Sağlam, İsmail2016-01-082016-01-081993http://hdl.handle.net/11693/17447Ankara : The Department of Economics and the Institute of Economics and Social Sciences of Bilkent Univ., 1993.Thesis (Master's) -- Bilkent University, 1993.Includes bibliographical references.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 uschLvii, 32 leavesEnglishinfo:eu-repo/semantics/openAccessSystematic RiskMean Square Error.Beta PredictionEmpirical Bayesİstanbul Stock ExchangeHG4661 .S24 1993Stock price forecasting.Stocks.Investments--Mathematical models.Thesis