Bridgewater Launches $2 Billion Fund Run by Machine Learning

Bridgewater Associates, a leading hedge fund managed by CEO Nir Bar Dea, has launched a new fund that utilizes machine learning as its primary decision-making tool. The fund, which debuted with nearly $2 billion in capital from more than a dozen clients, began trading on Monday.

Bridgewater has been developing this technology for over a decade and has been testing the strategy since late last year with a small portion of its main Pure Alpha fund. The new fund will also incorporate models developed by OpenAI, Anthropic, and Perplexity, among others. The fund will be run by co-chief investment officer Greg Jensen.

The push into machine learning is part of a broader transition at Bridgewater, led by Bar Dea since founder Ray Dalio ceded control in late 2022. This transition has also included a major management overhaul. The Pure Alpha fund, which has been mostly underperforming for over a decade, has climbed 14.4% this year through June 26, after a 7.6% loss in 2023.

The use of machine learning has the potential to change the hiring strategy and composition of staff at Bridgewater, with more data scientists being brought on board. Jensen, who has been thinking about the impact of machine learning on investing since 2012, has been a key driver of this initiative. He has also invested in OpenAI and Anthropic.

Bridgewater has hired Jasjeet Sekhon, a professor at Yale University, as its chief scientist for the initiative. The firm has also formed a division called Artificial Investment Associate Labs (AIA), which combines large language models, machine learning data models, and reasoning tools. Through AIA, Bridgewater has developed a way to use AI to understand causal relationships in markets and generate returns.

Jensen acknowledges the limitations of the machine learning strategy, stating that humans will still be responsible for risk management, data acquisition, and trade execution to ensure a complete investing process. He also notes that large language models have the problem of hallucination, as they do not understand concepts like greed, fear, or cause-and-effect relationships.

Tests using the AIA systems have included asking how asset prices would be affected if Donald Trump wins the November election and raises tariffs on Chinese goods. Bridgewater has also used the AIA machine learning process to calculate the impact on bond prices under the Federal Reserve’s quantitative tightening process. Jensen believes that machines will be better at finding patterns across times and across countries.

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