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The Effect of Brand Affinity on Investor Stock Choice
[Thesis]. Manchester, UK: The University of Manchester; 2016.
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Abstract
This study focuses on investigating some of the factors that influence the choice of stock to purchase (invest) by retail individual investors within the same industry. Specifically, understanding how brand affinity and stock choice of investors correlate and the effect on the price of the stock. Brand affinity, in this context, refers to the level of affect of favour that an individual has towards a certain corporate brand. The research also aims at developing a model for predicting the relationship between financial performance metrics of a company, brand affinity, and investor stock choice, which can be used in developing a simulator for predicting pricing and stock choice behaviours by simulating market choices. This research makes a relevant contribution to the fields of behavioural economics/finance, business strategy and investment management. Collection of primary data is done using a controlled experiment that involves an online simulation of a quantitative study using the choice-based conjoint analysis approach, which is a conjoint analysis variant. The data is collected and analysed using Sawtooth Software, an application for conjoint analysis, because of the complex mathematical operations involved. Investor stock choice is taken as the dependent variable while independent variables comprise of brand affinity and five financial performance metrics, which are dividend yield, price-to-earnings ratio, price-to-book ratio, return on equity and earnings per share. This study finds that brand affinity has a major impact, and is the most important factor affecting investor decision making in purchasing stocks. It is established that brand affinity and investor stock have a direct positive relationship, which is also the same for higher brand affinity levels and stock price. It is also established that when selecting stocks, investors do not exclusively rely on the rationality and expected utility in the same industry with same risk profiles. A market simulator is also successfully developed to examine the cross-elasticity effects between different stock attributes and levels of those attributes, albeit with a few limitations, which are to be improved through further research.
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A market simulator in Microsoft Excel format was generated that converted the raw conjoint (part-worth utility) data from the study into a model that allows simulated market choices.