Data-Based Adaptive Estimation in an Investment Model

Abstract

Listen

Translate article

We consider improved estimation strategies for the parameters in a capital asset pricing model under a general linear constraint; we suggest candidate subspace, a preliminary test, and shrinkage estimators. We develop a large sample theory for the estimators that include derivation of asymptotic bias and asymptotic distributional risk of the suggested estimators. The asymptotic results demonstrate the superiority of the suggested estimation technique. A simulation study shows that the method suggested here has sound finite sample properties and strongly corroborates with the theoretical result of the article. A data example is also presented to illustrate the suggested estimation strategies.