NYU’s MS in Finance is designed for students interested in high-level financial modeling, risk analysis, and investment strategies. The curriculum spans corporate finance, quantitative methods, machine learning, and asset pricing with real-world simulations and data. Students collaborate on applied finance projects with top institutions in NYC’s financial district. Whether targeting roles in investment banking, hedge funds, or fintech, this degree equips professionals with tools to succeed in a global capital economy.
Building a portfolio optimization model using Markowitz theory
Stress-testing investment portfolios under macroeconomic shocks
Algorithmic trading bot for arbitrage opportunities in crypto markets
Credit risk prediction model using machine learning techniques
Comparative analysis of value vs. growth investing strategies
Option pricing simulation using Monte Carlo methods
Developing a dashboard for portfolio return attribution
FX rate forecasting using ARIMA and LSTM models
Constructing a Sharpe-maximized ETF portfolio
Modeling bond duration and interest rate sensitivity
Analyzing hedge fund performance using factor models
Detecting asset bubbles using volatility clustering
Fintech innovation mapping: Robo-advisors and automated investing
High-frequency trading simulator for NYSE equities
ESG portfolio construction and sustainability scoring
Capital structure optimization for mid-cap firms
Backtesting trading strategies using historical market data
Behavioral biases in retail investor trading decisions
Comparing machine learning vs. logistic regression in bankruptcy prediction
Modeling equity returns using macroeconomic indicators
Master the science of financial markets with NYU’s quantitative and strategic Finance MS.
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