BUS-F455 Topics in Finance: Quant Finance

• 16 weeks
• 3 credits
• Prerequisite(s): BUS-S 364, BUS-S 432, or instructor consent

This course provides an overview of methods for quantitative analysis of asset prices using Python. Topics include properties of equity returns, mean-variance portfolio optimization, lifecycle investing, risk factors, return predictability, models of time-vary volatility, various “anomalies” leading to trading strategies that generate alpha, Monte Carlo simulation, option pricing, and machine learning applications for asset price prediction. Statistical methods will be introduced as needed, including regularized regression, classification and clustering algorithms, and neural networks. The Python modules NumPy, pandas, and scikit-learn will be used extensively.