2015
A Predictive Likelihood Approach to Bayesian Averaging
JEŘÁBEK, Tomáš a Radka ŠPERKOVÁZákladní údaje
Originální název
A Predictive Likelihood Approach to Bayesian Averaging
Autoři
JEŘÁBEK, Tomáš (203 Česká republika, garant, domácí) a Radka ŠPERKOVÁ (203 Česká republika)
Vydání
Acta Univ Agric Silvic Mendel Brun, Praha, Mendel University Press, 2015, 1211-8516
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
50200 5.2 Economics and Business
Stát vydavatele
Česká republika
Utajení
není předmětem státního či obchodního tajemství
Kód RIV
RIV/04274644:_____/15:#0000041
Organizační jednotka
Vysoká škola finanční a správní
Klíčová slova česky
predictive likelihood; density forecasts; Bayesian averaging; Bayesian VAR model
Klíčová slova anglicky
predictive likelihood; density forecasts; Bayesian averaging; Bayesian VAR model
Štítky
Příznaky
Recenzováno
Změněno: 8. 6. 2018 10:01, Mgr. Tomáš Jeřábek, Ph.D., MBA
V originále
Multivariate time series forecasting is applied in a wide range of economic activities related to regional competitiveness and is the basis of risk management analysis. In this paper we combine multivariate density forecasts. The performance of models is identified using historical dates including domestic economy and foreign economy, which is represented by countries of the Eurozone. Because forecast accuracy of observed models are different, the weighting scheme based on the predictive likelihood, the trace of past MSE matrix, model ranks are used to combine the models. The equal-weight scheme is used as a simple combination scheme. The results show that optimally combined densities are comparable to the best individual models.
Česky
Multivariate time series forecasting is applied in a wide range of economic activities related to regional competitiveness and is the basis of risk management analysis. In this paper we combine multivariate density forecasts. The performance of models is identified using historical dates including domestic economy and foreign economy, which is represented by countries of the Eurozone. Because forecast accuracy of observed models are different, the weighting scheme based on the predictive likelihood, the trace of past MSE matrix, model ranks are used to combine the models. The equal-weight scheme is used as a simple combination scheme. The results show that optimally combined densities are comparable to the best individual models.