Alternative investment firm managing $20B across quantitative and discretionary strategies
Graham Capital is a multi-strategy alternative investment manager built on a quantitative and discretionary foundation, managing roughly $20 billion for institutional and individual clients. The tech stack—Python, C++, Bloomberg, Kubernetes, AWS/Azure/GCP—reflects a computationally intensive trading operation, while active project work on execution strategies, market microstructure research, and systematic signal generation shows heavy focus on reducing the gap between simulated and live trading performance. Pain-point clustering around execution costs, trading system performance, and reconciliation accuracy reveals operational friction typical of high-frequency systematic shops.
Graham Capital Management was founded in 1994 and operates as an alternative investment firm offering quantitative and discretionary strategies to global pensions, sovereign wealth funds, endowments, foundations, and qualified individual investors. Headquartered in Rowayton, Connecticut, the firm employs 201–500 people across finance, research, data, engineering, and operations functions. Current project work spans portfolio construction, systematic signal development for futures and FX markets, and market microstructure research. The firm is expanding geographically, with an active hub launch underway in Hong Kong alongside existing operations in the United States and United Kingdom.
Python, C++, VBA, Bloomberg, Kubernetes, Docker, AWS, Azure, GCP, SQL Server, .NET Framework, Angular, and Vue. The mix reflects both quantitative research (Python, C++) and enterprise trading infrastructure (Bloomberg, Kubernetes).
Rowayton, Connecticut. The firm also operates in the United Kingdom and is launching a new hub in Hong Kong as of the input date.
Active projects include portfolio construction optimization, proprietary execution strategies for futures and FX, intraday systematic trading strategies, market microstructure research, and reducing the performance gap between simulated and live trading results.
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