New Course - Equity Analysis and Valuation
We are pleased to announce the addition of a new course - Equity Analysis and Valuation - to our library of courses for Finance Professionals.
Course: Equity Analysis and Valuation
Learn the characteristics, analysis, and valuation of equity securities.
This course provides a thorough understanding of the equity markets and the analysis and valuation of equity securities.
The first three sections of the course focus on the market organization, market indices, and how efficient the stock markets are. The last three sections focus on the characteristics, analysis and valuation of equity securities.
The first section discusses how the equity markets are organized, the types of assets, various market participants and how equities are traded.
The second section focuses on market indices. It explains in detail about how indices are constructed, managed, calculated and used in the investment world.
The third section discusses the market efficiency, that is, how well the market prices of securities reflect the latest information. It discusses the different degrees of market efficiency and its impact on security analysis.
The fourth section provides an overview of equity securities and their various types and features.
The fifth section introduces us to the importance of industry and company analysis in equity valuation and explains how to conduct such analysis with a focus on competitive analysis.
The sixth section discusses the concepts and tools for equity valuation in detail.
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
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