Cookies?
Library Header Image
LSE Research Online LSE Library Services

Informed trading in government bond markets

Czech, Robert, Huang, Shiyang, Lou, Dong ORCID: 0000-0002-5623-4338 and Wang, Tianyu (2021) Informed trading in government bond markets. Journal of Financial Economics, 142 (3). 1253 - 1274. ISSN 0304-405X

[img] Text (Informed Trading in Government Bond Markets) - Accepted Version
Download (1MB)

Identification Number: 10.1016/j.jfineco.2021.05.049

Abstract

Using comprehensive administrative data from the UK, we examine trading by different investor types in government bond markets. Our sample covers virtually all secondary market trading in gilts and contains detailed information on each transaction, including the identities of both counterparties. We find that hedge funds’ daily trading positively forecasts gilt returns in the following one to five days, which is then fully reversed in the following month. A part of this short-term return predictability is due to hedge funds’ ability to predict other investors’ future demand. Mutual fund trading also positively predicts gilt returns, but over a longer horizon of one to two months. This return pattern does not revert in the following year and is partly due to mutual funds’ ability to forecast changes in short-term interest rates.

Item Type: Article
Official URL: https://www.sciencedirect.com/science/journal/0304...
Additional Information: © 2021 Elsevier B.V.
Divisions: Finance
Subjects: H Social Sciences > HG Finance
H Social Sciences > HF Commerce
JEL classification: G - Financial Economics > G1 - General Financial Markets > G10 - General
G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing; Trading volume; Bond Interest Rates
G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency; Event Studies
Date Deposited: 20 Jan 2021 14:21
Last Modified: 27 Mar 2024 22:39
URI: http://eprints.lse.ac.uk/id/eprint/108504

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics