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Alpha Blue Capital
Alpha Blue Capital is a San Francisco-based systematic equity manager founded in 2016.
Alpha Blue Capital
Alpha Blue Capital was established in 2016 in San Francisco by Joonhyuk Lee and Gene H. Lee, combining expertise in quantitative finance, strategy consulting, and technology. Joonhyuk Lee's professional tenure at Goldman Sachs in cross-asset quantitative investment strategies and at McKinsey & Company informs the firm's analytical foundation. The firm operates as a quantitative equity manager, distinct from venture capital or single-family-office structures that the name might suggest. The firm manages a systematic long-only equity strategy, applying artificial intelligence and machine learning to fundamental and alternative datasets. Its model ingests vast quantities of structured and unstructured data to generate price forecasts and construct portfolios, covering sectors including technology, healthcare, and consumer. The strategy emphasizes risk-managed factor exposures. The firm's investment process is entirely model-driven, with human oversight concentrated on signal research and model refinement rather than discretionary stock-picking. Headquartered in San Francisco, Alpha Blue Capital draws from the city's deep technical talent pool. Professionals and current assets under management are not publicly disclosed. The firm's regulatory filings confirm its status as an SEC-registered investment adviser, with systematic trading as the core activity. No adjacent private vehicles, spin-outs, or philanthropic structures are publicly known. The firm's strategy operates in a fully liquid, daily-dealt format, allowing it to remain structurally simpler than many peers in the quantitative space. What structurally differentiates Alpha Blue Capital is its exclusive focus on a single systematic long-only equity sleeve at a moment when many quantitative managers have expanded into multi-strategy, private markets, or short-extension products. This concentrated mandate, paired with its San Francisco location outside the traditional quantitative hubs of the East Coast, gives it a distinct posture in the systematic equity landscape.
General information
Firm type
Asset Manager
Year founded
2016
AUM
< $500M (Altss estimate)
Location
Region
North America
Country
United States
City
San Francisco
Corporate office
San Francisco, CA, United States
Principals
Joonhyuk Lee
Chief Investment Officer & Co-Founder
Gene H. Lee
Co-Founder
Sector focus
Frequently asked questions
Who runs investment decisions at Alpha Blue Capital?
Investment decisions are driven by a systematic model developed under CIO and Co-Founder Joonhyuk Lee, whose prior experience includes cross-asset quantitative strategy at Goldman Sachs. The process removes individual discretionary stock-picking, with portfolio managers overseeing model performance, risk budgets, and signal research priorities rather than making single-name buy or sell calls.
Is the firm's strategy discretionary or purely systematic?
Alpha Blue Capital operates a purely systematic strategy. Human judgment is applied solely to research design, data acquisition, and model governance. Day-to-day portfolio construction and trade execution are automated by the proprietary machine-learning system.
Does Alpha Blue Capital manage private equity or venture capital allocations?
No. Despite its San Francisco location and a name that could imply venture investing, the firm exclusively manages liquid public equities. Its only known strategy is a long-only systematic equity fund.
What investment sectors does the strategy typically cover?
The systematic model draws from a broad universe across sectors including technology, healthcare, and consumer equities. The data-driven approach does not pre-commit to thematic or sector concentrations; exposures shift based on the model's continuous analysis of fundamentals and alternative data signals.
How does the firm use machine learning in its process?
Machine learning is central to both signal generation and portfolio construction at Alpha Blue Capital. The firm applies ML techniques to structured financial data and unstructured alternative datasets to identify predictive patterns, with the stated goal of generating consistent excess returns independent of human bias.
Profile maintained by Altss using OSINT (open-source intelligence), regulatory filings, licensed data partners, and verified direct submissions. Read the methodology. Last updated: . Continuous refresh with full update cycles at least every 30 days.
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