Bennett / Hugen | Financial Analytics with R | Buch | 978-1-107-15075-1 | sack.de

Buch, Englisch, 390 Seiten, Format (B × H): 177 mm x 254 mm, Gewicht: 914 g

Bennett / Hugen

Financial Analytics with R

Building a Laptop Laboratory for Data Science
Erscheinungsjahr 2016
ISBN: 978-1-107-15075-1
Verlag: Cambridge University Press

Building a Laptop Laboratory for Data Science

Buch, Englisch, 390 Seiten, Format (B × H): 177 mm x 254 mm, Gewicht: 914 g

ISBN: 978-1-107-15075-1
Verlag: Cambridge University Press


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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Weitere Infos & Material


Preface; Acknowledgements; 1. Analytical thinking; 2. The R language for statistical computing; 3. Financial statistics; 4. Financial securities; 5. Dataset analytics and risk measurement; 6. Time series analysis; 7. The Sharpe ratio; 8. Markowitz mean-variance optimization; 9. Cluster analysis; 10. Gauging the market sentiment; 11. Simulating trading strategies; 12. Data mining using fundamentals; 13. Prediction using fundamentals; 14. Binomial model for options; 15. Black–Scholes model and option implied volatility; Appendix. Probability distributions and statistical analysis; Index.


Bennett, Mark J
Mark J. Bennett is a senior data scientist with a major investment bank and a lecturer in the University of Chicago's Master's program in analytics. He has held software positions at Argonne National Laboratory, Unisys Corporation, AT&T Bell Laboratories, Northrop Grumman, and XR Trading Securities.

Hugen, Dirk L
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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