Brian Flaxman
Jupiter,FL
Summary
PhD Economist with a strong background in finance, specializing in fundamental and statistical analysis. Experienced in political economics and public economics, with a keen interest in macroeconomics and finance. Demonstrated expertise in utilizing natural language processing to uncover the influence of special interest group donations on legislative decision-making. Willing to relocate anywhere in the United States.
Overview
9
9
years of professional experience
Work History
AI Tutor (Freelance Position)
DataAnnotation
01.2025 - Current
- Trains and tests AI models, focusing on tasks involving economics and mathematics.
Teaching Assistant
University of Colorado Boulder
08.2016 - 12.2023
- Was a teaching assistant for and instructor of record of a variety of economics courses at the University of Colorado Boulder.
Intern
Consumer Financial Protection Bureau
05.2019 - 08.2019
- Assisted on various Equifax data set projects with a dedicated big-data Linux system.
Education
Ph.D. - Economics
University of Colorado Boulder
08.2024
Finance
TrendUp Finance
04-2024
M.A. - Economics
University of Colorado Boulder
05.2018
B.A. - Economics
University of Florida
05.2014
Skills
- Economics
- Mathematics
- Finance
- Python
- Natural Language Processing
- STATA
- Statistical Analysis
- Options Trading
- Futures Trading
- Statistical Analysis
- Fundamental Analysis
- Quantitative Analysis
- Webscraping
- Data Management
- Data Visualization
- APIs
- LATEX
- Linux
- Big Data
- R
- C
Other Education
TrendUp Now (L1-L3), Winter 25, Three, three-week financial trading courses dealing with the trading strategies of equities, options, futures. Internship opportunities to be granted at the conclusion. Will conclude with the Certified Futures and Options Analyst (CFOA) examination in May 2025.
Research Interests
- Policy Economics
- Political Economy
- Public Economics
- Finance
Works In Progress
Syntax and Stocks; Does Favorable Healthcare Legislation Language Increase Healthcare Company Stock Prices?, 02/25, This paper seeks to determine the extent to which stock performance of healthcare companies is impacted by healthcare legislation passed. It will be the first to do this by analyzing the textual content of the legislation passed, rather than by utilizing event analysis. Publicly available American Legislative Exchange Council (ALEC) healthcare model legislation and US Congress legislation passed will be collected for the years 2012-2020 and will be cleaned. Legislation favorability measures will be created using a similar Natural Language Processing methodology as Flaxman (2024). These favorabilities will be utilized in a sentiment model of asset prices similar to Garcia (2013) and others to determine if the legislation language is a significant factor in the price of the stock, and if so, by how much.
Software Proficiencies
- Python - Webscraping, Natural Language Processing, Data Management, Data Visualization, APIs
- Stata - Statistical Analysis, Data Management, Data Visualization
- LATEX - Document Creation
- Linux - Big Data Operating and Data Management, 'Regular' Linux OS's
- R - Statistical analysis
- Working knowledge of C++, Java, Matlab, SAS, and SQL.
Language Proficiencies
- English, Fully Fluent
- Spanish, Intermediate
- Chinese, Beginner
Citizenship
United States of America
Awards
Sieglinde Talbott Haller Endowed Economics Scholarship, 2017
Languages
English
Native or Bilingual
Spanish
Limited Working
Chinese (Mandarin)
Elementary
Timeline
AI Tutor (Freelance Position)
DataAnnotation
01.2025 - Current
Intern
Consumer Financial Protection Bureau
05.2019 - 08.2019
Teaching Assistant
University of Colorado Boulder
08.2016 - 12.2023
M.A. - Economics
University of Colorado Boulder
Ph.D. - Economics
University of Colorado Boulder
Finance
TrendUp Finance
B.A. - Economics
University of Florida
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