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          “終結(jié)者”AI基金經(jīng)理來了:能擊敗93%的人類操盤手

          Greg McKenna
          2025-06-08

          要檢驗(yàn)AI的潛力,不妨將金融界的“終結(jié)者”空降到20世紀(jì)90年代的華爾街。

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          圖片來源:CBS via Getty Images

          ? 要檢驗(yàn)AI的潛力,不妨將金融界的“終結(jié)者”空降到20世紀(jì)90年代的華爾街。斯坦福大學(xué)(Stanford University)與波士頓學(xué)院(Boston College)的研究人員采用該方法發(fā)現(xiàn),他們開發(fā)的AI機(jī)器人可通過降低投資組合風(fēng)險(xiǎn),顯著提升多數(shù)基金經(jīng)理的收益回報(bào)。

          人工智能究竟會(huì)增強(qiáng)還是取代人類勞動(dòng)?各行業(yè)對(duì)此爭(zhēng)論不休。兩年前,斯坦福大學(xué)與波士頓學(xué)院的研究人員決定探究飛速發(fā)展的AI技術(shù)對(duì)職業(yè)股票操盤手的意義。他們創(chuàng)造了一位“AI分析師”,并允許其每季度調(diào)整逾3,300只主動(dòng)管理型多元化共同基金的投資組合。

          在基金存續(xù)期內(nèi),經(jīng)AI機(jī)器人調(diào)整后的投資組合中,有93%的表現(xiàn)超越了人類經(jīng)理。1990至2020年間,由AI機(jī)器人管理的基金季度超額收益(即跑贏市場(chǎng)的回報(bào))比人類經(jīng)理多出1,710萬美元。該AI機(jī)器人僅利用財(cái)務(wù)報(bào)告、分析師預(yù)測(cè)和報(bào)價(jià)等公開數(shù)據(jù)就取得如此成果,其碾壓性優(yōu)勢(shì)甚至令研究者本人都感到震驚。

          斯坦福大學(xué)商學(xué)院會(huì)計(jì)學(xué)教授埃德·德哈恩對(duì)《財(cái)富》雜志表示:“我們?cè)谝荒昵暗贸鲞@些結(jié)果,AI的巨大優(yōu)勢(shì)令我們直呼‘這不可能’?!?/p>

          但德哈恩表示,經(jīng)過對(duì)每個(gè)步驟和假設(shè)的反復(fù)驗(yàn)證,結(jié)果確鑿無誤。他提醒切勿過度解讀,并強(qiáng)調(diào)其團(tuán)隊(duì)并非預(yù)言投資組合經(jīng)理將集體被AI取代,但初級(jí)分析師可能很快面臨失業(yè)危機(jī)。

          身兼《會(huì)計(jì)與經(jīng)濟(jì)學(xué)雜志》(Journal of Accounting and Economics)總編的德哈恩表示:“我認(rèn)為,五年后,枯坐辦公室處理Excel表格這類工作基本會(huì)消失?!?/p>

          德哈恩闡釋稱,傳統(tǒng)觀點(diǎn)認(rèn)為,最成功的主動(dòng)型經(jīng)理人主要依靠創(chuàng)造性思維和廣泛人脈制勝,他們通過深度把握企業(yè)與行業(yè)內(nèi)外的動(dòng)態(tài),發(fā)掘財(cái)務(wù)數(shù)據(jù)之外的機(jī)遇。

          德哈恩表示,新研究將樣本基金經(jīng)理可以掌握的會(huì)計(jì)報(bào)告、經(jīng)濟(jì)數(shù)據(jù)、分析師建議和賣方研究報(bào)告,提供給AI機(jī)器人,徹底顛覆了這一認(rèn)知。

          他表示,關(guān)鍵在于,AI并非通過挖掘人類可能忽略的冷門信息獲利。研究者開發(fā)的“隨機(jī)森林模型”持續(xù)以不同方式拆分重組數(shù)據(jù),依托多組變量反復(fù)生成新預(yù)測(cè)。

          德哈恩指出,AI僅需數(shù)小時(shí)就能完成原本需十名專業(yè)員工承擔(dān)的工作,從而發(fā)現(xiàn)那些“隱藏于眾目睽睽之下的信息”。

