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Are you innately curious about dynamically interoperating financial markets? Since the crisis of 2008, there is a need for professionals with more understanding about statistics and data analysis, who can discuss the various risk metrics, particularly those involving extreme events. By providing a resource for training students and professionals in basic and sophisticated analytics, this book meets that need. It offers both the intuition and basic vocabulary as a step towards the financial, statistical, and algorithmic knowledge required to resolve the industry problems, and it depicts a systematic way of developing analytical programs for finance in the statistical language R. Build a handson laboratory and run many simulations. Explore the analytical fringes of investments and risk management. Bennett and Hugen help profitseeking investors and data science students sharpen their skills in many areas, including timeseries, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.
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