Transaction cost analytics for corporate bonds
Xin Guo,
Charles-Albert Lehalle and
Renyuan Xu
Quantitative Finance, 2022, vol. 22, issue 7, 1295-1319
Abstract:
Electronic platforms have been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Transaction Cost Analysis (TCA). One of the challenges in TCA is to build a realistic benchmark for the expected transaction cost and to characterize the price impact of each individual trade with given bond characteristics and market conditions. Taking the viewpoint of retail investors, this paper presents an analytical methodology for TCA of corporate bond trading. Our analysis is based on the TRACE Enhanced dataset; and starts with estimating the initiator of a bond transaction, followed by estimating the bid-ask spread and the mid-price dynamics. With these estimations, the first part of our study is to identify key features for corporate bonds and to compute the expected average trading cost. This part is on the time scale of weekly transactions, and is by applying and comparing several regularized regression models. The second part of our study is using the estimated mid-price dynamics to investigate the amplitude of its price impact and the decay pattern of individual bond transaction. This part is on the time scale of each transaction of liquid corporate bonds, and is by applying a transient impact model to estimate the price impact kernel using a non-parametric method. Our benchmark model allows for identifying abnormal transactions and for enhancing counter-party selections. A key discovery of our study is the price impact asymmetry between customer-buy orders and consumer-sell orders.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2022.2054723 (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Transaction Cost Analytics for Corporate Bonds (2021) 
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:taf:quantf:v:22:y:2022:i:7:p:1295-1319
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20
DOI: 10.1080/14697688.2022.2054723
Access Statistics for this article
Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral
More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().