Highly Accurate Inference on the Sharpe Ratio for Autocorrelated Return Data

J. Qi, M. Rekkas and A. Wong

Journal of Statistical and Econometric Methods, 2018, vol. 7, issue 1, 2

Abstract: Performance measurement is an integral part of investment analysis and risk management. The Sharpe ratio is one of the most prominently used measures of performance of an investment with respect to return and risk. While most of the literature has addressed the large sample properties of the Sharpe ratio, it is important to compare the performance of these methods when only a small sample of observations is available. We propose a third-order asymptotic likelihood-based method to obtain highly accurate inference for the Sharpe ratio when returns are assumed to follow a Gaussian autoregressive process. Through real life examples, we show that results can vary vastly according to the methods used to obtain them. Results from simulation studies illustrate that our proposed method is superior to the existing methods used in the literature even with a very small number of observations.Mathematics Subject Classification: 62P05Keywords: Performance measurement; likelihood based method; Sharpe ratio

Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.scienpress.com/Upload/JSEM%2fVol%207_1_2.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spt:stecon:v:7:y:2018:i:1:f:7_1_2

Access Statistics for this article

More articles in Journal of Statistical and Econometric Methods from SCIENPRESS Ltd
Bibliographic data for series maintained by Eleftherios Spyromitros-Xioufis ().