Bennett M.J., Hugen D.L. Financial Analytics with R: Building a Laptop Laboratory for Data Science

Cambridge University Press, 2016. — 394 p. — ISBN: 978-1-107-15075-1.
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.Analytical Thinking
The R Language for Statistical Computing
Financial Statistics
Financial Securities
Dataset Analytics and Risk Measurement
Time Series Analysis
The Sharpe Ratio
Markowitz Mean-Variance Optimization
Cluster Analysis
Gauging the Market Sentiment
Simulating Trading Strategies
Data Exploration Using Fundamentals
Prediction Using Fundamentals
Binomial Model for Options
Black–Scholes Model and Option-Implied Volatility
Appendix. Probability Distributions and Statistical Analysis