This paper challenges the efficient market hypothesis, by testing to which degree it is possible to outperform the S&P500 index based on historic firm specific characteristics. An article by Marc Reinganum (1988) ‘The Anatomy of a Stock Market Winner’ analyzes the common characteristics of extreme stock market winners on the American stock market in 1970-1983. His article is the foundation for the methods used in this paper. Building on Reinganums methods, this paper analyzes which firm specific characteristics characterize an extreme stock winner, while simultaneously differentiate between extreme stock winners and extreme stock losers. 23 firm characteristics are tested, based on 117 extreme winners and 113 extreme losers in the period 2002-2018, in order to evaluate which metrics has the best ability to predict future extreme winners. To justify the claim that historic firm specific metrics can signal future development in stock prices, economic and empirical evidence is researched and showcased. Six firm characteristics are found to have an ability to differentiate extreme stock winners and extreme stock losers. These characteristics are used to form three investment strategies, which are then tested, in order to examine the strategies’ ability to generate buy signals, and their ability to outperform the S&P500 index. All three strategies manage to obtain a 2-year average excess return between 7%-26%. Furthermore, this paper puts Reinganums trading strategies to the test, in order to test whether his strategies performs well out-of-sample in the period 2007-2016. His adjusted 9-screen strategy does not have success during this period. His 4-screen strategy, albeit not as impressive as during his initial period, outperforms the S&P500 index with a 2-year average excess return of 14,97%. In this paper, the importance of incorporating an industry perspective to an analysis based on firm characteristics is also highlighted. Firm characteristics can vary a lot across industries, which can impact tendencies found and conclusions drawn. Lastly, this paper discusses certain issues of quantitative analysis, such as survivorship bias, data snooping, subjectivity in methods and how to overcome them. Although this paper to some degree is subject to biases such as survivorship bias and data snooping, it is concluded to be unlikely that these biases are the only reason for the success of the strategies examined. It is however not recommended to implement the strategies until out-of-sample tests has been conducted.
|Educations||MSc in Finance and Accounting, (Graduate Programme) Final Thesis|
|Number of pages||128|