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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
fractionally integrated moving average model which allows for long memory in the logarithms of realised volatility. We compare the … 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 …
Persistent link: https://www.econbiz.de/10011326944
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Detecting serial dependence in tail events
Diks, Cees G. H. - 2002
A test for serial independence is proposed which is related to the BDS test but focuses on tail event probabilities rather than probabilities near the center of the distribution. The motivation behind this approach is to obtain a test more suitable for detecting structure in the tails, such as...
Persistent link: https://www.econbiz.de/10011327543
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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 … economically outperforms recent alternatives such as the Multivariate HEAVY model and the 2006 "long-memory" version of the …
Persistent link: https://www.econbiz.de/10011531139
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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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Intraday stock price dependence using dynamic discrete copula distributions
Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2015
Persistent link: https://www.econbiz.de/10010494787
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A cointegration analysis of agricultural, energy and bio-fuel spot and futures prices
Allen, David E.; Chang, Chia-Lin; McAleer, Michael; … - 2016
vary according to whether they are in low or high volatility regimes. …
Persistent link: https://www.econbiz.de/10011479769
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Intraday stochastic volatility in discrete price changes : the dynamic Skellam model
Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2015
We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete … series per day varies from 1000 to 10,000. Complexities in the intraday dynamics of volatility and in the frequency of trades … intraday volatility shows that the dynamic modified Skellam model provides accurate forecasts compared to alternative modeling …
Persistent link: https://www.econbiz.de/10011295740
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Modeling and forecasting S&P 500 volatility : long memory, structural breaks and nonlinearity
Martens, Martin; Dijk, Dick van; Pooter, Michiel de - 2004
Persistent link: https://www.econbiz.de/10002128301
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Moments, shocks and spillovers in Markov switching VAR models
Dijk, Dick van; Kole, Erik - 2021
To investigate how economies, financial markets or institutions can deal with stress, we nowadays often analyze the effects of shocks conditional on a recession or a bear market. MSVAR models are ideally suited for such analyses because they combine gradual movement with sudden switches. In this...
Persistent link: https://www.econbiz.de/10012621564