Introduction - Industry and Company Analysis

In assessing a product or a company during market analysis, an important part of analysis is evaluating the competition, the customer and the company. The strengths and characteristics of each are assessed independently and in relation to each other to gain a comprehensive understanding of each. This is true while analysing a company's equity and how it will perform among other things. 

A company's industry is a group of similar or alike players in the same field of business. Understanding the performance indicators of the industry as a whole and benchmarking it against each company's performance gives us an idea of where the company is placed with respect to that industry. Parameters like growth opportunities, competitive dynamics and risk are analyzed. By analyzing an industry we get a better idea about the company's ability to meet obligations, particularly in the times of economic recession.

Investors use industry analysis to give investment weightages. Analysts assess industries based on their performance, growth and profitability. They then give the companies weightages -- overweight (positive outlook), market weight (on par with market), underweight (negative performance) -- in comparison to industry outlook.

Analysts also use industry analysis to their benefit by investing based on the industry's business cycles.

Industry analysis is a part of portfolio performance attribution, that is, the industry is studied as one of the sources that contribute to the portfolio's performance.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance 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 comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.