01
原文：Bianchi, M., & Brière, M. Human-Robot interactions in investment decisions. Management Science. 2024.
Human-Robot Interactions in Investment Decisions
ABSTRACT: We study the introduction of robo-advising on a large set of employee saving plans. Different from many services that fully automate portfolio decisions, our robo-advisor proposes investment and rebalancing strategies, leaving investors free to follow or ignore them. The resulting human -robot interactions occur both at the time of the subscription and over time, as the robot sends alerts when the investor’s portfolio gets too far from the target allocation. We show that the robo-service is associated with an increase in investors' attention and trading activities. Following the robot’s alerts, investors change their rebalancing behaviors so as to stay closer to their target allocation, which results in larger portfolio returns. Counterfactual returns induced by automatic rebalancing by the robot would be only slightly higher, suggesting that, on average, the financial cost of letting investors retain control is not large.
投资决策中的人机交互
摘要：文章研究了在大量员工储蓄计划中引入智能投顾的情况。与许多完全自动做出投资组合决策的服务不同，智能投顾会提出投资和再平衡策略，让投资者自由选择遵循或忽略这些策略。由此产生的人机交互既发生在订阅时，也发生在一段时间内，当投资者的投资组合与目标配置相差太远时，机器人会发出警报。研究表明，机器人服务提高了投资者的注意力和交易活动。在机器人发出警报后，投资者会改变他们的再平衡行为，以便更接近目标配置，从而获得更大的投资组合回报。机器人自动再平衡所带来的反事实回报率仅略有提高，这表明，平均而言，让投资者保留控制权的财务成本并不高。
亮点：（1）文章分析了智能投顾如何通过提供投资和再平衡策略建议，增加投资者对其投资组合的关注度和交易活动，对于理解机器人顾问如何影响投资者行为至关重要。（2）文章揭示了机器人顾问服务对投资者风险暴露和投资组合回报的积极影响，并进一步探讨了在自动化投资顾问服务中保留人工决策的权利的潜在财务成本，上述发现为理解智能投顾如何影响个人投资者的决策提供了新的视角。
02
原文：Reher, M., & Sokolinski, S. Robo-advisors and access to wealth management. Journal of Financial Economics, 2024, 155, 103869.
Robo Advisors and Access to Wealth Management
ABSTRACT: We investigate how access to robo-advisors impacts the financial investment and welfare of less-wealthy investors. We leverage a quasi-experiment where a major U.S. robo-advisor significantly expands access by reducing its account minimum, increasing participation by middle-class investors but not the poor. A benchmark model calibrated to portfolio-level data rationalizes this increase: middle-class investors want sophisticated investing but cannot achieve it themselves. Their welfare rises moderately, driven by advanced features like multi-dimensional glide-paths and additional priced risk factors. Middle-age investors gain three times more than millennials. Our results reveal novel margins of demand for robo-advisors, helping explain their sustained growth.
智能投顾和财富管理
摘要：文章研究了使用智能投顾如何影响不太富裕投资者的金融投资和财富。文章利用了一个准实验，美国一家智能投顾企业通过降低账户最低限额大幅扩大准入范围，这增加了中产阶级投资者的参与，但并未增加穷人的参与。投资组合层面的数据校准的基准模型合理解释了这一增长，即中产阶级投资者希望进行自己无法实现的复杂投资。在多维滑行路径和额外定价风险因素等先进功能的推动下，他们的财富适度增加。中年投资者的收益是千禧一代的三倍。我们的研究结果揭示了智能投顾的增量需求边际，这有助于解释其持续增长的原因。
亮点：（1）文章探讨了智能投顾服务对投资者金融投资和财富的影响，为理解智能投顾如何扩展服务到更广泛的客户群体提供了新的视角。（2）文章研究智能投顾的增长和投资者对智能投顾的需求，强调了智能投顾在提供个性化和多元化投资组合方面的价值，为理解智能投顾市场的增长提供了新的证据。
03
原文：Coleman, B., Merkley, K., & Pacelli, J. Human versus machine: A comparison of robo-analyst and traditional research analyst investment recommendations. The Accounting Review, 2022, 97(5), 221-244.
Human Versus Machine: A Comparison of Robo-Analyst and Traditional Research Analyst Investment Recommendations
ABSTRACT: We provide the first comprehensive analysis of the properties of investment recommendations generated by “Robo-Analysts” which are human analyst-assisted computer programs conducting automated research analysis. Our results indicate that Robo-Analyst recommendations differ from those produced by traditional “human” research analysts across several important dimensions. First, Robo-Analysts produce a more balanced distribution of buy, hold, and sell recommendations than do human analysts and are less likely to recommend “glamour” stocks and firms with prospective investment banking business. Second, automation allows Robo-Analysts to revise their recommendations more frequently than human analysts and incorporate information from complex periodic filings. Third, while Robo-Analysts’ recommendations exhibit weak short-window return reactions, they have long-term investment value. Specifically, portfolios formed based on the buy recommendations of Robo-Analysts significantly outperform those of human analysts. Overall, our results suggest that automation in the sell-side research industry can benefit investors.
人与机器：机器分析师与传统研究分析师投资建议的比较
摘要：文章首次全面分析了“机器人分析师”（Robo-Analysts）所生成的投资建议的特性，这些“机器人分析师”是一种计算机程序，进行自动研究分析。研究结果表明，机器人分析师的建议与传统“人类”分析师的建议在以下方面存在差异。第一，机器人分析师提供了更加平衡的买入、持有和卖出建议分布，且不太可能推荐“热门”股票和有潜在投资银行业务的公司。第二，相比于人类分析师，自动化使得机器人分析师更频繁地更改他们的建议，并纳入复杂周期性申报文件中的信息。第三，机器人分析师的投资建议表现出较弱的短期回报，但它们具有长期投资价值。具体来说，根据机器人分析师建议所构成的投资组合显著优于人类分析师的投资组合。总体而言，结果表明，卖方研究行业的自动化可以为投资者带来好处。
亮点：（1）文章首次提供了对机器人分析师和传统人类分析师在投资建议生成方面的全面比较。这种比较涵盖了建议的乐观性、修订频率以及对复杂财务披露信息的整合能力，为理解自动化技术在金融分析领域的应用提供了新的视角。（2）文章强调了自动化在金融分析中的潜在优势，为理解技术进步对劳动市场和行业结构的影响提供了实证依据。
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总编：游家兴
解析：王智源
审校：刘乾 秦会
编辑：潘芳妍
