FE 670 Algorithmic Trading Strategies
This course investigates statistical methods implemented in multiple quantitative trading strategies with emphasis on automated trading and based on combined technical-analytic and fundamental indicators to enhance the trade-decision making mechanism. Topics explore high-frequency finance, markets and data, time series, microscopic operators, and micro-patterns. Methodologies include, but not limited to, Bayesian classifiers, weak classifiers, boosting and general meta- algorithmic emerging methods of machine learning applied to trading strategies. Back-testing and assessment of model risk are explored.
Prerequisite
FE 545 and FE 570
Distribution
School of Business