Texas A&M University 3 credits FINC
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.
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