View the Schedule of Past Presentations.<\/a><\/p>\nWednesday, September 9, 2026<\/h6>\n
Title: <\/b>From HFT to Fintech: Lessons in Entrepreneurship & Risk-Taking in Finance<\/span><\/p>\nSpeaker: <\/b>Christina Qi, <\/span>Databento<\/span><\/p>\nChristina Qi is the Co-Founder and CEO of Databento, a financial data platform serving thousands of institutions worldwide. Prior to Databento, she co-founded Domeyard LP, a hedge fund focused on high-frequency trading, which grew to trade billions of dollars per day across global markets before winding down after a decade of service. Christina is a board member of her alma mater MIT, WGBH (National Public Radio\/PBS), and a visiting lecturer at several universities. She graduated from MIT in 2013 and lives in Utah with 10 chickens, 2 turtles, and a 15-year-old dog. She enjoys listening to classical piano music, watching anime, and playing rhythm games.<\/span><\/p>\nAbstract:<\/b><\/p>\n
What does it take to launch your own venture in finance – and is it worth the risk? In this talk, Christina Qi will walk through her unconventional journey from co-founding Domeyard LP, a high-frequency trading hedge fund, to starting Databento, a provider of real-time and historical market data. Drawing from personal experiences, Christina will candidly discuss the highs and lows of entrepreneurship in finance – from raising capital and hiring a team, to the day-to-day differences (& differing career trajectories) between having an alpha-chasing job vs. a product-oriented job. She\u2019ll also share lessons learned from failure, insights into compensation and risk trade-offs, whether location matters or not, and how to identify and validate an idea worth building. This session will provide students with a grounded, realistic view of what it means to forge your own path – and why sometimes, the biggest leaps of faith can lead to the most valuable growth.<\/b><\/p>\nWednesday, September 16, 2026<\/h6>\n
Title: <\/b>Sell-Side Sales & Trading<\/span><\/p>\nSpeaker: <\/b>Johnny Lee<\/span><\/p>\nJohnny Lee worked at Morgan Stanley as a trader for 23 years from 2000 to 2023. He was the Head of USD Interest Rate Structured Rates. He oversaw one of the largest trading books on Wall Street through the financial crisis and COVID. He ran a global business from New York, working with teams in Hong Kong, Tokyo, and London. His focus was three parts \u2013 making P&L, driving market share, and managing the risk for all non-linear products in US rates \u2013 from gamma and vega to exotics and hybrids. He retired in 2023 to focus on enjoyment of life.<\/span><\/p>\nAbstract:<\/b><\/p>\n
What is the Sell-Side? What is their investment objective? In a World of ETF\u2019s, passive investing, and electronic trading, where does the sell-side fit in? What is an investor versus a dealer versus a broker? How are dealers adapting to ever-more-transparent markets, and ever-smaller bid\/offer spreads? How did the sell-side separate from proprietary trading and how is it evolving as of late? What are some natural advantages and disadvantages of the sell-side? Finally, should you consider a career on the sell-side? We will be discussing these broad topics by taking some real-life examples from Johnny\u2019s career as a market maker for over 20 years in Treasury bonds, swaps, options, exotics, and hybrids.<\/b><\/p>\nWednesday, September 23, 2026<\/h6>\n
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Speaker: <\/b>Justin Hott, <\/span>Hudson River Trading<\/span><\/p>\nAbstract:<\/b><\/p>\nWednesday, September 30, 2026<\/h6>\n
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Abstract:<\/b><\/p>\nWednesday, October 7, 2026<\/h6>\n
Title: <\/b>Structured Covariance Estimation and Applications in Finance<\/span><\/p>\nSpeaker: <\/b>Jeremy Shen, <\/span>Columbia University<\/span><\/p>\nJeremy Shen is currently on garden leave from his former post as a Quantitative Research Lead at Citadel, where he led a team that focused on forecasting and trading futures & currencies. Prior to Citadel, he held systematic macro research roles at Two Sigma Investments. He holds a PhD in Statistics from Stanford University.<\/span><\/p>\nAbstract:<\/b><\/p>\n
Estimation of high-dimensional covariance matrices is a non-trivial problem that finds applications in the broader domain of systematic investing. In this talk, we review public-domain methods for estimating covariance that commonly arise in investment problems. We will discuss methodologically appropriate remedies for practical issues, such as non-random missing data and corrupted observations.<\/b><\/p>\nWednesday, October 14, 2026<\/span><\/h6>\nTitle: <\/b><\/p>\n
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Abstract:<\/b><\/p>\nWednesday, October 21, 2026<\/h6>\n
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Abstract:<\/b><\/p>\nWednesday, October 28, 2026<\/h6>\n
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Abstract:<\/b><\/p>\nWednesday, November 4, 2026<\/h6>\n
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Abstract:<\/b><\/p>\nWednesday, November 11, 2026<\/h6>\n
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Abstract:<\/b><\/p>\nWednesday, November 18, 2026<\/h6>\n
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Abstract:<\/b><\/p>\nWednesday, November 25, 2026 – no classes<\/span><\/h6>\nWednesday, December 9, 2026<\/h6>\n
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