Price Change and Trading Volume: Behavioral Heterogeneity in Stock Market

Changtai Li (), Weihong Huang (), Wei-Siang Wang () and Wai-Mun Chia ()
Additional contact information
Changtai Li: Tsinghua University
Weihong Huang: Nanyang Technological University
Wei-Siang Wang: Nanyang Technological University
Wai-Mun Chia: Nanyang Technological University

Computational Economics, 2023, vol. 61, issue 2, No 8, 677-713

Abstract: Abstract The well-known Wall Street adage that states, “It takes volume to make prices move” has long suggested that there exists a positive correlation between absolute changes in stock price and trading volume. To practitioners who use technical analysis as their trading tool, trading volume has always been treated as a key signal to price change. Although many studies have empirically examined the nonlinear relationship between price change and trading volume, very few studies are able to provide a persuasive explanation for such price-volume relationship. This paper fills this gap by providing an explanation for such relationship under a framework of heterogeneous agent model with evolutionary switching mechanism. With the support of US stock market data, we first summarize some stylized facts on stock return and trading volume. We then mimic these facts using our model. The comparison between simulated and “real” time series shows that our model is not only able to replicate the seemingly chaotic fluctuations of the financial market but also able to explain how stock prices and trading volumes co-evolve with agents’ belief.

Keywords: Heterogeneous belief; Trading volume; Stock market; Stylized facts (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-021-10224-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:kap:compec:v:61:y:2023:i:2:d:10.1007_s10614-021-10224-4

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-021-10224-4

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().