15.487 Algorithmic Trading and Quantitative Investment Strategies
Covers advanced financial analytics and their practical applications to algorithmic trading and quantitative investment strategies. Develops understanding of stochastic processes, option pricing, investment strategies, backtest simulation, data and computational architecture, portfolio construction, trading implementation, and risk management within the context of specific quantitative trading strategies. Follows natural sequence of research, development, testing, implementation, and performance attribution. Emphasizes financial applications, but also covers mathematical and statistical techniques, along with their computational implementation in software and the use of real-world market data. Meets with 15.4871 when offered concurrently. Expectations and evaluation criteria for graduate students differ from those of undergraduates; consult syllabus or instructor for specific details.
15.487 will be offered this semester (Spring 2019). It is instructed by P. Mende.
This class counts for a total of 9 credits. This is a graduate-level class.
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