Conflicts of Interest in a Corporate Environment

The Agency Relationship: When one party (the agent = company management) acts for another party (the principal = shareholders), an agency relationship exists.

The Principal-Agent Problem: The situation where agents act in their own best financial interest rather than the interest of their principals.  This is an ongoing challenge for investors.

Corporate Conflicts of Interest in the Agency Context

  • Corporate Managers vs. Equity Owners
    • Managers may not always act in the best interests of stockholders.
    • Executives may initiate unprofitable business ventures in order to expand their internal influence.
    • Managers may treat perks, such as excessive use of corporate jets, as regular operating expenses.
    • Managers also may make investments with corporate capital, which do not offer equity owners an appropriate risk adjusted return.
-   The checks and balances of a well-conceived corporate governance plan will help reduce management-shareholder agency problems.
  • The Board of Directors vs. Shareholders
    • The board plays a critical role in corporate checks and balances as well as business execution by approving strategic plans, approving mergers, selecting or removing executives, selecting auditors, and reviewing financial statements.
    • Theoretically, the board oversees company management to ensure that shareholder interests are promoted.
    • In reality, the board may side with the interests of management.  This can more readily occur when the board is not independent, that is when board members have close ties (business or personal) to management.
    • The board may also posture to receive excessive compensation, which increases the risk of siding with management over stockowners.

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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.