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Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models
Barra, Istvan - 2016
evidence for stochastic intensity and stochastic volatility models based on Ornstein-Uhlenbeck processes. For our empirical …
Persistent link: https://www.econbiz.de/10013005987
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Bayesian analysis of intraday stochastic volatility models of high-frequency stock returns with skew heavy-tailed errors
Nakakita, Makoto; Nakatsuma, Teruo - In: Journal of risk and financial management : JRFM 14 (2021) 4, pp. 1-29
Intraday high-frequency data of stock returns exhibit not only typical characteristics (e.g., volatility clustering and … the leverage effect) but also a cyclical pattern of return volatility that is known as intraday seasonality. In this paper …, we extend the stochastic volatility (SV) model for application with such intraday high-frequency data and develop an …
Persistent link: https://www.econbiz.de/10012520275
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Evolutionary sequential Monte Carlo samplers for change-point models
Dufays, Arnaud - In: Econometrics : open access journal 4 (2016) 1, pp. 1-33
Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. However, the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC) methods. Not only do SMC...
Persistent link: https://www.econbiz.de/10011504888
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Evolutionary Sequential Monte Carlo Samplers for Change-Point Models
Dufays, Arnaud - 2018
Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. Nevertheless the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC) methods. Not only SMC...
Persistent link: https://www.econbiz.de/10012936969
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The time-varying effects of permanent and transistory shocks to real output
Keating, John William; Valcarcel, Victor J. - In: Macroeconomic dynamics 19 (2015) 3, pp. 477-507
Persistent link: https://www.econbiz.de/10011308634
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Equity index variance : evidence from flexible parametric jump-diffusion models
Kaeck, Andreas; Rodrigues, Paulo Jorge Maurício; … - In: Journal of banking & finance 83 (2017), pp. 85-103
Persistent link: https://www.econbiz.de/10011816827
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Bayesian analysis of moving average stochastic volatility models : modeling in-mean effects and leverage for financial time series
Dimitrakopoulos, Stefanos; Kolossiatis, Michalis - In: Econometric reviews 39 (2020) 4, pp. 319-343
Persistent link: https://www.econbiz.de/10012181420
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Chapter 15. Forecasting with Bayesian Vector Autoregression
Karlsson, Sune - 2013
This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and special attention is given to the implementation of the...
Persistent link: https://www.econbiz.de/10014025233
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Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility
Jensen, Mark J. - 2015
Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market … found with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a …, stochastic volatility (SV-FIAR) model. Joint estimates of the autoregressive and fractional differencing parameters of volatility …
Persistent link: https://www.econbiz.de/10011382237
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Bayesian estimation of asymmetric jump-diffusion processes
Frame, Samuel J.; Ramezani, Cyrus A. - In: Annals of financial economics 9 (2014) 3, pp. 1-29
Persistent link: https://www.econbiz.de/10010512597