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Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …
Persistent link: https://www.econbiz.de/10010324972
Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative...
Persistent link: https://www.econbiz.de/10011605015
Any measure of unobserved inflation uncertainty relies on specific assumptions which are most likely not fulfilled completely. This calls into question whether an individual measure delivers a reliable signal. To reduce idiosyncratic measurement error, we propose using common information...
Persistent link: https://www.econbiz.de/10010312179
The paper develops a novel realized stochastic volatility model of asset returns and realized volatility that incorporates general asymmetry and long memory (hereafter the RSV-GALM model). The contribution of the paper ties in with Robert Basmann's seminal work in terms of the estimation of...
Persistent link: https://www.econbiz.de/10011636455
We investigate whether and to what extent multiple encompassing tests may help determine weights for forecast averaging in a standard vector autoregressive setting. To this end we consider a new test-based procedure, which assigns non-zero weights to candidate models that add information not...
Persistent link: https://www.econbiz.de/10010294025
Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML) estimation with variance … volatility equation and corresponding value-at-risk predictions. We find that most GARCH coefficients and associated predictions …
Persistent link: https://www.econbiz.de/10011410634
Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management.The recent availability of high-frequency data allows for refined methods in this field.In particular, more precise measures for the daily or lower frequency volatility can be...
Persistent link: https://www.econbiz.de/10003727640
Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management.The recent availability of high-frequency data allows for refined methods in this field.In particular, more precise measures for the daily or lower frequency volatility can be...
Persistent link: https://www.econbiz.de/10010274148
Persistent link: https://www.econbiz.de/10014303987
In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...
Persistent link: https://www.econbiz.de/10010324578