Riley, C orcid.org/0000-0003-0325-982X, Summers, B orcid.org/0000-0002-9294-0088 and Duxbury, D (2020) Capital Gains Overhang with a Dynamic Reference Point. Management Science, 66 (10). pp. 4359-4919. ISSN 0025-1909
Abstract
Financial models incorporating a reference point, such as the Capital Gains Overhang (CGO) model, typically assume it is fixed at the purchase price. Combining experimental and market data, this paper examines whether such models can be improved by incorporating reference-point adjustment. Using real stock prices over horizons from 6 months to 5 years, experimental evidence demonstrates that a number of salient points in the prior share price path are key determinants of the reference point, in addition to the purchase price. Market data testing is then undertaken by using the CGO model. We show that composite CGO variables, created by using a mix of salient points with weights determined in the experiment, have greater predictive power than the traditional CGO variable in both cross-sectional U.S. equity-return analysis and when analyzing the performance of double-sorted portfolios. In addition, future trading volume is more sensitive to changes in the composite CGO variables than to the traditional CGO, further emphasizing the importance of adjusting reference points.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020, The Author(s). This is an author produced version of a paper published in Management Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | reference points; prospect theory; price momentum; asset pricing |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Decision Research (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 May 2019 10:23 |
Last Modified: | 04 May 2021 14:51 |
Status: | Published |
Publisher: | Institute for Operations Research and the Management Sciences |
Identification Number: | 10.1287/mnsc.2019.3404 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:146448 |