Translating financial data and market complexity into quantitative signal through machine learning, risk modeling, and computational methods.
Quantitative & Computational Finance · Georgia Tech
Manasi PrasadI’m targeting full-time roles in quantitative risk, asset management, or trading in the US after graduation.
Available for full-time roles starting December 2026 · Open to relocation across the US
Measuring textual tone in SEC risk disclosures with the Loughran-McDonald dictionary, and linking it to stock returns and the business cycle.
Comparing Word2Vec and GloVe embedding-based sentiment to the Loughran-McDonald dictionary in SEC risk disclosures.
Classifying hawkish, dovish, and neutral language in FOMC minutes, and building a document-level hawkishness measure linked to inflation and the business cycle.
Zero- and few-shot classification of AI-related statements in earnings calls with Phi-3-Mini, used to construct a firm-level AI Bullishness measure across sectors.
Comparing RoBERTa and GPT-2 embeddings from SEC 10-K business descriptions for sector classification, K-Means clustering, and embedding-based portfolio construction.
Open to conversations about quantitative risk, asset management, and trading roles — and the research behind them.
Email MeAvailable for full-time roles starting December 2026 · Open to relocation across the US