基于心理的股价波动潜在预测因素

Q4 Business, Management and Accounting
Robert East, Malcolm Wright
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引用次数: 0

摘要

股票投资越来越依赖于人工智能(AI),但目前用于人工智能训练的措施可能无法完全涵盖影响股票价格的心理和社会因素。在此,我们将寻找可以改进人工智能预测的其他措施。我们首先回顾了似乎受社会和心理因素影响的股票价格走势,并借鉴了 COVID-19 大流行期间的股市行为。随后回顾了可能产生此类股市波动的过程:处置效应、动量和对信息的反应。然后用均值回归、消极偏差、可获得性机制和信息扩散来解释这些过程。考虑到这些过程,并借鉴消费者行为文献,我们确定了当前人工智能训练数据可能未涵盖的三个可能影响股票价格的因素:与资本化相关的宣传、与资本化相关的股票持有渗透率以及股票持有渗透率的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential Predictors of Psychologically Based Stock Price Movements
Investment in stocks is increasingly dependent on artificial intelligence (AI), but the psychological and social factors that affect stock prices may not be fully covered by the measures currently used in AI training. Here, we search for additional measures that may improve AI predictions. We start by reviewing stock price movements that appear to be affected by social and psychological factors, drawing on stock market behaviour during the COVID-19 pandemic. A review of processes that are likely to produce such stock market movements follows: the disposition effect, momentum, and the response to information. These processes are then explained by regression to the mean, negativity bias, the availability mechanism, and information diffusion. Taking account of these processes and drawing on the consumer behaviour literature, we identify three factors which may not be covered by current AI training data that could affect stock prices: publicity in relation to capitalization, stock-holding penetration in relation to capitalization, and changes in the penetration of stock holding.
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来源期刊
CiteScore
4.50
自引率
0.00%
发文量
512
审稿时长
11 weeks
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