Synopsis
Are you innately curious about dynamically inter-operating 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 hands-on laboratory and run many simulations. Explore the analytical fringes of investments and risk management. Bennett and Hugen help profit-seeking investors and data science students sharpen their skills in many areas, including time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.
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About the Author
Mark J. Bennett is a senior data scientist with a major investment bank and has taught financial analytics at the University of Iowa and the University of Chicago. Mark holds a Ph.D. from UCLA, an M.S. from the University of Southern California and a B.S. with Distinction from the University of Iowa, all in computer science. He has held software positions at Argonne National Laboratory, Unisys Corporation, AT&T Bell Laboratories, Northrop Grumman, and XR Trading Securities.
Dirk L. Hugen is a graduate student in the Department of Statistics and Actuarial Science at the University of Iowa. He previously worked as a signal processing engineer.
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