Date of Award
2024
Degree Type
Dissertation
Degree Name
Doctor of Business Administration (DBA)
Department
Business Administration
First Advisor
Devendra Kale
Abstract
The inspiration for this dissertation began as a practitioner. As a Wall Street equity analyst, I calculated the valuation of various types of stocks using relative and intrinsic valuation methods on a daily basis. I noticed an interesting phenomenon while performing these calculations. The estimated stock prices were often largely disconnected from the actual stock market price leading me to wonder what the role of estimated valuations was in the overall investment process.
I believe there is a separation between a stock’s market price and fundamental value consistent with the “Noise” Trader Model (NTM). If this is true, a researcher can isolate pricing error or the difference between the stock price and fundamental value and determine how best to forecast future stock price and what factors influence it.
My mixed methods study takes the unique approach of evaluating stock prices from a quantitative and qualitative perspective. Quantitatively, I completed a statistical analysis to understand better the relationship between stock prices and various forecasting methods. Qualitatively, I performed a thematic analysis of the responses to an investor survey designed to provide insights into the investment decisions driving those stock prices. I believe this approach is unique and valuable as it gives a “full” picture of the drivers of pricing error from a quantitative and qualitative standpoint linking the numbers to the psychology and filling a gap in the academic literature, which tends to focus on just the quantitative aspect of stock price movements.
There were several takeaways from the study. On the quantitative side, the primary takeaway is that the more refined the inputs into the valuation model, particularly the Residual Income Model, the closer the model came to forecasting future stock prices. Stock prices were found to have a statistically significant relationship with price estimates. Pricing error or the difference between the market price and its price estimate has a statistically significant relationship with investor sentiment.
Qualitatively, the research points to a homogenous group of stock market participants, who primarily rely on just a few valuation methods to predict stock market price. The study confirms the academic model of the different stock market participants, informed vs. uninformed, and their behavior and interactions. There is a clear separation between the two groups of investors; uninformed investors rely on comparatively unsophisticated information, often not utilizing a valuation method, leading them to drive stock prices up or down providing the “noise” in the market. The two groups appear to have a similar psychologically make up lending to the possibility that stock picking is a learned skill.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Foresi, Joseph D., "VALUATION’S ROLE IN THE INVESTMENT DECISIONS PROCESS A MIXED METHOD STUDY" (2024). Open Access Dissertations. Paper 1667.
https://digitalcommons.uri.edu/oa_diss/1667