About Me
I am a Ph.D. candidate in Financial Economics at LSU New Orleans. I work in empirical corporate finance and financial institutions, on how information reaches prices, financing and trading: what sell-side analysts and corporate insiders do with public signals, when banks' unrecognized securities losses become priced crash risk, and how machine learning and large language models can serve as measurement tools in finance.
My job market paper, which I presented at the FMA 2026 Annual Meeting, shows that government subsidies act as attention shocks: analyst coverage rises after an award while the content of analyst output does not change, and corporate insiders, not analysts, turn that attention into trading. I have also presented my work at the SWFA and SWDSI annual meetings, and a paper is accepted at the SFA 2026 Annual Meeting.
Before finance, I spent more than seven years in applied economic research, at the Bangladesh Institute of Development Studies, the Policy Research Institute of Bangladesh and WorldFish, and on projects for the USDA, the World Bank and the Asian Development Bank. I hold an M.S. in Agricultural and Applied Economics from Texas Tech University, where my team won 1st Place in the USDA Local Food Economics Data Visualization Challenge, and a B.Sc. and M.Sc. in Economics from IIUM. I am completing an M.Sc. in Computer Science and am on the 2026 to 2027 academic job market.
Research Highlights
Analysts, insiders and corporate attention
Government subsidies bring firms attention, not information. After a first award, analyst coverage rises while the content of analyst output does not change; insiders trade more, tilt toward selling, and their post-award sales predict returns less well than ordinary insider sales.
Related work studies how chief executives trade on analysts' views and on a firm's public conduct record, and how changes in the roster of analysts move the consensus recommendation.
Banks: hidden losses, crash risk and depositor discipline
This work asks when hidden losses on banks' long-duration securities become priced crash risk, using the 2022 UK gilt crisis, and how markets reprice unrecognized held-to-maturity losses in U.S. bank equity.
A further paper revisits depositor discipline across U.S. banks from 2000 to 2025.
Machine learning and language models as measurement tools
This work tests deep reinforcement learning against simple portfolio rules under one controlled protocol, compares how large language models and managers allocate capital against q-theory, and measures what earnings calls carry that the 10-K leaves out.
Development and policy research
Earlier work studies nonfarm income and migration in Bangladesh (Development Policy Review, 2023), Islamic banking and finance, and trade, fuel efficiency and emissions with the GTAP model. I have spoken at the U.S. Department of State's Foreign Service Institute on remittances and on the economy, infrastructure and energy of Bangladesh.
Technical Skills
Programming
Machine learning
Market and firm data
Other tools
Education
Ph.D. in Financial Economics
LSU New Orleans
Expected Spring 2027
M.Sc. in Computer Science
LSU New Orleans
2027
M.Sc. in Finance
LSU New Orleans
2026
M.S. in Agricultural and Applied Economics
Texas Tech University
2024
B.Sc. and M.Sc. in Economics
International Islamic University Malaysia (IIUM)
2014 and 2018
Honors and Awards
1st Place, USDA AMS Local Food Economics Data Visualization Challenge
AAEA Annual Meeting, Washington, D.C.
2023
Distinguished Graduate Student Assistantship
Texas Tech University
2022 to 2024
Graduate Student Assistantship
LSU New Orleans
2024 to Present
Invited Speaker
U.S. Department of State, Foreign Service Institute
2023, 2024