Financial analytics with R: building laptop laboratory for data science
- Cambridge Cambridge University Press 2016
- xvi, 377 p.
Table of Contents 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.
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.
Contains an ideal blend of innovative research and practical applications Tackles relevant investor problems Provides a multi-disciplined approach, solving problems from both fundamental and non-traditional methods.
9781107150751
Finance--Mathematical models--Data processing R (Computer program language) Finance--Databases