Aadit Narayanaswamy
Quantitative Research Intern at Cerebellum Capital, Inc
Quant Researcher
For work, I find signals in noisy backgrounds. In my free time, I apply tools from theoretical computer science and statistics to solve problems in biotech. Recently graduated from UC Berkeley.

If you have an opportunity in mind or just want to chat, contact me at aadit.narayanaswamy@berkeley.edu
Cerebellum Capital, Inc
https://www.linkedin.com/company/cerebellum-capital-inc
Focused on signals from NBBO (National Best Bid and Offer).
San Francisco, California
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Quantitative Research Intern
Teza Technologies
https://www.linkedin.com/company/teza-technologies
Part of the Alternative Data Group, focusing on sentiment analysis.
San Francisco Bay Area
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Quantitative Research Intern
Parade (Dray)
https://www.linkedin.com/company/paradeai
Co-wrote a case study on commoditization in the transportation industry. Was presented to several multimillion dollar brokerages as a method of capturing business.
Belmont, California
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Business and Operations Intern
Optimal Asset Management, Inc
https://www.linkedin.com/company/optimal-asset-management-inc
Created higher performing portfolios for groups of under-served investors using Optimal's factor-based portfolio software, FactorAllocator.
Los Altos, California
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Finance Intern
Stanford University School of Medicine
https://www.linkedin.com/company/stanford-university-school-of-medicine
Researched transcription factor induced neuronal differentiation.
Stanford, California
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Research Assistant, Wernig Lab
Mathematics and Data Science
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University of California, Berkeley
https://www.linkedin.com/school/uc-berkeley/
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Palo Alto High School
https://www.linkedin.com/school/palo-alto-high-school/
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Google Case Competition - Finalist
Kyocera
Kyocera Case Competition - Finalist
SOMAmetrics
SOMAmetrics Case Competion - Finalist
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Infosys Case Competition - 1st Place
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National AP Scholar
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President's Volunteer Service Award - Gold
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Eagle Scout Award
Applied Data Science and Machine Learning
IEOR 135
Computing with Data
Statistics 133
Concepts of Probability
Statistics 134
Decision Analysis
IEOR 166
Discrete Mathematics
Math 55
Healthcare Economics
Economics 157
Introduction to Financial Engineering
IEOR 221
Introduction to Machine Learning
CS 189
Linear Algebra
Math 110
Linear Programming and Network Flows
IEOR 162
Mathematical Theory for High Frequency Trading
IEOR 222
Microeconomic Analysis
Economics 100A
Portfolio Optimization
IEOR 224
Stochastic Processes
Statistics 150
Built low-turnover multifactor model trading GICS ETFs. Sharpe of 1.84 out-of-sample, a statistically significant improvement from our control model (Sharpe 0.82).
Multifactor ETF Model
Built a model for Medicare-certified healthcare providers that predicts CMS Star Rating (for any of 54 treatment courses) with ~95% accuracy (on average) out-of-sample, with no given treatment having lower than ~80% accuracy OOS.
Predicting CMS Star Rating
Built model using scraped polling data and financial contribution data. Predicted winners of the 2018 Midterm Elections (OOS) with ~94% accuracy several weeks in advance.
Predicting Winners of the 2018 Midterm Elections
Education
Buddies4Math
Helped increase Mariano Castro Elementary's state test scores by 9% over three years.
Activities Coordinator
UC Berkeley Data Science BA Alumni
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https://www.linkedin.com/groups/13726010
UC Berkeley Economics
https://media-exp1.licdn.com/dms/image/C5607AQEHBlaAaegW8g/group-logo_image-shrink_200x200/0/1631430136189?e=1647691200&v=beta&t=D0LKtJE0Nls0DItxPUzWxCHHrl98XU8tjFquChXC4uE
https://www.linkedin.com/groups/2043330
UC Berkeley Statistics BA Alumni
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https://www.linkedin.com/groups/4529144