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SYSTEMATIC RISK IN A PURELY RANDOM MARKET MODEL: SOME EMPIRICAL EVIDENCE FOR INDIVIDUAL PUBLIC UTILITIES
Author(s) -
Rahman Abdul,
Kryzanowski Lawrence,
Sim Ah Boon
Publication year - 1987
Publication title -
journal of financial research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.319
H-Index - 49
eISSN - 1475-6803
pISSN - 0270-2592
DOI - 10.1111/j.1475-6803.1987.tb00486.x
Subject(s) - estimator , econometrics , mean squared error , statistics , mathematics , economics , quadratic equation , sample (material) , ordinary least squares , chemistry , geometry , chromatography
A minimum norm quadratic (MINQU‐) type of OLS estimator is derived. The estimator is used to test if the betas of the single factor market (SFM) model are random for a sample of utilities for two contiguous periods. The estimated betas for individual utilities vary considerably over time. The statistical significance of such nonstationarity depends on both the utilities and period studied. The relative reduction in the mean square error (MSE) from using a GLS (and not OLS) estimator of beta, when beta is purely random, can be substantial for some utilities but is modest on average.