Computer Trading for Non-Finance Majors

Catalog description

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.