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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 - Tinbergen Institute - 2004
The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...
Persistent link: https://www.econbiz.de/10005137234
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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 - Tinbergen Instituut - 2004
This discussion paper resulted in a publication in the 'International Journal of Forecasting', 2009, 27, 282-303.<P …
Persistent link: https://www.econbiz.de/10011257135
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Realized Volatility Risk
Allen, David E.; McAleer, Michael; Scharth, Marcel - Tinbergen Instituut - 2013
forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation …
Persistent link: https://www.econbiz.de/10011256164
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Forecasting Volatility with Copula-Based Time Series Models
Sokolinskiy, Oleg; Dijk, Dick van - Tinbergen Institute - 2011
This paper develops a novel approach to modeling and forecasting realized volatility (RV) measures based on copula … index futures, we find that the copula-based RV (C-RV) model outperforms conventional forecasting approaches for one …
Persistent link: https://www.econbiz.de/10009293998
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Forecasting Volatility with Copula-Based Time Series Models
Sokolinskiy, Oleg; Dijk, Dick van - Tinbergen Instituut - 2011
This paper develops a novel approach to modeling and forecasting realized volatility (RV) measures based on copula … index futures, we find that the copula-based RV (C-RV) model outperforms conventional forecasting approaches for one …
Persistent link: https://www.econbiz.de/10011257654
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Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice
Callot, Laurent; Kock, Anders B.; Medeiros, Marcelo C. - Tinbergen Instituut - 2014
In this paper we consider modeling and forecasting of large realized covariance matrices by penalized vector …
Persistent link: https://www.econbiz.de/10011256058
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Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment
Koopman, Siem Jan; Ooms, Marius; Hindrayanto, Irma - Tinbergen Institute - 2006
This paper discusses identification, specification, estimation and forecasting for a general class of periodic … formulations are introduced for exact maximum likelihood estimation, component estimation and forecasting. Identification issues …
Persistent link: https://www.econbiz.de/10005137026
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An Alternative Bayesian Approach to Structural Breaks in Time Series Models
Hauwe, Sjoerd van den; Paap, Richard; Dijk, Dick J.C. van - Tinbergen Institute - 2011
We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...
Persistent link: https://www.econbiz.de/10008838634
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Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment
Koopman, Siem Jan; Ooms, Marius; Hindrayanto, Irma - Tinbergen Instituut - 2006
, pages 683-713.<P> This paper discusses identification, specification, estimation and forecasting for a general class of … formulations are introduced for exact maximum likelihood estimation, component estimation and forecasting. Identification issues …
Persistent link: https://www.econbiz.de/10011256849
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An Alternative Bayesian Approach to Structural Breaks in Time Series Models
Hauwe, Sjoerd van den; Paap, Richard; Dijk, Dick J.C. van - Tinbergen Instituut - 2011
We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...
Persistent link: https://www.econbiz.de/10011257521