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In this paper some effects of nonstationary parameters upon inferences and decisions in portfolio analysis are investigated. A Bayesian inferential model with nonstationary parameters is presented and is applied to the problem of portfolio choice. For this model, nonstationarity 1) implies greater uncertainty about future returns; 2) implies that in forecasting future returns, recent returns should receive more weight than not-so-recent returns; 3) restricts the amount of information that can be obtained about future values of the parameters of interest; 4) shifts investment among risky securities and from risky securities to risk-free securities; and 5) yields optimal portfolios with smaller expected returns than corresponding optimal portfolios in the stationary case.
|Item Type:||Monograph (IIASA Research Report)|
|Research Programs:||System and Decision Sciences - Core (SDS)|
|Depositing User:||IIASA Import|
|Date Deposited:||15 Jan 2016 01:40|
|Last Modified:||21 Jul 2016 18:59|
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