A1 - Fleicher, Karlheinz
A1 - Nietert, Bernhard
PB - Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
N2 - Semivariance is an intuitive risk measure because it concentrates on the shortfall below a target and not on total variation. To successfully use semivariance in practice, however, a statistical estimator of semivariance is needed; Josephy and Aczel provide such an estimator. Unfortunately, they have not correctly proven asymptotic unbiasedness and mean squared error consistency of their estimator since their proof contains a mistake. This paper corrects the computational mistake in Josephy-Aczel’s original proof and, that way, allows researchers and practitioners in the field of downside portfolio selection, hedging, downside asset pricing, risk measurement in a regulatory context, and performance measurement to work with a meaningfully specified downside measure
L1 - http://www.dbc.wroc.pl/Content/70699/Karlheinz_Nietert_Statistically_optimal_estimators_of_semivariance.pdf
L2 - http://www.dbc.wroc.pl/Content/70699
KW - risk analysis
KW - semivariance
KW - statistical estimation
KW - analiza ryzyka
KW - semiwariancja
KW - estymacja statystyczna
ER -
T1 - Statistically (optimal) estimators of semivariance: A correction of Josephy-Aczel’s proof
UR - http://www.dbc.wroc.pl/dlibra/docmetadata?id=70699