Building Trust in Illiquid Markets: an AI-Powered Replication of Private Equity Funds

TL;DR

This paper presents an AI-driven framework to replicate private equity fund performance using liquid strategies, aiming to improve transparency, trust, and stability in illiquid markets.

Contribution

It introduces a novel graphical model-based method that emulates private equity performance with liquid assets, enhancing transparency and systemic resilience.

Findings

Close alignment with traditional PE benchmarks

Scalable and liquid replication strategy

Supports market stability and investor confidence

Abstract

In response to growing demand for resilient and transparent financial instruments, we introduce a novel framework for replicating private equity (PE) performance using liquid, AI-enhanced strategies. Despite historically delivering robust returns, private equity's inherent illiquidity and lack of transparency raise significant concerns regarding investor trust and systemic stability, particularly in periods of heightened market volatility. Our method uses advanced graphical models to decode liquid PE proxies and incorporates asymmetric risk adjustments that emulate private equity's unique performance dynamics. The result is a liquid, scalable solution that aligns closely with traditional quarterly PE benchmarks like Cambridge Associates and Preqin. This approach enhances portfolio resilience and contributes to the ongoing discourse on safe asset innovation, supporting market stability and investor confidence.