
• 要检验AI的潜力,不妨将金融界的“终结者”空降到20世纪90年代的华尔街。斯坦福大学(Stanford University)与波士顿学院(Boston College)的研究人员采用该方法发现,他们开发的AI机器人可通过降低投资组合风险,显著提升多数基金经理的收益回报。
人工智能究竟会增强还是取代人类劳动?各行业对此争论不休。两年前,斯坦福大学与波士顿学院的研究人员决定探究飞速发展的AI技术对职业股票操盘手的意义。他们创造了一位“AI分析师”,并允许其每季度调整逾3,300只主动管理型多元化共同基金的投资组合。
在基金存续期内,经AI机器人调整后的投资组合中,有93%的表现超越了人类经理。1990至2020年间,由AI机器人管理的基金季度超额收益(即跑赢市场的回报)比人类经理多出1,710万美元。该AI机器人仅利用财务报告、分析师预测和报价等公开数据就取得如此成果,其碾压性优势甚至令研究者本人都感到震惊。
斯坦福大学商学院会计学教授埃德·德哈恩对《财富》杂志表示:“我们在一年前得出这些结果,AI的巨大优势令我们直呼‘这不可能’。”
但德哈恩表示,经过对每个步骤和假设的反复验证,结果确凿无误。他提醒切勿过度解读,并强调其团队并非预言投资组合经理将集体被AI取代,但初级分析师可能很快面临失业危机。
身兼《会计与经济学杂志》(Journal of Accounting and Economics)总编的德哈恩表示:“我认为,五年后,枯坐办公室处理Excel表格这类工作基本会消失。”
德哈恩阐释称,传统观点认为,最成功的主动型经理人主要依靠创造性思维和广泛人脉制胜,他们通过深度把握企业与行业内外的动态,发掘财务数据之外的机遇。
德哈恩表示,新研究将样本基金经理可以掌握的会计报告、经济数据、分析师建议和卖方研究报告,提供给AI机器人,彻底颠覆了这一认知。
他表示,关键在于,AI并非通过挖掘人类可能忽略的冷门信息获利。研究者开发的“随机森林模型”持续以不同方式拆分重组数据,依托多组变量反复生成新预测。
德哈恩指出,AI仅需数小时就能完成原本需十名专业员工承担的工作,从而发现那些“隐藏于众目睽睽之下的信息”。
但该研究存在重要限制条件。一方面,AI并未与其他掌握同等技术的基金竞争。
德哈恩表示:“当所有人开始使用AI时,游戏规则将彻底改变。”
他强调该研究实为思想实验——以AI的能力为标尺,衡量人类经理因无力负担额外人力或技术投入而“错失的收益”。
换言之,检验AI潜力的方法之一,是推演若35年前就有参与者掌握该技术,行业格局将如何改写。或用德哈恩一位同行的说法:假如将金融版“终结者”(即施瓦辛格在1984年同名电影中饰演的机械杀手)送回1990年,会发生什么。
鉴于人类管理的基金平均每季度向投资者收取360万美元管理费,研究显示基金需将费用提高至少五倍才能匹配AI的收益水平。德哈恩表示,该数字同时折射出机构应用新技术时面临的多重阻力。
他表示:“绝不能把最新AI模型生搬硬套进现有工作流,尤其在受监管领域。”
主动型基金经理会否退出历史舞台?
德哈恩表示,重要的是该研究综合考虑了基金经理面临的实际操作与合规限制。例如许多基金被限定只能投资大盘股。即便这些限制条件未明确排除某些机会,大型基金机构也难以高效利用交易频率较低的小盘股定价偏差获利。
总体而言,与以往的技术革命一样,德哈恩对人工智能持乐观态度,他认为AI将成为就业净创造者。投资领域亦不例外,但特定岗位正在被逐步淘汰。
高塔咨询(Hightower Advisors)首席投资策略师斯蒂芬妮·林克看好AI在科技与网络安全公司的投资价值。但她认为,即便AI技术持续完善,短期内仍无法取代其麾下的初级分析师。
她对《财富》杂志表示:“我该如何退休,让更年轻的人接替我?因为我认为我的工作绝非计算机可替代。”
德哈恩表示,主动型经理人始终有其存在空间,但随着海量资金涌入低成本、高流动性的ETF等被动投资工具,这个阵营将持续萎缩。
过去数年对股票操盘手尤为艰难,多数主动管理型基金未能跑赢蓬勃的市场。(正如林克所说的那样,数据显示在熊市中情况可能逆转。)
德哈恩表示,部分经理人确实技艺非凡,尤其考虑到有人类经理的表现击败了他们所研发的AI机器人。AI机器人主要通过调仓降险优化组合,用被动指数基金替换其不看好的头寸。事实上,当研究者将选股权完全交给AI时,其平均将42%的资金配置于指数跟踪产品。
但德哈恩始终认为,最擅长驾驭AI模型的基金经理在市场上仍有立足之地。
德哈恩表示:“或许是那些保持人类思维模式的智者,能够战胜AI。”
他补充道:“他们不会消失,只是数量将有所减少。”(财富中文网)
译者:刘进龙
审校:汪皓
• 要检验AI的潜力,不妨将金融界的“终结者”空降到20世纪90年代的华尔街。斯坦福大学(Stanford University)与波士顿学院(Boston College)的研究人员采用该方法发现,他们开发的AI机器人可通过降低投资组合风险,显著提升多数基金经理的收益回报。
