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19-09-2024 | Original Research

Investor sentiment, limits to arbitrage, and hard-to-value stocks

Authors: Zhaobo Zhu, Dehua Shen

Published in: Review of Quantitative Finance and Accounting

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Abstract

An uninformed demand shock driven by investor sentiment and limits on arbitrage jointly result in the mispricing of hard-to-value stocks in standard behavioral models. However, existing work focuses on investigating the mispricing effect of either investor sentiment or limits to arbitrage possibly due to the difficulty of empirically distinguishing proxies for limits to arbitrage from hard-to-value proxies, while assuming the other is given. This paper explicitly investigates the joint and distinct roles of investor sentiment and limits to arbitrage in the mispricing effect simultaneously in a unified empirical framework. Our results show that the existence and magnitude of a mispricing depend on whether these two factors, i.e., investor sentiment and limits to arbitrage, reinforce or undermine each other. We emphasize that both investor sentiment and limits to arbitrage are two necessary conditions for a mispricing in an empirical setting.

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Footnotes
1
Following Stambaugh et al. (2012), most studies on sentiment do not explicitly consider the role of limits to arbitrage. For example, Karavias, Spilioti, and Tzavalis (2021), Koutmos (2023), Simlai (2024), and Sakariyahu, Paterson, Chatzivgeri, and Lawal (2024) examine how investor sentiment affects asset prices without explicitly considering the role of limits to arbitrage.
 
2
Hribar and McInnis (2012) argue that limits to arbitrage have little impact on analysts’ earnings forecasts, which are used as a proxy for investor earnings expectations in their paper.
 
3
For example, Ali, Hwang, Trombley (2003), Mendenhall (2004), Lesmond, Schill and Zhou (2004), Mashruwala, Rajgopal, and Shevlin (2006), Lam and Wei (2011), Li and Lou (2017), Avramov, Cheng, and Metzker (2023), Sha, Bu, Wang (2023), Abhyankar, Filippou, and Garcia-Ares (2024), DeLisle, Wang, Yuksel, and Zaynutdinova (2024) examine how various limits to arbitrage affect book-to-market effect, momentum, post-earnings-announcement drift, accruals, cash holding effect, asset growth and investment anomalies, performance of machine learning strategies, distress risk effect as well as import competition exposure premium, respectively. These studies do not explicitly control for the impact of investor sentiment when testing the role of limits to arbitrage in anomalies.
 
4
In the robustness tests, we use the firm-level idiosyncratic volatility (IVOL) as a proxy for the main holding cost. Pontiff (2006) argues that IVOL as a proxy for idiosyncratic risk is the main cost faced by arbitrageurs. IVOL has been widely used as a proxy for arbitrage risk in many studies (e.g., Lam and Wei 2011; An et al. 2020).
 
5
To further mitigate the concern that the raw IO data is highly correlated with the proxy for difficulty to value, we use the residual IO value that is obtained from a cross-sectional regression in which the HTV index is the independent variable. In addition, these two terms “difficulty to value” and “hard to value” are used interchangeably.
 
6
Alburaythin, Fifield, and Paramati (2024) examine how investor sentiment and limits to arbitrage jointly affect anomalies in the U.K. stock market.
 
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Metadata
Title
Investor sentiment, limits to arbitrage, and hard-to-value stocks
Authors
Zhaobo Zhu
Dehua Shen
Publication date
19-09-2024
Publisher
Springer US
Published in
Review of Quantitative Finance and Accounting
Print ISSN: 0924-865X
Electronic ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-024-01353-6

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