Renaissance Technologies famed hedge fund, Medallion, along with other AI-driven funds including Citadel, D.E. Shaw and Two Sigma, are on the verge of facing off against a new generational hedge fund fueled by the latest AI technologies with one key difference: a 100 percent model-driven, alpha-learning, AI algorithm designed to pinpoint market demand projections while actively applying real-time data analysis insights without human interruptions. The new hedge fund is Project One.
The brainchild of Andrew Sobko and Rami Jachi, the Project One hedge fund, targets $1B under management by 2021 and projects an average of 60 percent annualized returns, surpassing the success and performance of the Medallion predecessor. Interested investors must meet the minimum $1M threshold.
The Project One hedge fund is built to fuel performance and provide resilience toward volatile markets due to global unrest or global pandemics that have roiled markets of late. The algorithm is designed with an alpha-learning AI model that continues to develop and apply all future predictive models without human involvement. Comparatively, traditional hedge funds rely on AI algorithms that become obsolete in a short period due to its need for human management in the process of how data is collected and analyzed.
“If you missed out on Medallion, don’t miss Project One,” says Andrew Sobko, CEO and Head of Business Development, Project One Capital. “We’ve removed the error-laden human component from this fund and employed an AI algorithm with alpha-learning capabilities toward market analysis that adapts and applies its projective models in real-time. With the sophistication of technology applied in this fund, other hedge funds must embrace AI or die.”
One of the challenges facing the use of AI in hedge funds is the inability of human programmers to keep up with its speed and sophistication. The Project One hedge fund removes all human interaction and management, relying on the algorithm’s alpha-learning and adaptive technologies.
“Through our study of praxeology, there is no guessing,” said Sobko. “We are fully aware of the facts associated with human behavior and involvement, which is why we moved to eliminate the error-prone component from our proprietary algorithm.”
During testing of the Project One’s proprietary alpha-learning AI market fund algorithm, a return of 160 percent was achieved over three months, reporting limited downsides. Unlike many other hedge fund analytical algorithms, Project One analyzes, projects, and applies volumes of direct and peripheral market industry data and acts in real-time without human interaction.
According to Preqin Pro, hedge funds that use AI to help with trading have been outperforming the hedge fund benchmark with three-year cumulative returns at +26.96 percent over the past three years.