CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Hedge fund pricing and model uncertainty
Authors
D. Giamouridis
D. Giamouridis
+4 more
I.D. Vrontos
I.D. Vrontos
S. Vrontos
S. Vrontos
Publication date
1 January 2008
Publisher
'Elsevier BV'
Doi
Cite
Abstract
This article uses Bayesian model averaging to study model uncertainty in hedge fund pricing. We show how to incorporate heteroscedasticity, thus, we develop a framework that jointly accounts for model uncertainty and heteroscedasticity. Relevant risk factors are identified and compared with those selected through standard model selection techniques. The analysis reveals that a model selection strategy that accounts for model uncertainty in hedge fund pricing regressions can be superior in estimation/inference. We explore potential impacts of our approach by analysing individual funds and show that they can be economically important. © 2007 Elsevier B.V. All rights reserved
Similar works
Full text
Available Versions
WestminsterResearch
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:westminsterresearch.westmi...
Last time updated on 15/09/2018
CiteSeerX
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:CiteSeerX.psu:10.1.1.1073....
Last time updated on 07/12/2020
University of Essex Research Repository
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:repository.essex.ac.uk:115...
Last time updated on 09/02/2017