Supply and Demand Analysis

Supply Analysis

  • Commonly demand analysis is the greater concern when analyzing and industry, but supply analysis is not without its useful insights.

  • The story of supply is largely told by knowing an industry’s capacity and the degree to which it is over or under-utilized.

  • If the analyst knows that capacity is being highly utilized, then it may signal high profitability.  Alternatively, when there is significant excess capacity, profit margins may be declining; firms may offer price discounts in order to induce buying and increase capacity utilization.

  • In industries with only a few firms or with significant capital costs to increase capacity, analysts may find it easy to estimate capacity utilization.  However, in industries with many firms or low expansion costs, capacity utilization can be much more difficult to estimate.

Demand Analysis

  • Understanding industry demand trends is critical for equity analysts; this receives more attention than supply analysis.

  • Historical data will be useful, but the ability to spot industry turning points can separate good analysts from great ones.

  • In order to understand demand, analysts will need to study an industry’s customer base and their needs.

  • In the case where an industry provides an intermediate good, product demand is a derived demand.

  • One technique for analyzing intermediate good demand is called input/output analysis.

Pricing Practices Analysis

  • The ability of a company to retain some degree of pricing flexibility can have a significant impact on its profit margins.

  • Many inferences can be made about an industry’s pricing practices through the lens of Porter’s Five Competitive Forces; product segmentation also provides insights into industry pricing.

  • Product segmentation can be seen in the form of branding and service levels.  In segmenting products, companies can create some pricing flexibility.

  • For example, a large clothing designer might create a middle market clothing line to appeal to middle class consumers, but also have an upscale brand distributed only in luxury boutiques.

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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.