Prediction of systematic risk: "a case from Turkey"

Date
1993
Advisor
Akdoğan, Haluk
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Publisher
Bilkent University
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Language
English
Type
Thesis
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Abstract

This stjid}^ sugpjosts Bayesian and time-varying models to adjust for the regression tc'ndeiK'y of lietas [iresent in standard asset i)ricing applications. Beta, adjustment techniciues are a])])li('d to the Istcinl.^ul Stock Exchange da.ta. Empirical findings show tlia.t MSE (Mean Square Error) are lowest among all models used in tlie study when log-linear or sciuare-root linear Blume modcds are used and lietas predicted according to Bayesian models have lower MSl·^ tlian unadjusted Ivetas. Also, it is oliserved tha,t inediciency ])art of tlie MSE changes most when various adjustment teclmiques are uschL

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Keywords
Systematic Risk, Mean Square Error., Beta Prediction, Empirical Bayes, İstanbul Stock Exchange
Citation
Published Version (Please cite this version)