Publication:

Robust performance hypothesis testing with smooth functions of population moments

Date

Date

Date
2018
Working Paper

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Citation copied

Ledoit, O., & Wolf, M. (2018). Robust performance hypothesis testing with smooth functions of population moments (No. 305; Working Paper Series / Department of Economics).

Abstract

Abstract

Abstract

Applied researchers often want to make inference for the difference of a given performance measure for two investment strategies. In this paper, we consider the class of performance measures that are smooth functions of population means of the underlying returns; this class is very rich and contains many performance measures of practical interest (such as the Sharpe ratio and the variance). Unfortunately, many of the inference procedures that have been suggested previously in the applied literature make unreasonable assumptions that d

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Creators (Authors)

Series Name

Series Name

Series Name
Working paper series / Department of Economics

Institution

Institution

Institution

Item Type

Item Type

Item Type
Working Paper

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Dewey Decimal Classifikation

JEL Classification

JEL Classification

JEL Classification
C12
C14
C22

Keywords

Bootstrap, HAC inference, kurtosis, Sharpe ratio, sknewness, variance, Bootstrap-Statistik, Kurtosis, Schiefe, Varianz, Investition, Strategie

Scope

Scope

Scope
Discipline-based scholarship (basic research)

Language

Language

Language
English

Publication date

Publication date

Publication date
2018-10

Date available

Date available

Date available
2018-10-24

Number of pages

Number of pages

Number of pages
22

ISSN or e-ISSN

ISSN or e-ISSN

ISSN or e-ISSN
1664-7041

OA Status

OA Status

OA Status
Green

Other Identification Number

Other Identification Number

Other Identification Number
merlin-id:17109

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Citation copied

Ledoit, O., & Wolf, M. (2018). Robust performance hypothesis testing with smooth functions of population moments (No. 305; Working Paper Series / Department of Economics).

Green Open Access
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