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Discrete-time stochastic volatility models and MCMC-based statistical inference
Hautsch, Nikolaus (contributor); Ou, Yangguoyi (contributor) - 2008
In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and … indices and foreign exchange rates. -- Stochastic volatility ; Markov chain Monte Carlo ; Metropolis-Hastings algorithm Jump …
Persistent link: https://www.econbiz.de/10003770817
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Inference for adaptive time series models : stochastic volatility and conditionally Gaussian state space form
Bos, Charles S.; Shephard, Neil G. - 2004
volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …
Persistent link: https://www.econbiz.de/10011334849
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Modeling and Forecasting Realized Range Volatility
Caporin, Massimiliano - 2011
In this paper, we estimate, model and forecast Realized Range Volatility, a new realized measure and estimator of the …-known stylized effects present in financial data. We consider an HAR model with asymmetric effects with respect to the volatility and …
Persistent link: https://www.econbiz.de/10013130487
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Forecasting Realized Volatility : Does Anything Beat Linear Models?
Branco, Rafael; Rubesam, Alexandre; Zevallos, Mauricio - 2022
volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a …
Persistent link: https://www.econbiz.de/10014076641
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Innovation efficiency in European high-tech industries : evidence from a Bayesian stochastic frontier approach
Haschka, Rouven E.; Herwartz, Helmut - In: Research policy : policy, management and economic … 49 (2020) 8, pp. 1-20
Persistent link: https://www.econbiz.de/10012583887
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Extreme value models in a conditional duration intensity framework
Herrera, Rodrigo; Schipp, Bernhard - 2011
capability to capture the short-term behaviour of extremes without involving an arbitrary stochastic volatility model or a … from the German stock market index DAX. -- Extreme value theory ; autoregressive conditional duration ; value at risk …
Persistent link: https://www.econbiz.de/10009009682
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A Bayesian semiparametric analysis of ARCH models
Kozumi, Hideo; Polasek, Wolfgang - In: Optimization, dynamics, and economic analysis : essays …, (pp. 389-400). 2000
Persistent link: https://www.econbiz.de/10001497195
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MEM or/and LogARMA : which model for realized volatility?
Anatolyev, Stanislav - 2022
such as realized volatility. One is a class of multiplicative error models (MEM), where the conditional mean is modelled … terms of in-sample fit and out-of-sample predictability, using real data on realized volatility. The forecast combination …
Persistent link: https://www.econbiz.de/10013405770
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Cycles and long-range behaviour in the European stock markets
Caporale, Guglielmo Maria; Gil-Alaña, Luis A.; Poza, Carlos - 2019
This paper uses a modelling framework which includes two singularities (or poles) in the spectral density function, one corresponding to the long-run (zero) frequency and the other to the cyclical (non-zero) frequency. The adopted specification is very general, since it allows for fractional...
Persistent link: https://www.econbiz.de/10012123055
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Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis
Hafner, Christian M.; Herwartz, Helmut - 1999
prices caused by stochastic volatility. -- option pricing ; autoregression ; heteroskedasticity ; GARCH ; leverage effect …
Persistent link: https://www.econbiz.de/10009580460