Accessibility navigation


Information biases and behaviour in asset markets

Zhang, F. (2024) Information biases and behaviour in asset markets. PhD thesis, University of Reading

[img]
Preview
Text - Thesis
· Please see our End User Agreement before downloading.

5MB
[img] Text - Thesis Deposit Form
· Restricted to Repository staff only

236kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.48683/1926.00119061

Abstract/Summary

This thesis conducts a comprehensive analysis of the behaviour and biases of information intermediaries in asset markets, focusing on analysts and media. The first empirical chapter examines analysts’ herding behaviours in stock recommendation revisions. The findings suggest that foreign analysts typically exhibit a higher herding tendency than local analysts. Our analysis further reveals that social connections between analysts and markets significantly influence their herding behaviour. The degree of herding among analysts varies depending on the market they operate in and the strength of their social connections within that market. The second empirical chapter investigates the home bias of local analysts. The results reveal a pronounced home bias towards local firms among local analysts, which is stronger in the local market and weakens in nonlocal markets. Familiarity, represented by the broker’s entry duration and firms’ media exposure, intensifies this home bias in the local market; however, it exerts a lesser effect in nonlocal markets. The study also examines how local analysts respond to state-owned enterprises in different economic environments. The third empirical chapter shifts to a macro perspective to examine the impact of city-level media political bias on land investors. The results indicate that residential and commercial land investors react negatively to media political bias due to increased information asymmetry. By contrast, industrial land investors respond positively due to potential bribery practices. The study also reveals that, in cities with efficient information flows and strong growth, the impact of media bias is reduced. Additionally, it observes that state-owned enterprises bid more aggressively for industrial land in cities with higher media bias. Overall, this thesis highlights the impact of the human element on objectivity, which potentially leads to the biased dissemination of information. It contributes to the existing literature on information intermediaries and finance as well as provides insights for market participants and policymakers in the financial market.

Item Type:Thesis (PhD)
Thesis Supervisor:Marcato, G.
Thesis/Report Department:Henley Business School
Identification Number/DOI:https://doi.org/10.48683/1926.00119061
Divisions:Henley Business School
ID Code:119061
Date on Title Page:December 2023

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation