The ‘Alternatives Turing Test’: How BlackRock Is Using AI to Crack Opaque Private Markets

Using artificial intelligence and data science, investors will be able to bring the portfolio construction and risk modeling techniques that they have long used for public securities to alternatives like private equity and venture capital, according to research published by BlackRock.

Private market investors have faced barriers to improving their portfolio construction, including illiquidity, opaque valuations, and a lack of public information. But the BlackRock paper, expected to be published Friday, offers a portfolio framework investors can use for alternatives. By using AI and data science techniques, investors can forecast the performance of potential investment opportunities in different asset classes over time and optimize various combinations of funds according to their risk appetite, BlackRock said.

Pam Chan, chief investment officer and global head of BlackRock’s Alternative Solutions Group, which has $8 billion in client assets, said it didn’t matter quite as much in the past if investors used rules of thumb or other approaches to build alternatives portfolios because they were ultimately a small part of the whole. But now investors are increasing their allocations to alternatives, as well as putting money into new varieties of funds, including music royalties, aviation finance, and agriculture.

“食欲增加mount of alternatives is very high today — and that’s an understatement,” said Chan, in an interview. “Alternatives have become much more versatile. That has increased the importance of thinking through one’s alternatives portfolio as portion of the whole and not as something off to the side.”

Chan stressed that alternatives are often meant to be high returning and are a big part of the risk exposure for most investors. As such, it’s important for investors to understand how alternatives specifically contribute to risk, as well as the impact of illiquidity.

“As allocations to private markets have increased, many investors have struggled to develop portfolio construction methodologies that account for the unique aspects of private market investing,” wrote the authors of the paper, which includes professors from Stanford University, who advise BlackRock AI Labs. “Some have ignored quantitative portfolio construction altogether, opting for a more qualitative approach, while others have attempted to use standard quantitative methods developed for liquid investments.”

The authors pointed out that some of the standard quant methods use metrics like internal rates of return, which don’t fully represent the behavior of private assets.

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但是，对衡量方案有巨大的利益，包括投资者能够在经济周期中的某些时期进行战术地分配给低估或更具吸引力的机会。就像公开交易的股票和债券一样，私募股权，私人信贷，基础设施和其他替代方案已经交付了往复日常差异的回报。

BlackRock’s paper addresses limitations including illiquidity, which prevents investors from easily rebalancing their portfolios. Because of that, BlackRock argued that it’s even more important to bring a new approach to these portfolios.

But BlackRock is careful to acknowledge the current limits, even with AI.

“与传统的市场证券不同，私人资产类别通常需要专门的建模技术和仔细策划数据，”报告说。“重要的是，任何对建模的定量方法都应通过经验丰富的私人市场投资者的判断来锻炼。”

Chan described BlackRock’s approach as an “Alternatives Turing Test,” referencing the test proposed by mathematician and computer scientist Alan Turing to judge the results of a computer by determining whether it’s indistinguishable from that of a human being.

“我们与长期以来一直投资这些资产课程的人合作，”她说。“如果他们说，'我不会认识到'，然后我们回到绘图板，并确保模型本身不会被带走。”