Artikel
Hierarchical time-varying estimation of asset pricing models
This paper presents a new hierarchical methodology for estimating multi factor dynamic asset pricing models. The approach is loosely based on the sequential Fama-MacBeth approach and developed in a kernel regression framework. However, the methodology uses a very flexible bandwidth selection method which is able to emphasize recent data and information to derive the most appropriate estimates of risk premia and factor loadings at each point in time. The choice of bandwidths and weighting schemes are achieved by a cross-validation procedure; this leads to consistent estimators of the risk premia and factor loadings. Additionally, an out-of-sample forecasting exercise indicates that the hierarchical method leads to a statistically significant improvement in forecast loss function measures, independently of the type of factor considered.
- Sprache
-
Englisch
- Erschienen in
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Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 15 ; Year: 2022 ; Issue: 1 ; Pages: 1-26 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
-
asset pricing model
Fama-MacBeth model
estimation of beta
kernel-weighted regressions
cross-validation
time-varying parameter regressions
- Ereignis
-
Geistige Schöpfung
- (wer)
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Baillie, Richard
Calonaci, Fabio
Kapetanios, George
- Ereignis
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Veröffentlichung
- (wer)
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MDPI
- (wo)
-
Basel
- (wann)
-
2022
- DOI
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doi:10.3390/jrfm15010014
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Baillie, Richard
- Calonaci, Fabio
- Kapetanios, George
- MDPI
Entstanden
- 2022
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