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FINANCIAL DATA ANALYSIS -PRACTICAL
Course Outcomes (Cos):
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Course Outcomes |
Learning and teaching strategies |
Assessment Strategies |
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|---|---|---|---|
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On completion of this course, the students will be able to: CO246 Process, organise, clean and validate financial Data CO247 Use Graphical and Visualization tools to present financial and non-financial data CO248 Conduct Financial Statement Analysis CO249 Apply Equity Valuation Models CO250 Conduct Investment Analysis for designing investment profile |
Interactive Lectures, Group Discussion, Tutorials, Reading assignments, Workshops and question preparation |
Quiz, test, assignments and viva-voce |
• Introduction to data analysis techniques and tools (Excel/Python/R)
• Data cleaning and preprocessing techniques
• Handling missing data and outliers
Data presentation: Visualization and graphical Presentation
• Dashboard, graphs, Diagrams, Tables Report Design
• Application of Tools and Techniques of Visualization and Graphical Presentation
Financial Statement Analysis
• Introduction to financial statements (balance sheet, income statement, cash flow statement)
• Ratio analysis for financial statement interpretation
• Assessing profitability, liquidity, and solvency
• Comparative analysis and benchmarking
Equity Valuation Models
• Introduction to equity valuation
• Discounted cash flow (DCF) analysis
• Relative valuation methods (P/E ratio, P/B ratio)
• Analyzing analyst recommendations and target prices
Investment Analysis
Risk and Return Analysis/Sentiment Analysis/ Technical Analysis
SUGGESTED TEXT BOOKS
• Albright, S. C., Winston, W. L., & Zappe, C. (2019). Data Analysis and Decision Making (6th ed.). Cengage Learning.
• Chen, C., & Zhang, L. (2020). Financial Data Analysis with Python: Analyzing, Visualizing and Modeling Financial Data with Python. Apress.
• Montgomery, D. C., Peck, E. A., & Vining, G. G. (2020). Introduction to Linear Regression Analysis (6th ed.). John Wiley & Sons.
• Ruey S. T., & Tsay, R. S. (2012). Analysis of Financial Time Series (3rd ed.). John Wiley & Sons.
• Sharma, J. (2020). Financial Analytics with R: Building a Laptop Laboratory for Data Science. Springer.
SUGGESTED REFERENCE BOOKS
• De Jong, E., & Wilmott, P. (2017). Financial Modeling and Valuation: A Practical Guide to Investment Banking and Private Equity. John Wiley & Sons.
• Greene, W. H. (2017). Econometric Analysis (8th ed.). Pearson.
• Johnson, R. A., & Wichern, D. W. (2020). Applied Multivariate Statistical Analysis (7th ed.). Pearson.
• Kuhn, M., & Johnson, K. (2013). Applied Predictive Modeling. Springer.
• McDonald, R. L. (2014). Derivatives Markets (3rd ed.). Pearson.
e-RESOURCES:
• http://ww1.shodhganga.com/
• https://shodhgangotri.inflibnet.ac.in/
• https://www.scopus.com/home.uri
• http://www.e-book.com.au/freebooks.htm
• https://www.doaj.org/
REFERENCE JOURNALS:
• Journal of Financial Econometrics, Oxford University Press
• Journal of Financial Data Science, Global Association of Risk Professionals