          但該研究存在重要限制條件。一方面,AI并未與其他掌握同等技術(shù)的基金競(jìng)爭(zhēng)。

          德哈恩表示:“當(dāng)所有人開始使用AI時(shí),游戲規(guī)則將徹底改變?!?/p>

          他強(qiáng)調(diào)該研究實(shí)為思想實(shí)驗(yàn)——以AI的能力為標(biāo)尺,衡量人類經(jīng)理因無力負(fù)擔(dān)額外人力或技術(shù)投入而“錯(cuò)失的收益”。

          換言之,檢驗(yàn)AI潛力的方法之一,是推演若35年前就有參與者掌握該技術(shù),行業(yè)格局將如何改寫。或用德哈恩一位同行的說法:假如將金融版“終結(jié)者”(即施瓦辛格在1984年同名電影中飾演的機(jī)械殺手)送回1990年,會(huì)發(fā)生什么。

          鑒于人類管理的基金平均每季度向投資者收取360萬美元管理費(fèi),研究顯示基金需將費(fèi)用提高至少五倍才能匹配AI的收益水平。德哈恩表示,該數(shù)字同時(shí)折射出機(jī)構(gòu)應(yīng)用新技術(shù)時(shí)面臨的多重阻力。

          他表示:“絕不能把最新AI模型生搬硬套進(jìn)現(xiàn)有工作流,尤其在受監(jiān)管領(lǐng)域。”

          主動(dòng)型基金經(jīng)理會(huì)否退出歷史舞臺(tái)?

          德哈恩表示,重要的是該研究綜合考慮了基金經(jīng)理面臨的實(shí)際操作與合規(guī)限制。例如許多基金被限定只能投資大盤股。即便這些限制條件未明確排除某些機(jī)會(huì),大型基金機(jī)構(gòu)也難以高效利用交易頻率較低的小盤股定價(jià)偏差獲利。

          總體而言,與以往的技術(shù)革命一樣,德哈恩對(duì)人工智能持樂觀態(tài)度,他認(rèn)為AI將成為就業(yè)凈創(chuàng)造者。投資領(lǐng)域亦不例外,但特定崗位正在被逐步淘汰。

          高塔咨詢(Hightower Advisors)首席投資策略師斯蒂芬妮·林克看好AI在科技與網(wǎng)絡(luò)安全公司的投資價(jià)值。但她認(rèn)為,即便AI技術(shù)持續(xù)完善,短期內(nèi)仍無法取代其麾下的初級(jí)分析師。

          她對(duì)《財(cái)富》雜志表示:“我該如何退休,讓更年輕的人接替我?因?yàn)槲艺J(rèn)為我的工作絕非計(jì)算機(jī)可替代。”

          德哈恩表示,主動(dòng)型經(jīng)理人始終有其存在空間,但隨著海量資金涌入低成本、高流動(dòng)性的ETF等被動(dòng)投資工具,這個(gè)陣營(yíng)將持續(xù)萎縮。

          過去數(shù)年對(duì)股票操盤手尤為艱難,多數(shù)主動(dòng)管理型基金未能跑贏蓬勃的市場(chǎng)。(正如林克所說的那樣,數(shù)據(jù)顯示在熊市中情況可能逆轉(zhuǎn)。)

          德哈恩表示,部分經(jīng)理人確實(shí)技藝非凡,尤其考慮到有人類經(jīng)理的表現(xiàn)擊敗了他們所研發(fā)的AI機(jī)器人。AI機(jī)器人主要通過調(diào)倉降險(xiǎn)優(yōu)化組合,用被動(dòng)指數(shù)基金替換其不看好的頭寸。事實(shí)上,當(dāng)研究者將選股權(quán)完全交給AI時(shí),其平均將42%的資金配置于指數(shù)跟蹤產(chǎn)品。

          但德哈恩始終認(rèn)為,最擅長(zhǎng)駕馭AI模型的基金經(jīng)理在市場(chǎng)上仍有立足之地。

          德哈恩表示:“或許是那些保持人類思維模式的智者,能夠戰(zhàn)勝AI?!?/p>

          他補(bǔ)充道:“他們不會(huì)消失,只是數(shù)量將有所減少?!保ㄘ?cái)富中文網(wǎng))

          譯者:劉進(jìn)龍

          審校:汪皓

          ? 要檢驗(yàn)AI的潛力,不妨將金融界的“終結(jié)者”空降到20世紀(jì)90年代的華爾街。斯坦福大學(xué)(Stanford University)與波士頓學(xué)院(Boston College)的研究人員采用該方法發(fā)現(xiàn),他們開發(fā)的AI機(jī)器人可通過降低投資組合風(fēng)險(xiǎn),顯著提升多數(shù)基金經(jīng)理的收益回報(bào)。

          人工智能究竟會(huì)增強(qiáng)還是取代人類勞動(dòng)?各行業(yè)對(duì)此爭(zhēng)論不休。兩年前,斯坦福大學(xué)與波士頓學(xué)院的研究人員決定探究飛速發(fā)展的AI技術(shù)對(duì)職業(yè)股票操盤手的意義。他們創(chuàng)造了一位“AI分析師”,并允許其每季度調(diào)整逾3,300只主動(dòng)管理型多元化共同基金的投資組合。

          在基金存續(xù)期內(nèi),經(jīng)AI機(jī)器人調(diào)整后的投資組合中,有93%的表現(xiàn)超越了人類經(jīng)理。1990至2020年間,由AI機(jī)器人管理的基金季度超額收益(即跑贏市場(chǎng)的回報(bào))比人類經(jīng)理多出1,710萬美元。該AI機(jī)器人僅利用財(cái)務(wù)報(bào)告、分析師預(yù)測(cè)和報(bào)價(jià)等公開數(shù)據(jù)就取得如此成果,其碾壓性優(yōu)勢(shì)甚至令研究者本人都感到震驚。

          斯坦福大學(xué)商學(xué)院會(huì)計(jì)學(xué)教授埃德·德哈恩對(duì)《財(cái)富》雜志表示:“我們?cè)谝荒昵暗贸鲞@些結(jié)果,AI的巨大優(yōu)勢(shì)令我們直呼‘這不可能’?!?/p>

          但德哈恩表示,經(jīng)過對(duì)每個(gè)步驟和假設(shè)的反復(fù)驗(yàn)證,結(jié)果確鑿無誤。他提醒切勿過度解讀,并強(qiáng)調(diào)其團(tuán)隊(duì)并非預(yù)言投資組合經(jīng)理將集體被AI取代,但初級(jí)分析師可能很快面臨失業(yè)危機(jī)。

          身兼《會(huì)計(jì)與經(jīng)濟(jì)學(xué)雜志》(Journal of Accounting and Economics)總編的德哈恩表示:“我認(rèn)為,五年后,枯坐辦公室處理Excel表格這類工作基本會(huì)消失?!?/p>

          德哈恩闡釋稱,傳統(tǒng)觀點(diǎn)認(rèn)為,最成功的主動(dòng)型經(jīng)理人主要依靠創(chuàng)造性思維和廣泛人脈制勝,他們通過深度把握企業(yè)與行業(yè)內(nèi)外的動(dòng)態(tài),發(fā)掘財(cái)務(wù)數(shù)據(jù)之外的機(jī)遇。

          德哈恩表示,新研究將樣本基金經(jīng)理可以掌握的會(huì)計(jì)報(bào)告、經(jīng)濟(jì)數(shù)據(jù)、分析師建議和賣方研究報(bào)告,提供給AI機(jī)器人,徹底顛覆了這一認(rèn)知。

          他表示,關(guān)鍵在于,AI并非通過挖掘人類可能忽略的冷門信息獲利。研究者開發(fā)的“隨機(jī)森林模型”持續(xù)以不同方式拆分重組數(shù)據(jù),依托多組變量反復(fù)生成新預(yù)測(cè)。

          德哈恩指出,AI僅需數(shù)小時(shí)就能完成原本需十名專業(yè)員工承擔(dān)的工作,從而發(fā)現(xiàn)那些“隱藏于眾目睽睽之下的信息”。

          但該研究存在重要限制條件。一方面,AI并未與其他掌握同等技術(shù)的基金競(jìng)爭(zhēng)。

          德哈恩表示:“當(dāng)所有人開始使用AI時(shí),游戲規(guī)則將徹底改變。”

