Lottery mindset, mispricing and idiosyncratic volatility puzzle: Evidence from the Chinese stock market

Hoang Van Hai, Jong Won Park, Ping-Chen Tsai and Cheoljun Eom
Authors registered in the RePEc Author Service: Hoàng Văn Hải () and Hai Van Hoang

The North American Journal of Economics and Finance, 2020, vol. 54, issue C

Abstract: This study investigates the MAX effect regarding lottery mindset in the Chinese stock market. The MAX effect significantly affects stock returns through quintile portfolio and cross-sectional regression analyses. The most-overpriced stock groups, as categorized by mispricing index, show more support for the MAX effect. However, the idiosyncratic volatility (IVOL) effect continues regardless of consideration for the MAX effect, indicating that the MAX effect is not a source of the IVOL effect. Our results suggest that the MAX effect, which is highly relevant for overpriced stocks, might have information for determining stock price, and appears to be independent from information of the IVOL effect in the Chinese stock market.

Keywords: MAX effect; Lottery mindset; Mispricing; Idiosyncratic volatility; Emerging stock market (search for similar items in EconPapers)
JEL-codes: G11 G12 G17 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1062940820301637
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:ecofin:v:54:y:2020:i:c:s1062940820301637

DOI: 10.1016/j.najef.2020.101266

Access Statistics for this article

The North American Journal of Economics and Finance is currently edited by Hamid Beladi

More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().