The Mean and Variance of the Mean-Variance Decision Rule

Autor:	Shankar Subramanian, James A. Chalfant, Robert N. Collender
Rok vydání:	1990
Předmět:	Variance risk premium Economics and Econometrics Admissible decision rule Joint probability distribution Price variance Statistics Econometrics Economics Decision rule Variance (accounting) Agricultural and Biological Sciences (miscellaneous) Random variable Optimal decision
Zdroj:	American Journal of Agricultural Economics. 72(4):966-974
DOI:	10.2307/1242628
Popis:	The widely used mean-variance approach to decisions under uncertainty requires estimates of the parameters of the joint distribution of returns. When optimal behavior is determined using estimates, rather than the true values, the decision is a random variable. We consider the reliability of mean-variance analysis by examining the bias and variance-covariance matrix for the decision vector. The latter shows that decisions based on estimated parameters can have a large variance around the true optimum. The results show that optimal decisions can differ substantially from those based on mean-variance analysis.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef1575e4a1b02ef430397b8718fac331 http://hdl.handle.net/10.2307/1242628 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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