EconPapers    
Economics at your fingertips  
 

Forecasting stock returns: A time-dependent weighted least squares approach

Yudong Wang, Xianfeng Hao and Chongfeng Wu

Journal of Financial Markets, 2021, vol. 53, issue C

Abstract: We improve the performance of stock return forecasts using predictive regressions with ordinary least squares (OLS) estimates weighted by a class of time-dependent functions (TWLS). To address the structural breaks in predictive relationships, these functions assign heavier weights to more recent observations. We find return predictability that is statistically and economically significant using a forecast combination of univariate TWLS models. TWLS estimates lead to much stronger return predictability than OLS estimates. The forecast improvement from TWLS is also found when forecasting characteristic portfolio returns and when using newly proposed predictor variables. These findings survive a series of robustness checks.

Keywords: Equity premium; Structural break; Weighted least squares; Machine learning; Out-of-sample forecasting (search for similar items in EconPapers)
JEL-codes: G11 G14 G17 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1386418120300379
Full text for ScienceDirect subscribers only

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:eee:finmar:v:53:y:2021:i:c:s1386418120300379

DOI: 10.1016/j.finmar.2020.100568

Access Statistics for this article

Journal of Financial Markets is currently edited by B. Lehmann, D. Seppi and A. Subrahmanyam

More articles in Journal of Financial Markets from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2021-11-23
Handle: RePEc:eee:finmar:v:53:y:2021:i:c:s1386418120300379