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Quantifying time-varying forecast uncertainty and risk for the real price of oil
Aastveit, Knut Are; Cross, Jamie; Dijk, Herman K. van - 2021
, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach … analysis of profit-loss and hedging against price risk. …
Persistent link: https://www.econbiz.de/10012545165
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Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil
Aastveit, Knut Are; Cross, Jamie; Dijk, Herman K. van - 2021
, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach … analysis of profit-loss and hedging against price risk. …
Persistent link: https://www.econbiz.de/10012795319
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Modelling and simulation : an overview
McAleer, Michael; Chan, Felix; Oxley, Les - 2013
Persistent link: https://www.econbiz.de/10009765832
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Out-of-sample comparison of Copula specifications in multivariate density forecasts
Diks, Cees G. H.; Panchenko, Valentyn; Dijk, Dick van - 2008
Persistent link: https://www.econbiz.de/10003787159
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Out-of-sample comparison of copula specifications in multivariate density forecasts
Diks, Cees G. H.; Panchenko, Valentyn; Dijk, Dick van - 2008
conditions: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or non-nested. Monte …
Persistent link: https://www.econbiz.de/10011377261
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Forecasting economic time series using score-driven dynamic models with mixeddata sampling
Gorgi, Paolo; Koopman, Siem Jan; Li, Mengheng - 2018
We introduce a mixed-frequency score-driven dynamic model for multiple time series where the score contributions from high-frequency variables are transformed by means of a mixed-data sampling weighting scheme. The resulting dynamic model delivers a flexible and easy-to-implement framework for...
Persistent link: https://www.econbiz.de/10011809978
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Beating the random walk : a performance assessment of long-term interest rate forecasts
Butter, Frank A. G. den; Jansen, Pieter W. - 2008
Persistent link: https://www.econbiz.de/10003787153
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The evolution of forecast density combinations in economics
Aastveit, Knut Are; Mitchell, James; Ravazzolo, Francesco; … - 2018
Increasingly, professional forecasters and academic researchers present model-based and subjective or judgment-based forecasts in economics which are accompanied by some measure of uncertainty. In its most complete form this measure is a probability density function for future values of the...
Persistent link: https://www.econbiz.de/10011895935
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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
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/10011335205
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Forecasting daily time series using periodic unobserved components time series models
Koopman, Siem Jan; Ooms, Marius - 2004
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend and seasonal. Periodic time series models allow dynamic characteristics to depend on the period of the year, month, week or day. In the...
Persistent link: https://www.econbiz.de/10011342560