          他強(qiáng)調(diào)該研究實(shí)為思想實(shí)驗(yàn)——以AI的能力為標(biāo)尺,衡量人類經(jīng)理因無力負(fù)擔(dān)額外人力或技術(shù)投入而“錯(cuò)失的收益”。

          換言之,檢驗(yàn)AI潛力的方法之一,是推演若35年前就有參與者掌握該技術(shù),行業(yè)格局將如何改寫。或用德哈恩一位同行的說法:假如將金融版“終結(jié)者”(即施瓦辛格在1984年同名電影中飾演的機(jī)械殺手)送回1990年,會(huì)發(fā)生什么。

          鑒于人類管理的基金平均每季度向投資者收取360萬美元管理費(fèi),研究顯示基金需將費(fèi)用提高至少五倍才能匹配AI的收益水平。德哈恩表示,該數(shù)字同時(shí)折射出機(jī)構(gòu)應(yīng)用新技術(shù)時(shí)面臨的多重阻力。

          他表示:“絕不能把最新AI模型生搬硬套進(jìn)現(xiàn)有工作流,尤其在受監(jiān)管領(lǐng)域?!?/p>

          主動(dòng)型基金經(jīng)理會(huì)否退出歷史舞臺(tái)?

          德哈恩表示,重要的是該研究綜合考慮了基金經(jīng)理面臨的實(shí)際操作與合規(guī)限制。例如許多基金被限定只能投資大盤股。即便這些限制條件未明確排除某些機(jī)會(huì),大型基金機(jī)構(gòu)也難以高效利用交易頻率較低的小盤股定價(jià)偏差獲利。

          總體而言,與以往的技術(shù)革命一樣,德哈恩對(duì)人工智能持樂觀態(tài)度,他認(rèn)為AI將成為就業(yè)凈創(chuàng)造者。投資領(lǐng)域亦不例外,但特定崗位正在被逐步淘汰。

          高塔咨詢(Hightower Advisors)首席投資策略師斯蒂芬妮·林克看好AI在科技與網(wǎng)絡(luò)安全公司的投資價(jià)值。但她認(rèn)為,即便AI技術(shù)持續(xù)完善,短期內(nèi)仍無法取代其麾下的初級(jí)分析師。

          她對(duì)《財(cái)富》雜志表示:“我該如何退休,讓更年輕的人接替我?因?yàn)槲艺J(rèn)為我的工作絕非計(jì)算機(jī)可替代?!?/p>

          德哈恩表示,主動(dòng)型經(jīng)理人始終有其存在空間,但隨著海量資金涌入低成本、高流動(dòng)性的ETF等被動(dòng)投資工具,這個(gè)陣營(yíng)將持續(xù)萎縮。

          過去數(shù)年對(duì)股票操盤手尤為艱難,多數(shù)主動(dòng)管理型基金未能跑贏蓬勃的市場(chǎng)。(正如林克所說的那樣,數(shù)據(jù)顯示在熊市中情況可能逆轉(zhuǎn)。)

          德哈恩表示,部分經(jīng)理人確實(shí)技藝非凡,尤其考慮到有人類經(jīng)理的表現(xiàn)擊敗了他們所研發(fā)的AI機(jī)器人。AI機(jī)器人主要通過調(diào)倉降險(xiǎn)優(yōu)化組合,用被動(dòng)指數(shù)基金替換其不看好的頭寸。事實(shí)上,當(dāng)研究者將選股權(quán)完全交給AI時(shí),其平均將42%的資金配置于指數(shù)跟蹤產(chǎn)品。

          但德哈恩始終認(rèn)為,最擅長(zhǎng)駕馭AI模型的基金經(jīng)理在市場(chǎng)上仍有立足之地。

          德哈恩表示:“或許是那些保持人類思維模式的智者,能夠戰(zhàn)勝AI?!?/p>

          他補(bǔ)充道:“他們不會(huì)消失,只是數(shù)量將有所減少。”(財(cái)富中文網(wǎng))

          譯者:劉進(jìn)龍

          審校: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 “l(fā)eft 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.”

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