Arbeitspapier
Comparing and evaluating Bayesian predictive distributions of assets returns
Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative models of asset returns applied to daily S&P 500 returns from 1976 through 2005. The comparison exercise uses predictive likelihoods and is inherently Bayesian. The evaluation exercise uses the probability integral transform and is inherently frequentist. The illustration shows that the two approaches can be complementary, each identifying strengths and weaknesses in models that are not evident using the other.
- Sprache
-
Englisch
- Erschienen in
-
Series: ECB Working Paper ; No. 969
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Forecasting Models; Simulation Methods
- Thema
-
forecasting
GARCH
inverse probability transform
Markov mixture
predictive likelihood
S&P 500 returns
stochastic volatility
Wahrscheinlichkeitsrechnung
ARCH-Modell
Markov-Kette
Prognoseverfahren
Kapitaleinkommen
Theorie
USA
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Geweke, John
Amisano, Gianni
- Ereignis
-
Veröffentlichung
- (wer)
-
European Central Bank (ECB)
- (wo)
-
Frankfurt a. M.
- (wann)
-
2008
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Geweke, John
- Amisano, Gianni
- European Central Bank (ECB)
Entstanden
- 2008
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