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Master’s Research Project

Master in Finance

Master’s Research Project

While a thesis is not required, students may elect to carry out a Master’s Research Project during the second year of study under the supervision of a BCF-affiliated faculty member. Though the Master’s Research Project does not count as course credit for the Master in Finance degree, it does count for the Certificate in Machine Learning. Currently enrolled students interested in pursuing research opportunities should contact the Princeton BCF Director of Graduate Studies and seek out a faculty advisor from among the Princeton BCF-affiliated faculty. Master’s Research Projects can only be conducted while the student is enrolled full-time in the program.

The Princeton BCF Master in Finance lounge, equipped with workstations and programming tools, facilitates such projects. Princeton BCF provides a standardized computing environment, based on R, Python, Matlab, Mathematica, and C++. Princeton BCF also offers students access to numerous financial databases through Finance Library subscriptions. In addition, the Finance Library offers Master in Finance students terminal-based access to Bloomberg, Datastream, Morningstar Direct, SDC Platinum, and

The following list of past Master’s Research Projects provides examples of topics students might pursue:

  • MLB Moneylines as Investment Assets
  • Natural Language Processing for Price Change Prediction using Transformer Architecture
  • Robust Optimization of Time Series Momentum Portfolios: Regularizing Turnover via the L1 Penalty
  • Tactical Currency Hedging using Hierarchical Model
  • Analysis of Micro-Venture Capital Fund Performance
  • A Bayesian Non-Parametric Approach to Option Pricing
  • Forecasting Foreign Exchange Volatility: Extending the HAR model with Additional Regressors and Shrinking Estimators
  • Option Pricing using LSTM Neural Networks
  • An Empirical Investigation of the Dynamics of the Mexican Term Structure of Interest Rates
  • Mean Reversion Trading of Futures Products: An Application of Regression Trees