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Estimation of dynamic panel data models with stochastic volatility using particle filters

Xu, Wen - In: Econometrics : open access journal 4 (2016) 4, pp. 1-13

Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel...

Persistent link: https://www.econbiz.de/10011650493

Estimating correlated jumps and stochastic volatilities

Witzany, Jiří - In: Prague economic papers : a bimonthly journal of … 22 (2013) 2, pp. 251-283

Persistent link: https://www.econbiz.de/10010226453

Regime-switching stochastic volatility model : estimation and calibration to VIX options

Goutte, Stéphane; Ismail, Amine; Pham, Huyên - In: Applied mathematical finance 24 (2017) 1/2, pp. 38-75

Persistent link: https://www.econbiz.de/10011746993

Performance comparison of alternative stochastic volatility models and its determinants in energy futures : COVID-19 and Russia-Ukraine conflict features

Fernandes, Mário Correia; Dias, José Carlos; Nunes, … - In: The journal of futures markets 44 (2024) 3, pp. 343-383

Persistent link: https://www.econbiz.de/10014475488

Inference for adaptive time series models : stochastic volatility and conditionally Gaussian state space form

Bos, Charles S.; Shephard, Neil G. - 2004

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...

Persistent link: https://www.econbiz.de/10011334849

Bayesian dynamic modeling of high-frequency integer price changes

Barra, Istvan; Koopman, Siem Jan - 2016

estimation procedures. Our key interest is the extraction of intra-day volatility patterns from high-frequency integer price … each model we develop a Markov chain Monte Carlo estimation method that takes advantage of auxiliary mixture …

Persistent link: https://www.econbiz.de/10011456723

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

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

efficient, facilitates parameter estimation for models with high-dimensional state vectors, and overcomes a bias-variance trade …

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

Sample path generation of the stochastic volatility CGMY process and its application to path-dependent option pricing

Kim, Young Shin - In: Journal of risk and financial management : JRFM 14 (2021) 2/77, pp. 1-18

This paper proposes the sample path generation method for the stochastic volatility version of the CGMY process. We present the Monte-Carlo method for European and American option pricing with the sample path generation and calibrate model parameters to the American style S&P 100 index options...

Persistent link: https://www.econbiz.de/10012484130

ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models

Creel, Michael; Kristensen, Dennis - School of Economics and Management, University of Aarhus - 2014

We develop novel methods for estimation and filtering of continuous-time models with stochastic volatility and jumps …. We show how the methods can incorporate intra-daily information to improve on the estimation and filtering. In particular … employed in the estimation of a flexible stochastic volatility model for the dynamics of the S&P 500 equity index. We find …

Persistent link: https://www.econbiz.de/10010892068

Robust Sign-Based and Hodges-Lehmann Estimators in Linear Median Regressions with Heterogenous Serially Dependent Errors

Coudin, Elise; Dufour, Jean-Marie - Centre Interuniversitaire de Recherche en Analyse des … - 2011

We propose estimators for the parameters of a linear median regression without any assumption on the shape of the error distribution including no condition on the existence of moments allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous distributions, and very...

Persistent link: https://www.econbiz.de/10008855591