Jacob Ryan

Performed economic and financial analysis for commercial litigation and regulatory proceedings. Worked with testifying experts, including prominent faculty and industry practitioners.

Performed economic and financial analysis for commercial litigation and regulatory proceedings. Worked with testifying experts, including prominent faculty and industry practitioners, to calculate damages, review depositions, research the case, and visualize financial data.

I interned with the Quantitative Analysis Unit (QAU) within the U.S. Securities and Exchange Commission (SEC) in New York City.

• I wrote a data input-output and cleaning program for trading blotters submitted for Exchange Traded Funds (ETF) to streamline the SEC’s process of formatting and aggregating these data and help identify non-compliance with regulation or even fraud.
• ETF-trading analysis had previously taken SEC analysts many hours of work and upwards of 1,000 lines of code per exam just to read in the irregularly formatted data. Using my program, ETFs can now be read in and analyzed in a fraction of that time and typically without the need for additional code.
• My supervisors gave me freedom to design the program, which I used to create an efficient and well documented program.
• I took a leadership role in directing the project and assigning tasks to the other intern.

I learned a lot interning with the QAU.

• In the week before the internship, I taught myself Python, which I used daily at the QAU.
• During the first week of the internship, I taught myself Q and KDB+, which I used to read through previously written SEC code for ETF-trading analysis.
• While reading through SEC code and creating my own program, I learned a lot about trading, creation, and redemption of ETFs.
• I participated in weekly lectures on machine learning given by one of my supervisors, a Ph.D. in statistics.
• I gained experience managing a GitLab repository with at least one other active user.

This thesis examines how proprietary trading firms' uncertainty about the development of the Volcker Rule influenced their program trading. I construct measures of regulatory risk associated with the Rule from the sentiment of reputable financial news articles. I provide evidence that these firms rely significantly on recent articles to make their trading decisions, but that they quickly forget older articles. I use previous research to split my sample into "affected entities" who are directly affected by the Rule (i.e., banks and their subsidiaries) and "unaffected entities" who may be indirectly affected by the Rule (i.e., non-bank proprietary traders). I provide evidence that (1) affected entities were sensitive to articles implying that the Rule would be strong during the period leading up to Congress' ratification of the Volcker Rule, (2) affected entities were sensitive to articles implying that the Rule would be weak or delayed during the periods that regulators implemented and firms complied with the Rule, and (3) unaffected entities were sensitive to any information about the timing (i.e., progress and delay) of the Rule during the period of regulatory implementation. Collectively, this evidence indicates that uncertainty about the Rule had consequential and distinct effects on both bank and non-bank entities throughout its ratification, implementation, and compliance periods.