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Dynamic correlations and optimal hedge rations
Bos, Charles S.; Gould, Phillip - 2007
Persistent link: https://www.econbiz.de/10003482688
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Dynamic correlations and optimal hedge ratios
Bos, Charles S.; Gould, Phillip - 2007
good on the present set of measures as the stochastic volatility models, with or without dynamic correlation. …The focus of this article is using dynamic correlation models for the calculation of minimum variance hedge ratios …. Modelling the correlation explicitly is shown to produce the best hedges when applied to the simulated data. For financial time …
Persistent link: https://www.econbiz.de/10011372522
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A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations
Creal, Drew; Koopman, Siem Jan; Lucas, André - 2010
We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...
Persistent link: https://www.econbiz.de/10011380135
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The euro introduction and non-euro currencies
Dijk, Dick van; Munandar, Haris; Hafner, Christian M. - 2006
the framework of dynamic conditional correlation (DCC) models, we find that such breaks occurred both at the time the …
Persistent link: https://www.econbiz.de/10011343243
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Long memory dynamics for multivariate dependence under heavy tails
Janus, Paweł; Koopman, Siem Jan; Lucas, André - 2011
Persistent link: https://www.econbiz.de/10009720703
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Realized Wishart-GARCH : a score-driven multi-Asset volatility model
Hansen, Peter Reinhard; Janus, Paweł; Koopman, Siem Jan - 2016
We propose a novel multivariate GARCH model that incorporates realized measures for the variance matrix of returns. The key novelty is the joint formulation of a multivariate dynamic model for outer-products of returns, realized variances and realized covariances. The updating of the variance...
Persistent link: https://www.econbiz.de/10011520881
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Modeling dynamic volatilities and correlations under skewness and fat tails
Zhang, Xin; Creal, Drew; Koopman, Siem Jan; Lucas, André - 2011
autoregressive conditional heteroskedasticity model and the dynamic conditional correlation model where distributional assumptions …
Persistent link: https://www.econbiz.de/10011386468
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Realized variances vs. correlations : unlocking the gains in multivariate volatility forecasting
Capera Romero, Laura; Opschoor, Anne - 2024
volatility forecasting into two pillars: the realized variances and realized correlations and quantifies the corresponding …% and at least 78%). The results on the GMV portfolios show that realized covariance models exhibit lower ex-post volatility …
Persistent link: https://www.econbiz.de/10015064180
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Value-at-risk and extreme returns
Daníelsson, Jón; Vries, Casper G. de - 1997
Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...
Persistent link: https://www.econbiz.de/10010533206
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Score driven exponentially weighted moving average and value-at-risk forecasting
Lucas, André; Zhang, Xin - 2014
dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …
Persistent link: https://www.econbiz.de/10010384110