Professional Journey
Here is a broad overview of how my academic interests have continually informed my dynamic professional aspirations.
Current Resume
Investment Strategies Summer Analyst at NISA Investment Advisors, LLC
NISA is an institutional asset manager with $440B+ AUM in St. Louis, MO. Focused on maximizing information ratios through actively managed, liability-driven investment decisions, NISA also specializes in a number of duration-immunized completion and derivative overlay-focused portfolios. Today, the firm is a leading manager in fixed-income and derivatives while growing its business in HY, quantitative equity, and hedge fund strategies.
This past summer, I served as a Summer Analyst for their Investment Strategies team, which is a division of the firm focused on alpha generation through devising tailored, optimized quantitative trading solutions that address specific client portfolio benchmarks and needs. During my thirteen week internship, I worked on a number of complex projects that both challenged me mathematically and programmatically while addressing some of NISA's recent areas of inquiry.
Main Project: Debt Risk Allocation
Skills: Python (NumPy, Pandas, Matplotlib, Plotly, etc.)
Designed six python debt allocation strategies into credit (CB) and treasuries (TSY) that exactly met projected liabilities in expectation whilst dynamically de-risking as soon as possible with surplus in response to rolling start of year cash, the previous year’s default draws, and other relevant parameters (e.g., TSY/CB yields, liabilities owed in that year, starting default rates, etc.).
I then performed hundreds of set-seed 30-year simulations per strategy, which included yearly default binomial draws and (originally-fixed) single-year default rates modeled by a mean-reverting lognormal random walk centered at the previous year’s rate with a spread volatility parameter to capture correlated multi-year default events.
Credit spreads and changing yields were a function of the changing annual default rate, and the parameters for the mean reversion were generated through a time-series lag-1 regression on data generated by looking at monthly OAS backward minus forward index changes on a 100 bp starting level. Simulations permitted interactive single-path inspection, borrowing back to $0 or the cost of full-credit allocation, as well as choosing to overshoot liabilities in expectation.
I also generated from Bloomberg a TSY term premium curve, linearly interpolating excluded data and incorporating this on to the PV allocation pricing and yields for TSY and CB. This research ultimately led me to compare the relative efficacy of strategies placing credit risk in different ways across the liability horizon.
Side Projects:
Skills: Excel, SQL, Bloomberg, Python, Azure OpenAI
Derivatives Visualization
Approximated Black-Scholes pricing in python for puts and calls through the PV of the mean option payouts from n paths of prices that followed geometric brownian motion
Graphed Delta, Vega, Theta, Gamma, and Option Price vs. Spot, including additional lines per chart that accounted for changes in time to maturity and volatility
Index Replication
Replicated Bloomberg’s 60/40 Index (BMA6040) through rebalancing between 60% stocks (B500T Index) and 40% bonds (LBUSTRUU index) with minimal tracking error
Continually computed post-rebalancing shares of B500T and LBUSTRUU to back-into how component price changes impacted the index value over time
Compared percents of B500T and LBUSTRUU to Bloomberg-provided weightings
HY Beta Compensation
Generated two sample portfolios from NISA’s HY Portfolio benchmarked to the Bloomberg HY Index, including only tickers that have CUSIPS in the portfolio with different numerical credit ratings (mimicking senior/subordinated debt, securitized vs. not)
Calculating historical annualized excess returns and volatility against same-duration treasury bonds to see if increase in beta from subordinated credit is well-compensated
Also found the average OAS and duration for comparison purposes between portfolios and the original index
AI Project on Derivatives Confirms
Leveraged NISA’s Azure OpenAI model API endpoint to create a python method that would take derivative confirms documents as an input, (1) produce JSON and HTML outputs recognizing confirm type and summarizing key document features from pre-build structured corresponding classes, (2) compare document features to a vanilla confirm example of the same type, recapping key differences, and (3) launch a terminal Q&A to query about the found document
AI Project on Transaction Recaps
Leveraged NISA’s Azure OpenAI model API endpoint to create a python method that would take derivative transaction recap documents (e.g., email or counterparty recap pdf) as an input, compare them automatically to NISA’s internal transaction database using SQL, then identify discrepancies that may exist
Can be dynamically run many times per-document and across all recaps to produce a differences matrix that is compared to an answer key to study the performance efficacy of AI at identifying recap errors
UChicago XRisk Laboratory: Summer 2024 Summer Research Fellow
UChicago's Existential Risk Laboratory (XRisk) is focused on pioneering undergraduate and graduate multidisciplinary research into some of the largest threats to humankind. It's yearly cohort is split into four subgroups (AI Safety / Governance, Biosecurity, Cascading Risks, and Nuclear Security) and includes students from a variety of STEM and political science backgrounds.
