Date of Award
1991
Document Type
Thesis
Degree Name
Master of Valuation Science
Department
Business
Abstract
This thesis will focus on the study and use of Shareholder Value Analysis as a technique to be implemented as a measure for business performance. Using the Al car software to perform the financial modeling for ESCO this thesis will prove that ESCO is undervalued and why. The financial models were built and based upon management's forecast and expectation trends.
Shareholder Value Analysis enables managers to evaluate alternative strategies in terms of changes in corporate value. The approach provides a uniform yardstick, a measuring tool for comparing one business plan to another in order to see which creates the most long- term value. The seven value drivers give a quick idea of where management should focus its planning effort to affect cash flow. Another good reason management should use this technique ; the approach helps make intelligent, informed decisions that will maximize the market value of the company, which could be realized in an eventual "cash out" or restructuring.
The process to get management to incorporate shareholder value in their company may be more difficult because American industry is still run and measured by short-term accounting numbers such as ROI (return on investment) and EPS (earnings per share). Market value is also driven by EPS performance and increasing shareholder value is not the driving force for the corporate restructuring movement.
Thesis Statement: Value like beauty, is in the eye of the beholder. Therefore, management's plans for and expectations of future performance have to be communicated to current and prospective investors in the market place so the value inherent in those plans will be reflected in the price of the stock, and therefore, the expectation gap, or difference between management's perception of value and the market's expectations of value can be closed.
Recommended Citation
Hullihen, Kelley A., "Shareholder Value for Esco" (1991). Theses. 854.
https://digitalcommons.lindenwood.edu/theses/854
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.