Demystifying Stock Succes: A Strategy for Excess Return

Abstract

This thesis investigates the potential for excess returns in the stock market by looking into the assumptions of the Capital Asset Pricing Model (CAPM) and the Efficient Market Hypothesis (EMH). Specifically, the focus is on stocks that have doubled their value in a single year. We use a framework similar to Marc Reinganum's ground-breaking 1988 work, "Anatomy of a Stock Market Winner", but with up-to-date data to reflect today's market dynamics. Our main goal is to identify the key characteristics that separate successful stocks from the rest and enable higher-than-average returns. We look at 25 specific variables, using a sample of 204 winner stocks and 38 loser stocks from the period 2005 to 2021. Our main aim is to find the variables that are most likely to result in higher returns. Firstly, we made a percentile analysis of every variable to find the most significant ones. From our findings, we experimented with two investment strategies. Each strategy uses a different combination of 8-10 buying criteria from the 25 variables we studied. These criteria are chosen from variables that showed the highest individual returns before selection. We then looked at which variables gave the highest returns and are triggered most often, forming a combined framework of 2-4 variables. Interestingly, all three screening strategies managed to do better than the CAPM model, with returns adjusting for risk ranging from -3% to 63% and did better in 14 out of 15 tests. In our testing of these investment strategies, we found that the Weighted Average Cost of Capital (WACC) and Free Cash Flow (FCF) variables were particularly influential in generating higher returns. We also critically examined our results using insights from behavioral finance to explain why our strategies outperformed. These findings suggest that it may be possible to take advantage of systematic inefficiencies in the market, challenging the foundations of both the CAPM and EMH. However, the complexity of financial markets means we need to be careful about how we interpret these findings. Nonetheless, our results do suggest that it's possible to systematically achieve higher returns once risk is considered. This challenges the common assumptions of the CAPM and EMH. The study also suggests that beta may not be the best measure of risk, indicating that existing theoretical frameworks may need further refinement.