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投资App中的大数据分析、分析师研报与投资者投资判断——一项实验研究 被引量:2

Big Data Analytics,Analyst Reports on Investment Apps and Investors’Investment Judgments——An Experimental Research
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摘要 随着大数据的广泛应用,投资app开始同时提供大数据分析和分析师研报评级等投资建议。基于心理学理论和实验研究方法,检验了投资app中分析师研报评级数量、大数据分析建议与研报评级的一致性对投资者投资判断的影响。研究发现,研报评级较多时,投资者判断的投资吸引力更高;大数据建议与研报评级一致时,评级数量的效应被强化,投资者判断的投资吸引力更高;大数据建议与研报评级不一致时,评级数量的效应被弱化,投资者判断的投资吸引力较低。此外,研报评级较少时,投资者更倾向于使用大数据分析即人工智能提出的建议;研报评级较多时,投资者更倾向于使用分析师即人力提出的建议。本文对理解大数据分析和分析师研报对投资者的影响具有重要意义。 With the widespread use of big data analytics,some investment apps are offering investors investment advice of big data analytics and analyst report simultaneously.Applying psychological theory and experimental research method,this paper examines the effect of the consistency between investment advice of big data analytics and analyst stock recommendations and number of analyst reports on apps on investors’investment judgments.The results show that the investment attractiveness judged by investors are higher under more versus less analyst reports;in the case of consistent investment advice from big data analytics and analyst recommendations,the effect of analyst recommendations numbers is stronger,i.e.,investment attractiveness will be higher;in the case of inconsistent investment advice from big data analytics and analyst recommendations,the effect of analyst recommendations numbers is weaker,i.e.,investment attractiveness will be relatively low.In addition,the study finds that investors tend to rely on advice from big data analytics,i.e.,artificial intelligence under less analyst reports conditions,while tend to rely on advice from analyst.i.e.,human under more analyst reports conditions.This paper is of great significance for understanding the impact of big data analytics and analyst recommendations on investors.
作者 张继勋 赵艺 杨小娟 何亚南 Zhang Jixun
出处 《会计研究》 CSSCI 北大核心 2023年第7期166-177,共12页 Accounting Research
基金 国家自然科学基金项目(72272080,71872090,72202204)资助。
关键词 APP 大数据分析 分析师 三角互证 投资判断 App Big Data Analytics Analyst Triangulation Investment Judgment
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