EconPapers    
Economics at your fingertips  
 

Predictive ability of low-frequency volatility measures: Evidence from the Hong Kong stock markets

Christopher Gan, Gilbert Nartea and Ji Wu

Finance Research Letters, 2018, vol. 26, issue C, 40-46

Abstract: We employ low-frequency data to estimate historical volatility measures for Hong Kong stocks and examine the relationship between these measures and the one-month ahead stock return over thirty-five years. First, we employ a stock's past three-year weekly return to compute idiosyncratic volatility. Second, we use a stock's past three-year maximum weekly return to create a MAX measure. We find that both IVOL and MAX are significant and negatively related to the one-month ahead stock return. Both effects co-exist in the Hong Kong stock markets and are robust after controlling for the financial crisis, January effect, and tiny stocks.

Keywords: Total volatility; Idiosyncratic volatility; Maximum weekly returns; Asset pricing; Weekly data; Hong Kong stock markets (search for similar items in EconPapers)
JEL-codes: G11 G12 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S154461231730346X
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:finlet:v:26:y:2018:i:c:p:40-46

DOI: 10.1016/j.frl.2017.11.007

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:finlet:v:26:y:2018:i:c:p:40-46