Business Analytics in Finance

Welcome

Business Analytics in Finance is a practical guide that equips you with essential skills using R to analyze data, predict market trends, and manage risk. We begin with the fundamentals of time series analysis, teaching you to import, manipulate, and visualize stock market data.

We then dive into Technical Analysis with the quantmod package to forecast market movements using various indicators. You will master modern Portfolio Management by applying the Sharpe and CAPM models and learn to manage Fixed Income Securities by measuring risk and pricing bonds.

Finally, we explore Credit Risk and Advanced Analytics, building predictive models with logistic regression and segmenting customers with cluster analysis. By the end of this book, you will have the hands-on R programming skills to apply these powerful financial models effectively in real-world scenarios.

References

  • Brooks, Chris. Introductory Econometrics for Finance. 2nd ed.

  • Dettling, Marcel. Statistical Analysis for Financial Data in R. Springer Publications.

Text Books

  • Daroczi, George, Michael Puhle, Marton Michaletzsky, Zsolt Tulassay, Kata Varadi, and Agnes Vidovics Dancs. Introduction to R for Quantitative Finance. Packt Publishing, 2013.

  • Gujarati, Damodar N. Basic Econometrics.