Welcome to Karana Capital
A New York-based hedge fund that employs a time-tested quantamental strategy delivering excellent returns

WHY KARANA
Industry Expertise
Our team is composed of highly experienced professionals in stock market trading, data analysis, risk management, software engineering, and hedge fund management.

Effective Strategy
Our AI-powered quantamental trading strategy has consistently delivered strong performance across different market cycles, providing excellent returns in both bull and bear markets.

Unique Edge
Our one-of-a-kind approach is designed to be uncorrelated to broader market trends and is rarely replicated by other funds, giving us a competitive edge in continuously generating alpha.


Strategy
Karana Capital's AI-powered quantamental approach seamlessly integrates behavioral finance, game theory, market sentiment analysis, large language models, fundamental research, and technical analysis. Across varying market cycles, the strategy is designed to identify high-probability trading opportunities—aiming to generate ultra-alpha and market-uncorrelated returns for investors while actively managing risks.
Core Philosophy

Factors and Signals

Focused Instruments

Risk Management


Leadership

Yuxi Li is the Founder, CEO, and CIO of Karana Capital. A self-made trader who began her investment journey with minimal capital and a non-traditional Wall Street background, she built her track record through sharp trading instincts, emotional discipline, mental resilience, and a deep understanding of market psychology and dynamics. Backed by a strong mathematical foundation, she has an exceptional ability to quickly spot patterns and relationships within complex data—an edge that drives her high-speed, high-conviction decision-making. Starting with equities and options trading, she gradually expanded into strategy design and evaluation—ultimately founding and managing her own hedge fund.
At Karana Capital, Yuxi oversees portfolio management, strategy development, talent cultivation, and investor relations. She brings a fresh perspective to markets, and applies a creative, nuance-oriented approach to trading. Her style reflects a deliberate balance between bold conviction and prudent risk management. Known for her "sniper-like" trading style, Yuxi is highly selective and patiently waits for asymmetric, high-conviction opportunities—striking with agility and precision the moment conditions align. She specializes in identifying market inflection points, drawing on a multi-dimensional framework that includes macro fundamentals, technicals, sentiment, and cyclical analysis.
A strong believer in innovation, Yuxi is deeply engaged in frontier technologies and actively empowers herself with tools like AI and machine learning to sharpen her trading process and decision-making. She continually explores how emerging technologies can enhance both market insights and operational edge.
Yuxi holds a bachelor’s degree in Finance from Zhejiang Gongshang University in China and a master’s degree in Education from Columbia University. Beyond her role as a hedge fund manager, she is a profoundly creative person who expresses herself through the arts—particularly music, dance, poetry, and photography.
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Yuxi is supported by a highly experienced team of quant analysts and stock market traders, whose expertise spans diverse backgrounds in both finance and technology. The team includes a former Silicon Valley engineer - mentee of Jim Simons (founder of Renaissance Technologies), a former financial advisor from Morgan Stanley & Merrill Lynch, a former software engineer from China International Capital Corporation (CICC), a former clinical psychologist, as well as a former C-level human resources executive from Yahoo. The team members’ individual trading experience ranges from 10 to 30 years, accumulating to over 100 years of combined experience. Renowned for their deep market insight, the team employs a precision-driven, sniper-like approach—patiently waiting for high-probability opportunities and executing trades with discipline and precision.