On the Cascading Risks team over the 10-week fellowship, I completed an independent research project that addresses the implications of nuclear winter on international food trade, helping to build a framework for what international food relations would look like without a traditional no-export post-disaster assumption. To do this, I was mentored by UChicago Professor and Statistician Mihai Anitescu. This process involved:
1) Generating a five page comprehensive literature review outlining the asymmetrical impacts of both anthropogenic climate change and nuclear winter on agriculture yields.
2) Viewing international trade as a weighted directed network, where nodes are countries and edges are the weighted net export of each considered crop between partners.
3) Evaluating the Louvain community detection method, used in a prior paper, with respect to standard normal p-values generated from the Logrank test statistic to more rigorously discuss which spatial implications of nuclear winter on country trade communities are meaningful.
4) Constructing a score function that considers the severity and difficulty of post-disaster trade transitions, food insecurity from production (yields) and imports, and the extent a trade community can satisfy domestic demand alone, to approximate national food vulnerability following a nuclear disaster.
By the end of the fellowship, I generated a 6500-word research paper, including many spatial graphs, tables, and robust quantitative analysis. I hope to continue work until the paper can be published, and the current version of my paper is found below.
Summer Analyst at Siebert Williams Shank (SWS): Summer 2023
SWS is a leading minority and women-owned underwriting firm in public finance investment banking. I was a member of the Municipal Banking Team first in Chicago and later in Texas, and below are some of my accomplishments:
1) Gained considerable industry knowledge, especially in fixed-income issuances
2) Built and ran debt profiles for clients (IL Tollway, CPD, Cook County, CTA) using MuniOS and EMMA
3) Prepared muni market update book graphs for SWS and Bexar County Hospital District
4) Completed post-pricing books for Gregory-Portland ISD and Crowley ISD
5) Using SDC, IPREO, and Excel:
Tracked firm negotiated new money/refunding single family mortgage revenue bond transactions for TDHCA
Created a debt call horizons graph for Hillsborough County Schools
Broward County RFP: pulled S&P rating, institutional/retail order volume, gross spread for recent lead transactions
UTexas RFP: used an index-match model to efficiently find bonds underwritten for 100+ transactions
Made pricing progressions for San Marcos CISD and Needville ISD
Used custom function conditional formatting to inform higher-ed issuers of possible institutional investors
Growth Marketing Intern at TrueToForm (TTF): Fall 2022
TTF is a SaaS firm focusing on transforming the fit experience for users through a novel 3D body-scanning app.
Leveraging my interest in quantifying behavior, I used app user data, google analytics, google search console, and other internal data sources (see right) to design and recommend actionable KPIs and SEO optimization strategies from pivot tables, graphs, and presentations. Later, I informed their market expansion strategy through researching and visualizing the firm's competitive landscape.
High School DECA and the ILDECA State Action Team (SAT)
DECA is a competitive business club supporting students with interests in finance, marketing, hospitality, and management through case study competition at the local, state, and international levels. Inspired by an interest in how human and consumer behavior can be leveraged and quantified to make informed decisions, I participated in Business Services Marketing (BSM) and won 1st Place Overall at Internationals (ICDC) in 2022 in Atlanta, Georgia.
During this time, I led both my local chapter and Illinois DECA as President and VP of Leadership Development for the State Action Team (SAT), respectively. In the latter, I organized, held, and published four Leadership Councils to connect state members to local business leaders whilst logistically organizing and speaking at our state conference (CDC).
Certificates
