The Stock Market’s Greatest Winners - Picking the Stocks that Move the Soonest, Fastest and Farthest in Every Bull Cycle Authors Christopher Kjær Hansen Daniel Dyhr Schjunk Supervisor Ole Risager, Department of International Economics and Management, Copenhagen Business School Purpose This paper is divided into three parts; firstly, 1) we present empirical evidence from previous studies that have investigated characteristics of stock market winners or similar notions around the world. Then, 2) we device a strategy (“the OWL strategy”) that takes the characteristics of stock market winners as inputs. We test it in the Nordics from January 1992 to January 2016 to examine whether the strategy outperformed the sample universe of the study, the S&P 500 index and the MSCI Nordic index. Thirdly, 3) we discuss the stock market winners of the Nordics in the same period. Specifically, we ask the question of whether an investor, trader or speculator could have identified these winners that were coming out of the chute before the fact. Methodology The study is two-fold. Firstly, we present a quantitative backtest of how a strategy based on the characteristics of historical stock market winners fares over time. We furthermore consider the impact of transaction costs, factor attribution, sector attribution, stock attribution, performance consistency, and institutional investors’ ability to implement the strategy. Secondly, we examine the common characteristics of stock market winners in the Nordics based on statistics and case studies, and compare with previous findings. Conclusions Our back-test of the OWL strategy has an average monthly return of 4.21 percent between 1992 and 2016 vs. 1.72 percent for the MSCI Nordic index and 1.12 percent for the S&P 500 index. We find that relative strength, new high prices as well as profitability and growth measures are the most important quantitative factors in identifying stock market winners. Key words Momentum, Growth, Behavioral finance, Quantitative investing strategies, Stock market winner, Multi-baggers.
|Educations||MSc in Applied Economics and Finance, (Graduate Programme) Final Thesis|
|Number of pages||143|