Systematic Trading Strategies

Catalog description

Credits 3. 3 Lecture Hours. Overview of quantitative investing using algorithmic trading for investment management; topics include exploration of collecting and preparing financial trading data, time series analysis, trend systems, momentum and mean reversal, arbitrage, backtesting, order execution, and reporting of risk and performance measures; tools, methods, and trading techniques are taught using the R programming language and using R Studio. Prerequisites: Admission to Master of Science in Quantitative Finance program or approval of department head.