15.4871 Algorithmic Trading and Quantitative Investment Strategies
Covers practical aspects of analytics in finance from the perspective of a quantitative investment manager. 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, and implementation. Emphasizes financial applications, but also covers mathematical and statistical techniques in some depth, along with their computational implementation in software and the use of real-world market data. Meets with 15.487 when offered concurrently. Expectations and evaluation criteria for graduate students will differ from those of undergraduates; consult syllabus or instructor for specific details.
This class counts for a total of 9 credits.
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