Arbeitspapier
Bayesian inference for hedge funds with stable distribution of returns
Recently, a body of academic literature has focused on the area of stable distributions and their application potential for improving our understanding of the risk of hedge funds. At the same time, research has sprung up that applies standard Bayesian methods to hedge fund evaluation. Little or no academic attention has been paid to the combination of these two topics. In this paper, we consider Bayesian inference for alpha-stable distributions with particular regard to hedge fund performance and risk assessment. After constructing Bayesian estimators for alpha-stable distributions in the context of an ARMA-GARCH time series model with stable innovations, we compare our risk evaluation and prediction results to the predictions of several competing conditional and unconditional models that are estimated in both the frequentist and Bayesian setting. We find that the conditional Bayesian model with stable innovations has superior risk prediction capabilities compared with other approaches and, in particular, produced better risk forecasts of the abnormally large losses that some hedge funds sustained in the months of September and October 2008.
- Sprache
-
Englisch
- Erschienen in
-
Series: KIT Working Paper Series in Economics ; No. 1
- Klassifikation
-
Wirtschaft
- Thema
-
Hedgefonds
Wertpapieranalyse
Kapitalertrag
Risiko
Statistische Verteilung
Bayes-Statistik
Schätztheorie
Theorie
Schätzung
Welt
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Güner, Biliana
Rachev, Svetlozar T.
Edelman, Daniel
Fabozzi, Frank J.
- Ereignis
-
Veröffentlichung
- (wer)
-
Karlsruher Institut für Technologie (KIT), Institut für Volkswirtschaftslehre (ECON)
- (wo)
-
Karlsruhe
- (wann)
-
2010
- DOI
-
doi:10.5445/IR/1000019743
- Handle
- URN
-
urn:nbn:de:swb:90-197430
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Güner, Biliana
- Rachev, Svetlozar T.
- Edelman, Daniel
- Fabozzi, Frank J.
- Karlsruher Institut für Technologie (KIT), Institut für Volkswirtschaftslehre (ECON)
Entstanden
- 2010
Ähnliche Objekte (12)
Nonparametric Bayesian inference for meta-stable conformational dynamics
Why Bayesian inference?
Bayesian nonparametric measurement of factor betas and clustering with application to hedge fund returns
Bayesian inference of engineering models
Value investing via Bayesian inference
Inference in Bayesian proxy-SVARs
Value investing via Bayesian inference
Bayesian inference with geodetic applications
Recovering delisting returns of hedge funds
Bayesian TWAS: a causal inference approach
Bayesian inference of early-universe signals
SPARROW Applications Using Bayesian Inference Techniques
Nonparametric Bayesian inference for meta-stable conformational dynamics
Why Bayesian inference?
Bayesian nonparametric measurement of factor betas and clustering with application to hedge fund returns
Bayesian inference of engineering models
Value investing via Bayesian inference
Inference in Bayesian proxy-SVARs
Value investing via Bayesian inference
Bayesian inference with geodetic applications
Recovering delisting returns of hedge funds
Bayesian TWAS: a causal inference approach
Bayesian inference of early-universe signals
SPARROW Applications Using Bayesian Inference Techniques
Nonparametric Bayesian inference for meta-stable conformational dynamics
Why Bayesian inference?
Bayesian nonparametric measurement of factor betas and clustering with application to hedge fund returns
Bayesian inference of engineering models
Value investing via Bayesian inference
Inference in Bayesian proxy-SVARs
Value investing via Bayesian inference
Bayesian inference with geodetic applications
Recovering delisting returns of hedge funds
Bayesian TWAS: a causal inference approach
Bayesian inference of early-universe signals