Overview of quantitative investing using algorithmic trading for investment management; 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 using R programming language and R Studio. Prerequisites: ISTM 313 or ISTM 315; BUSN 203; admission to upper division in Mays Business School Credits 3. 3 Lecture Hours.
Overview of quantitative investing using algorithmic trading for investment management; 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 using R programming language and R Studio. Prerequisites: ISTM 313 or ISTM 315; BUSN 203; admission to upper division in Mays Business School Credits 3. 3 Lecture Hours.