人工智能究竟会增强还是取代人类劳动?各行业对此争论不休。两年前,斯坦福大学与波士顿学院的研究人员决定探究飞速发展的AI技术对职业股票操盘手的意义。他们创造了一位“AI分析师”,并允许其每季度调整逾3,300只主动管理型多元化共同基金的投资组合。
在基金存续期内,经AI机器人调整后的投资组合中,有93%的表现超越了人类经理。1990至2020年间,由AI机器人管理的基金季度超额收益(即跑赢市场的回报)比人类经理多出1,710万美元。该AI机器人仅利用财务报告、分析师预测和报价等公开数据就取得如此成果,其碾压性优势甚至令研究者本人都感到震惊。
斯坦福大学商学院会计学教授埃德·德哈恩对《财富》杂志表示:“我们在一年前得出这些结果,AI的巨大优势令我们直呼‘这不可能’。”
但德哈恩表示,经过对每个步骤和假设的反复验证,结果确凿无误。他提醒切勿过度解读,并强调其团队并非预言投资组合经理将集体被AI取代,但初级分析师可能很快面临失业危机。
身兼《会计与经济学杂志》(Journal of Accounting and Economics)总编的德哈恩表示:“我认为,五年后,枯坐办公室处理Excel表格这类工作基本会消失。”
德哈恩阐释称,传统观点认为,最成功的主动型经理人主要依靠创造性思维和广泛人脉制胜,他们通过深度把握企业与行业内外的动态,发掘财务数据之外的机遇。
德哈恩表示,新研究将样本基金经理可以掌握的会计报告、经济数据、分析师建议和卖方研究报告,提供给AI机器人,彻底颠覆了这一认知。
他表示,关键在于,AI并非通过挖掘人类可能忽略的冷门信息获利。研究者开发的“随机森林模型”持续以不同方式拆分重组数据,依托多组变量反复生成新预测。
德哈恩指出,AI仅需数小时就能完成原本需十名专业员工承担的工作,从而发现那些“隐藏于众目睽睽之下的信息”。
但该研究存在重要限制条件。一方面,AI并未与其他掌握同等技术的基金竞争。
德哈恩表示:“当所有人开始使用AI时,游戏规则将彻底改变。”
他强调该研究实为思想实验——以AI的能力为标尺,衡量人类经理因无力负担额外人力或技术投入而“错失的收益”。
换言之,检验AI潜力的方法之一,是推演若35年前就有参与者掌握该技术,行业格局将如何改写。或用德哈恩一位同行的说法:假如将金融版“终结者”(即施瓦辛格在1984年同名电影中饰演的机械杀手)送回1990年,会发生什么。
鉴于人类管理的基金平均每季度向投资者收取360万美元管理费,研究显示基金需将费用提高至少五倍才能匹配AI的收益水平。德哈恩表示,该数字同时折射出机构应用新技术时面临的多重阻力。
他表示:“绝不能把最新AI模型生搬硬套进现有工作流,尤其在受监管领域。”
主动型基金经理会否退出历史舞台?
德哈恩表示,重要的是该研究综合考虑了基金经理面临的实际操作与合规限制。例如许多基金被限定只能投资大盘股。即便这些限制条件未明确排除某些机会,大型基金机构也难以高效利用交易频率较低的小盘股定价偏差获利。
总体而言,与以往的技术革命一样,德哈恩对人工智能持乐观态度,他认为AI将成为就业净创造者。投资领域亦不例外,但特定岗位正在被逐步淘汰。
高塔咨询(Hightower Advisors)首席投资策略师斯蒂芬妮·林克看好AI在科技与网络安全公司的投资价值。但她认为,即便AI技术持续完善,短期内仍无法取代其麾下的初级分析师。
她对《财富》杂志表示:“我该如何退休,让更年轻的人接替我?因为我认为我的工作绝非计算机可替代。”
德哈恩表示,主动型经理人始终有其存在空间,但随着海量资金涌入低成本、高流动性的ETF等被动投资工具,这个阵营将持续萎缩。
过去数年对股票操盘手尤为艰难,多数主动管理型基金未能跑赢蓬勃的市场。(正如林克所说的那样,数据显示在熊市中情况可能逆转。)
德哈恩表示,部分经理人确实技艺非凡,尤其考虑到有人类经理的表现击败了他们所研发的AI机器人。AI机器人主要通过调仓降险优化组合,用被动指数基金替换其不看好的头寸。事实上,当研究者将选股权完全交给AI时,其平均将42%的资金配置于指数跟踪产品。
但德哈恩始终认为,最擅长驾驭AI模型的基金经理在市场上仍有立足之地。
德哈恩表示:“或许是那些保持人类思维模式的智者,能够战胜AI。”
他补充道:“他们不会消失,只是数量将有所减少。”(财富中文网)
译者:刘进龙
审校:汪皓
• One way to examine AI’s potential is by dropping the finance world’s version of “The Terminator” on 1990’s Wall Street. Researchers at Stanford University and Boston College took that approach and found their bot could significantly boost most fund managers’ returns by de-risking their portfolios.
