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Modelling stochastic volatility with leverage and jumps : a simulated maximum likelihood approach via particle filtering.

Malik, Sheheryar (contributor); Pitt, Michael K. (contributor) - 2009

In this paper we provide a unifed methodology in order to conduct likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...

Persistent link: https://www.econbiz.de/10003866080

Modelling Stochastic Volatility with Leverage and Jumps : A Simulated Maximum Likelihood Approach via Particle Filtering

Malik, Sheheryar; Pitt, Michael K. - 2011

In this paper we provide a unified methodology for conducting likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...

Persistent link: https://www.econbiz.de/10014185810

The stochastic volatility in mean model

Koopman, Siem Jan; Hol Uspensky, Eugenie - 2000

(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable …

Persistent link: https://www.econbiz.de/10011303314

Numerically accelerated importance sampling for nonlinear non-Gaussian state space models

Koopman, Siem Jan; Lucas, André; Scharth, Marcel - 2012

methods. Our methodology explores the idea that only a small part of the likelihood evaluation problem requires simulation. We …-off encountered by other sampling methods. An elaborate simulation study and an empirical application for U.S. stock returns reveal …

Persistent link: https://www.econbiz.de/10011386179

Modelling stochastic volatility with leverage and jumps : a simulated maximum likelihood approach via particle filtering

Malik, Sheheryar; Pitt, Michael K. - 2010

Persistent link: https://www.econbiz.de/10009382185

Hawkes-based models for high frequency financial data

Nyström, Kaj; Zhang, Changyong - In: Journal of the Operational Research Society 73 (2022) 10, pp. 2168-2185

Persistent link: https://www.econbiz.de/10013532430

Intraday power trading : toward an arms race in weather forecasting?

Kuppelwieser, Thomas; Wozabal, David - In: OR spectrum : quantitative approaches in management 45 (2023) 1, pp. 57-83

Persistent link: https://www.econbiz.de/10014226371

Estimation of the stochastic volatility models by simulated maximum likelihood : C++ code

Daníelsson, Jón (contributor) - In: Studies in nonlinear dynamics and econometrics : SNDE ; … 1 (1996) 1, pp. 39-34

Persistent link: https://www.econbiz.de/10001769603

On importance sampling for state space models

Jungbacker, Borus; Koopman, Siem Jan - 2005

and smoother and the simulation smoother which do not rely on a linear Gaussian observation equation. Furthermore, results …

Persistent link: https://www.econbiz.de/10011348357

Numerically accelerated importance sampling for nonlinear non-Gaussian state-space models

Koopman, Siem Jan; Lucas, André; Scharth, Marcel - In: Journal of business & economic statistics : JBES ; a … 33 (2015) 1, pp. 114-127

Persistent link: https://www.econbiz.de/10011389921

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