By |Published On: April 21st, 2015|Categories: Uncategorized|

Quantitative Value: Seeking Excess Returns on the Stock Market

The objective of this thesis is to develop and back-test an investment strategy created by professors Wesley R. Gray and Tobias E. Carlisle in their book Quantitative Value, published in 2013. Gray and Carlisle construct a quantitative strategy based on Warren Buffet’s investment philosophy and when back-tested, show that the strategy has been able to outperform the S&P500 TR Index for the last 40 years. The author tries to replicate the results shown by Gray and Carlisle for the US stock market which, despite the short period analyzed, gives promising results as the strategy generates a positive Jensen’s alpha that is statistically significant. When implemented for the Icelandic stock market the results are very impressive as the model’s return is significantly higher than the market’s. The model also manages to outperform Icelandic equity funds over a recent 18 month period, generating the highest Jensen’s alpha that is also statistically significant. The author set out to see if the model could be improved by introducing a new measure; return on invested capital (ROIC). The model’s results with ROIC included were impressive but did not improve the performance of the original model. However, due to the small sample size, the author believes that the result give cause to further research. The results support Gray and Carlisle’s findings that they have managed to find a model that systematically picks value stocks that generate excess returns.

A Better Model? An Empirical Investigation of the Fama-French Five-Factor Model in Australia

Recently, Fama and French (2014) document a five-factor model that includes the market and factors related to size, book-to-market, profitability and investment outperforms the three-factor model of Fama and French (1993). Using an extensive sample over the period 1982 to 2013, we investigate the performance of the five-factor model in pricing Australian equities. We find that the five-factor is able to explain more asset-pricing anomalies than the three-factor model, which supports the superiority of the five-factor model. In contrast to that documented in Fama and French (2014), the book-to-market factor is found to remain its explanatory power in the presence of the investment and profitability factors. Our study provides an update to the existing Australian asset pricing literature.

Print Friendly, PDF & Email

About the Author: Wesley Gray, PhD

Wesley Gray, PhD
After serving as a Captain in the United States Marine Corps, Dr. Gray earned an MBA and a PhD in finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. Next, Wes took an academic job in his wife’s hometown of Philadelphia and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management firm dedicated to an impact mission of empowering investors through education. He is a contributor to multiple industry publications and regularly speaks to professional investor groups across the country. Wes has published multiple academic papers and four books, including Embedded (Naval Institute Press, 2009), Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016). Dr. Gray currently resides in Palmas Del Mar Puerto Rico with his wife and three children. He recently finished the Leadville 100 ultramarathon race and promises to make better life decisions in the future.

Important Disclosures

For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. Third party information may become outdated or otherwise superseded without notice.  Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency has approved, determined the accuracy, or confirmed the adequacy of this article.

The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. Our full disclosures are available here. Definitions of common statistics used in our analysis are available here (towards the bottom).

Join thousands of other readers and subscribe to our blog.

Print Friendly, PDF & Email