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The economic valuation of variance forecasts: An artificial option market approach
Parrák, Radovan - 2013
In this paper we compared two distinct volatility forecasting approaches. GARCH models were contrasted to the models …
Persistent link: https://www.econbiz.de/10010322171
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Value at risk forecasting with the ARMA-GARCH family of models in times of increased volatility
Jánský, Ivo; Rippel, Milan - 2011
processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are … separately. The primary result of the paper is that the volatility is best modelled using a GARCH process and that an ARMA …
Persistent link: https://www.econbiz.de/10010322244
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Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts
Benavides, Guillermo; Capistrán, Carlos - 2009
This paper provides empirical evidence that combinations of option implied and time series volatility forecasts that are conditional on current information are statistically superior to individual models, unconditional combinations, and hybrid forecasts. Superior forecasting performance is...
Persistent link: https://www.econbiz.de/10010322599
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Is there a Friday the 13th Effect in Emerging Asian Stock Markets?
Auer, Benjamin R.; Rottmann, Horst - 2013
increased interest in recent research. Using a dummy-augmented GARCH model, we investigate whether the occurrence of this …
Persistent link: https://www.econbiz.de/10010323003
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Daily Exchange Rate Behaviour and Hedging of Currency Risk
Bos, Charles S.; Mahieu, Ronald J.; van Dijk, Herman K. - 1999
methods. The effects of several model characteristics(unit roots, GARCH, stochastic volatility, heavy tailed …
Persistent link: https://www.econbiz.de/10010324426
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The Stochastic Volatility in Mean Model
Koopman, Siem Jan; Uspensky, Eugenie Hol - 2000
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
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Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk
Bauwens, Luc; Bos, Charles S.; van Dijk, Herman K. - 1999
applied within a Bayesian analysisof a GARCH-mixture model which is used for the evaluation of theValue-at-Risk of the return …
Persistent link: https://www.econbiz.de/10010324702
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Herding, A-synchronous Updating and Heterogeneity in Memory in a CBS
Diks, Cees; van der Weide, Roy - 2003
predicts MA(1) structure with a negative coeffient. Asynchronous updating leads to an MA(1) model for returns with GARCH($1 …,1$) innovations, and predicts a relation between the ARCH and GARCH coefficients. Heterogeneity in memory leads to long … coefficient and the relation between the ARCH and GARCH coefficients for exchange rate data. …
Persistent link: https://www.econbiz.de/10010324793
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Daily Exchange Rate Behaviour and Hedging of Currency Risk
Bos, Charles S.; Mahieu, Ronald J.; van Dijk, Herman K. - 2001
methods. The effects ofseveral modelcharacteristics (unit roots, GARCH, stochastic volatility, heavy taileddisturbance …
Persistent link: https://www.econbiz.de/10010324963
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Stock Index Volatility Forecasting with High Frequency Data
Hol, Eugenie; Koopman, Siem Jan - 2002
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