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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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Value-at-risk and extreme returns
Daníelsson, Jón; Vries, Casper G. de - 1998
Persistent link: https://www.econbiz.de/10000980737
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Spot variance path estimation and its application to high frequency jump testing
Bos, Charles S.; Janus, Paweł; Koopman, Siem Jan - 2009
This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...
Persistent link: https://www.econbiz.de/10011379469
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Stock index volatility forecasting with high frequency data
Hol Uspensky, Eugenie; Koopman, Siem Jan - 2002
improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …
Persistent link: https://www.econbiz.de/10011326944
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Fractional integration and fat tails for realized covariance kernels and returns
Lucas, André; Opschoor, Anne - 2016 - This version: September 1, 2016
We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...
Persistent link: https://www.econbiz.de/10011531139
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GARCH models for daily stock returns : impact of estimation frequency on value-at-risk and expected shortfall forecasts
Ardia, David; Hoogerheide, Lennart - 2013
Persistent link: https://www.econbiz.de/10010191413
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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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Return-volatility relationship : insights from linear and non-linear quantile regression
Allen, David E.; Singh, Abhay Kumar; Powell, Robert; … - 2013
Persistent link: https://www.econbiz.de/10009724826
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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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A hybrid joint moment ratio test for financial time series
Groenendijk, Patrick A.; Lucas, André; Vries, Casper G. de - 1998
. The methodology is hybrid because it combines a formaltesting procedure with volatility curve pattern recognition based …
Persistent link: https://www.econbiz.de/10011299968