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x/y[1] 5Business 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.
About the Authors
Vijayakumar P is an accomplished educator and data professional with over eight years of teaching and research experience in business analytics, data science, and HR analytics. He is a UGC Junior Research Fellow (JRF) and has qualified the UGC NET and SET in Management multiple times, reflecting his strong academic foundation.
Proficient in Python, R, STATA, SPSS, AMOS, PLS-SEM, Tableau, Power BI, Google Looker Studio, GitHub, and Excel , he has guided students and professionals in transforming data into actionable insights. His teaching spans business analytics using R and Python, HR metrics and dashboards, business forecasting, and business research methods, and he has also developed interactive eBooks to enhance hands-on learning.
Vijayakumar’s work is marked by clarity, precision, and innovation—whether in research, classroom teaching, or applied analytics—making data more accessible, impactful, and meaningful for decision-making.
Inclusion of R & Python codes in this book
Throughout the book, the R & Python codes used for the analysis are included in this document as shown below. And the output of each code is given below the code.
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.