Arbeitspapier
Hierarchical time varying estimation of a multi factor asset pricing model
This paper presents a new hierarchical methodology for estimating multi factor dynamic asset pricing models. The approach is loosely based on the sequential approach of Fama and MacBeth (1973). However, the hierarchical method uses very flexible bandwidth selection methods in kernel weighted regressions which can emphasize local, or recent data and information to derive the most appropriate estimates of risk premia and factor loadings at each point of time. The choice of bandwidths and weighting schemes, are achieved by cross validation. This leads to consistent estimators of the risk premia and factor loadings. Also, out of sample forecasting for stocks and two large portfolios indicates that the hierarchical method leads to statistically significant improvement in forecast RMSE.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 879
- Klassifikation
-
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Foreign Exchange
Financial Crises
International Financial Markets
- Thema
-
Asset pricing model
FamaMacBeth model
estimation of beta
kernel weighted regressions
cross validation
time-varying parameter regressions
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Baillie, Richard
Calonaci, Fabio
Kapetanios, George
- Ereignis
-
Veröffentlichung
- (wer)
-
Queen Mary University of London, School of Economics and Finance
- (wo)
-
London
- (wann)
-
2019
- 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
- Baillie, Richard
- Calonaci, Fabio
- Kapetanios, George
- Queen Mary University of London, School of Economics and Finance
Entstanden
- 2019
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