A new method for estimating Sharpe ratio function via local maximum likelihood

doi:10.1080/02664763.2022.2114431

	A new method for estimating Sharpe ratio function via local maximum likelihood
	Xu, Wenchao 1; Lin, Hongmei 2; Tong, Tiejun 3; Zhang, Riquan 2,4,5
刊名	JOURNAL OF APPLIED STATISTICS
	2022-08-30
页码	19
关键词	Direct method heteroscedastic non-parametric regression joint limiting distribution local polynomial smoothing Sharpe ratio function
ISSN号	0266-4763
DOI	10.1080/02664763.2022.2114431
英文摘要	The Sharpe ratio function is a commonly used risk/return measure in financial econometrics. To estimate this function, most existing methods take a two-step procedure that first estimates the mean and volatility functions separately and then applies the plug-in method. In this paper, we propose a direct method via local maximum likelihood to simultaneously estimate the Sharpe ratio function and the negative log-volatility function as well as their derivatives. We establish the joint limiting distribution of the proposed estimators, and moreover extend the proposed method to estimate the multivariate Sharpe ratio function. We also evaluate the numerical performance of the proposed estimators through simulation studies, and compare them with existing methods. Finally, we apply the proposed method to the three-month US Treasury bill data and that captures a well-known covariate-dependent effect on the Sharpe ratio.
资助项目	China Postdoctoral Science Foundation[2021M693340] ; National Natural Science Foundation of China[1207010822] ; Shanghai Natural Science Foundation[20ZR1421800] ; General Research Fund[HKBU12303421] ; General Research Fund[HKBU12303918] ; Initiation Grant for Faculty Niche Research Areas of Hong Kong Baptist University[RC-FNRA-IG/20-21/SCI/03] ; National Science Foundation of China[1207010822] ; National Science Foundation of China[11971171] ; National Science Foundation of China[11831008] ; Basic Research Project of Shanghai Science and Technology Commission[22JC1400800]
WOS研究方向	Mathematics
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000865661200001
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/60850]
专题	中国科学院数学与系统科学研究院
通讯作者	Lin, Hongmei
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 2.Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai, Peoples R China 3.Hong Kong Baptist Univ, Dept Math, Hong Kong, Peoples R China 4.East China Normal Univ, MOE, Key Lab Adv Theory & Applicat Stat & Data Sci, Shanghai, Peoples R China 5.East China Normal Univ, Sch Stat, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Xu, Wenchao,Lin, Hongmei,Tong, Tiejun,et al. A new method for estimating Sharpe ratio function via local maximum likelihood[J]. JOURNAL OF APPLIED STATISTICS,2022:19.
APA	Xu, Wenchao,Lin, Hongmei,Tong, Tiejun,&Zhang, Riquan.(2022).A new method for estimating Sharpe ratio function via local maximum likelihood.JOURNAL OF APPLIED STATISTICS,19.
MLA	Xu, Wenchao,et al."A new method for estimating Sharpe ratio function via local maximum likelihood".JOURNAL OF APPLIED STATISTICS (2022):19.