Noise trader clusters and market efficiency

IF 4.3 2区 经济学 Q1 BUSINESS, FINANCE
Christos Pantzalis, Jung Chul Park, Pinshuo Wang
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引用次数: 0

Abstract

We posit that noise trader clusters, retail investor base configurations that are homogeneous and informationally segmented, should be associated with greater market inefficiency because they facilitate the spread of common, “local” narratives and sentiment about the stock over fundamentals and market information. Our tests confirm that noise trader clusters have significant stock pricing implications. Stocks with retail investor clusters are associated with stronger peer effects, greater delay in incorporating market information, and more idiosyncratic risk. Consistent with the notion that they are associated with greater arbitrage risk and mispricing, such stocks earn higher risk-adjusted returns and display stronger long-run reversals.
噪声交易者集群与市场效率
我们假设噪音交易者集群,即同质且信息分割的散户投资者基础配置,应该与更大的市场效率有关,因为它们促进了对股票的共同,“本地”叙述和情绪的传播,而不是基本面和市场信息。我们的测试证实,噪音交易者集群有显著的股票定价影响。散户聚集的股票具有更强的同伴效应、更大的市场信息整合延迟和更大的特质风险。这类股票与更大的套利风险和错误定价相关联,它们获得更高的风险调整后回报,并表现出更强的长期逆转。
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来源期刊
CiteScore
13.20
自引率
6.10%
发文量
75
审稿时长
69 days
期刊介绍: Behavioral and Experimental Finance represent lenses and approaches through which we can view financial decision-making. The aim of the journal is to publish high quality research in all fields of finance, where such research is carried out with a behavioral perspective and / or is carried out via experimental methods. It is open to but not limited to papers which cover investigations of biases, the role of various neurological markers in financial decision making, national and organizational culture as it impacts financial decision making, sentiment and asset pricing, the design and implementation of experiments to investigate financial decision making and trading, methodological experiments, and natural experiments. Journal of Behavioral and Experimental Finance welcomes full-length and short letter papers in the area of behavioral finance and experimental finance. The focus is on rapid dissemination of high-impact research in these areas.
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