Company Analysis

After the analyst runs through all the factors -- demographic, governmental, social -- analysts undertake company analysis. Analysts will seek to understand if the company wishes to achieve its strategy through an offensive or a defensive strategy. According to Porter, the strategy could be a low cost strategy (cost leadership) or a product or service differentiation strategy.

In low cost strategies companies fight on the basis of lower price than the competition, by lowering their costs. Thanks to their lower costs, they achieve good profitability. This strategy is employed to protect market share or gain new market share. Certain times companies will pursue an aggressive price strategy in order to chase out the competition. Once this is done they will then gradually raise prices. This is known as the predatory strategy. Companies pursuing a low cost strategy and successful at it are characterised by high efficiency, tight cost control, excellent reporting and operating systems and above average management.

Companies employing the product/service differentiation do so by having a unique product or service. Since most markets are price sensitive, managers must be able to understand motivations for customer purchases. Differentiation can be on quality, distribution, etc.

Company analysis must:

  • Detail industry characteristics

  • Analyse customer demand

  • Assess supply of products and services

  • Explain company's pricing structure and environment

  • Detail historical returns, assess financial ratios and their interpretations

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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.