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In-sample bounds for time-varying parameters of observation driven models
Blasques, Francisco; Koopman, Siem Jan; Łasak, Katarzyna; … - 2015
. They are applicable to the complete class of observation driven models and are valid for a wide range of estimation … that is embedded in the time-varying parameter path. We illustrate our findings in a volatility analysis for monthly …
Persistent link: https://www.econbiz.de/10010484891
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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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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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Short patches of outliers, ARCH and volatility modeling
Franses, Philip Hans; Dijk, Dick van; Lucas, André - 1998
In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span...
Persistent link: https://www.econbiz.de/10011284080
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A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations
Creal, Drew; Koopman, Siem Jan; Lucas, André - 2010
the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we account …. We provide an empirical illustration for a panel of daily global equity returns. …
Persistent link: https://www.econbiz.de/10011380135
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Modeling dynamic volatilities and correlations under skewness and fat tails
Zhang, Xin; Creal, Drew; Koopman, Siem Jan; Lucas, André - 2011
We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...
Persistent link: https://www.econbiz.de/10011386468
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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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Long memory dynamics for multivariate dependence under heavy tails
Janus, Paweł; Koopman, Siem Jan; Lucas, André - In: Journal of empirical finance 29 (2014), pp. 187-206
Persistent link: https://www.econbiz.de/10011300485
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Score driven exponentially weighted moving averages and value-at-risk forecasting
Lucas, André; Zhang, Xin - 2015
volatility of individual stock returns and exchange rate returns. …
Persistent link: https://www.econbiz.de/10011332948
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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