

Lleo, Sébastien; Zhitlukhin, M. V.; Ziemba, William T. - 2021

Persistent link: https://www.econbiz.de/10012534838

Option pricing model biases : Bayesian and Markov Chain Monte Carlo regression analysis

Mozumder, Sharif; Choudhry, Taufiq; Dempsey, Michael - In: Computational economics 57 (2021) 4, pp. 1287-1305

Persistent link: https://www.econbiz.de/10012543312

Volatility estimation and jump detection for drift-diffusion processes

Laurent, Sébastien; Shi, Shuping - In: Journal of econometrics 217 (2020) 2, pp. 259-290

Persistent link: https://www.econbiz.de/10012482762