Olga Kane is an accomplished investment industry executive with extensive experience in alternative investments, hedge funds, equity research, trading, data-driven investment strategies, product development, capital raising, and launching new businesses. She is currently a Managing Director of Synthesis, a quant investment company focusing on equity statistical arbitrage. Synthesis team develops machine learning powered research framework to extract insights from a wide range of alternative data sets. In her role, Olga oversees trading execution, data sourcing strategy, strategic partnerships, and broker/vendor relationships.
Before co-founding Synthesis in 2019, she was a Director at QST Financial, an algorithmic trading group, overseeing business development, data sourcing, broker, and vendor relations. Previously, she launched an incubator platform for early-stage quantitative hedge funds at ITI Group, a global broker-dealer. Prior to that, Olga was head of operations and investor relations for an alternative investment firm Da Vinci Capital. She started her career at Renaissance Capital as a Vice president covering electronic trading execution services.
Olga is a graduate of Baruch College Zicklin School of Business and Harvard Business School. She holds a Chartered Alternative Investment Analyst (CAIA) designation and FINRA series 65 license.
Olga is an established speaker, panelist, and guest lecturer covering fintech innovation, data-driven portfolio construction, AI and machine learning in finance. She was named among 25 most inspirational women in AI for the financial industry by Re:work.
Olga is a member of CAIA Association, CFA Society of New York, 100 Women in Finance, HBS Club of New York, HBS Angel Investors group.
More than 100 miles
Everything is negotiable
Between 2020 and 2030, more than $68 trillion in wealth will transfer from boomers to millennials and Gen Z. Younger investors have different goals and favor new investment strategies. Investment advisors need to adjust their approach to portfolio construction to incorporate cutting-edge tech solutions, alternative investments, and sustainable impact exposure.
Most of the existing ESG ratings have little to do with actual corporate responsibility. A more granular data-driven approach is required to quantify the true impact of business behavior. Separate factors derived from multiple data sources can accurately measure the economic, human, and environmental costs of corporate decisions.
Institutional investment managers use generative AI to improve efficiency in writing code, translate between programming languages, analyze internal and external data, facilitate client communication, and more.
Data and quantitative techniques enable more dynamic and rigorous thematic exposure
Trends and use cases of AI and big data technologies in investments