Whether artificial intelligence will augment or replace human labor is fiercely debated across countless industries. Two years ago, researchers at Stanford University and Boston College decided to explore what this rapidly advancing technology could mean for professional stock pickers—so they built an “AI analyst” and gave it the chance to modify the portfolios of over 3,300 actively managed and diversified mutual funds every three months.
Ninety-three percent of the bot’s AI-modified portfolios beat the human managers over their funds’ lifetimes. From 1990 to 2020, the bot-managed funds earned $17.1 million more in quarterly alpha—or market-beating returns—than human managers. The AI achieved those results using publicly available data such as financial reports, analyst forecasts, and price quotes, surprising even the researchers themselves with the decisiveness of the outperformance.
“We had these results a year ago, and they were so large that we said, ‘This is not real,’” Ed deHaan, a professor of accounting at Stanford Graduate School of Business, told Fortune.
But going back through every step and assumption confirmed the results, deHaan said. He cautions against taking them too literally, and he stressed he and his colleagues are not predicting portfolio managers will be replaced by AI en masse. Junior analysts, however, could soon see their jobs on the chopping block.
“I don’t think sitting around, crunching Excel spreadsheets is a job that will exist in a material sense in five years,” said deHaan, managing editor of the Journal of Accounting and Economics.
Traditionally, deHaan explained, it’s believed most successful active managers beat the market by thinking creatively and having great contacts—knowing companies and industries inside and out to find opportunities not apparent in the numbers.
This new study, deHaan said, turns that logic on its head by giving the AI access to the same accounting reports, economic data, analyst recommendations, and sell-side research that managers in the sample would have had.
Crucially, the AI didn’t find gains by pulling obscure information or signals that humans would have missed, he said. Instead, the random forest model the researchers developed kept splitting and organizing data in different ways, relying on different sets of variables to repeatedly make new predictions.
Instead of hiring 10 skilled employees to do that work, deHaan said, the AI could go through the process in a matter of hours, finding what he called “information hiding in plain sight.”
There are some important caveats, though. For one, the AI didn’t compete against other funds that simultaneously had access to the same technology.
“As soon as everybody starts using it,” deHaan said, “the game changes.”
The study is a thought experiment, he emphasized, that uses the AI’s ability as a proxy for the earnings human managers “left on the table” because they couldn’t afford the additional manpower or technological investments that might have replicated it.
In other words, one way to examine AI’s potential is to reflect on what the industry would have looked like if a participant possessed the technology 35 years ago. Or, as one of deHaan’s peers put it, see what happens if you go back to 1990 and bring the finance world’s version of “The Terminator,” the cyborg assassin famously portrayed by Arnold Schwarzenegger in the 1984 film with the same name.
Given the average human-managed fund charged its investors fees of $3.6 million per quarter, the study suggests a fund would have needed to at least quintuple its fees to match the bot’s returns. The number also reflects various frictions organizations face in adopting new technology, deHaan said.
“You can’t just grab the latest AI model and chuck it into your workflow,” he said, “especially in a regulated space.”
Will active managers stick around?
Still, it’s critical that the study accounts for the practical and compliance constraints fund managers face, deHaan said. Many funds are restricted to only investing in large-cap names, for example. Even if those criteria don’t explicitly rule out certain opportunities, it might be inefficient for large managers to profit off the mispricing of smaller, less frequently traded stocks.
Overall, deHaan is optimistic artificial intelligence—like previous technological developments—will be a net job creator. That could include the investment world, he said, but certain types of roles are already becoming obsolete.
Stephanie Link, chief investment strategist at Hightower Advisors, is a bull on AI when it comes to investing in tech and cybersecurity companies. But she doesn’t think the technology, even as it gets better and better, will supplant her junior analysts anytime soon.
“How am I going to retire and have someone who’s younger than me replace me?” she told Fortune. “Because I think what I do is not replaceable by a computer.”
There will likely always be a place for active managers, deHaan said, but he sees the space continuing to winnow as huge amounts of money flow into passive investment vehicles like low-cost, highly liquid ETFs.
It’s been a tough couple of years for stock pickers, with most actively managed funds failing to match the returns of a booming market. (As Link noted, the data shows that can change during downturns.)
Some managers clearly have skill, deHaan said, especially given that some beat the AI created by him and his colleagues. The bot improved most portfolios by de-risking them, however, swapping positions it didn’t like with passive index funds. In fact, when the researchers fully outsourced stock picking to AI, it allocated an average of 42% of its funds to tracking indices.
Still, he always sees a place in the market for managers who are most effective at leveraging AI models.
“Or maybe it’s the clever human who thinks like a human and can ‘out-human’ the AI,” deHaan said.
“They’ll always be there,” he added, “probably just not as many.”