by
Ekkehard Arne Friedrich
Dissertation presented in fulfilment of the requirements for the degree
MSc (Engineering Management) at the
University of Stellenbosch
Supervisor: Mr. Konrad von Leipzig
Department of Industrial Engineering
March 2010
Abstract
Several studies have shown that abnormal returns can be generated simply by buying past winning stocks and selling past losing stocks. Being able to predict future price behavior by past price movements represents a direct challenge to the Efficient Market Hypothesis, a centre piece of contemporary finance.
Fund managers have attempted to exploit this effect, but reliable footage of the performance of such funds is very limited. Several academic studies have documented the presence of the momentum effect across different markets and between different periods. These studies employ trading rules that might be helpful to establish whether the momentum effect is present in a market or not, but have limited practical value as they ignore several practical constraints.
The number of shares in the portfolios formed by academic studies is often impractical. Some studies (e.g. Conrad & Kaul, 1998) require holding a certain percentage of every share in the selection universe, resulting in an extremely large number of shares in the portfolios. Others create portfolios with as little as three shares (e.g. Rey & Schmid, 2005) resulting in portfolios that are insufficiently diversified. All academic studies implicitly require extremely high portfolio turnover rates that could cause transaction costs to dissipate momentum profits and lead the returns of such strategies to be taxed at an investor’s income tax rate rather than her capital gains tax rate. Depending on the tax jurisdiction within which the investor resides these tax ramifications could represent a tax difference of more than 10 percent, an amount that is unlikely to be recovered by any investment strategy.
Critics of studies documenting positive alpha argue that momentum returns may be due to statistical biases such as data mining or due to risk factors not effectively captured by the standard CAPM. The empirical tests conducted in this study were therefore carefully designed to avoid every factor that could compromise the results and hinder a meaningful interpretation of the results. For example, small-caps were excluded to avoid the small firm effect from influencing the results and the tests were conducted on two different samples to avoid data mining from being a possible driver. Previous momentum studies generally used long/short strategies. It was found, however, that momentum strategies generally picked short positions in volatile and illiquid stocks, making it difficult to effectively estimate the transaction costs involved with holding such positions. For this reason it was chosen to test a long-only strategy.
Three different strategies were tested on a sample of JSE mid-and large-caps on a replicated S&P500 index between January 2000 and September 2009. All strategies yielded positive abnormal returns and the null hypothesis that feasible momentum strategies cannot generate statistically significant abnormal returns could be rejected at the 5 percent level of significance for all three strategies on the JSE sample. However, further analysis showed that the momentum profits were far more pronounced in “up” markets than in “down” markets, leaving macroeconomic risk as a possible explanation for the vast returns generated by the strategy. There was ample evidence for the January anomaly being a possible driver behind the momentum returns derived from the S&P500 sample.
Introduction
The main critic of momentum investing is the Efficient Market Hypothesis (EMH), a fundamental theorem in contemporary finance. The EMH claims that past price information cannot be used to predict future price patterns, one of the core principles upon which momentum investing relies. Jegadeesh and Titman (2001) remark that “the momentum effect represents perhaps the strongest evidence against the Efficient Market Hypothesis”. It is safe to say that momentum investing is one of the most disputed topics in investment finance academia today.
Momentum investing was used by investors and fund managers long before the academic debate even started. One of the most prominent examples is Gerald Tsai, who used a momentum approach to manage Fidelity’s Capital Fund with great success throughout the bullish “Go-Go” years on Wall Street from 1958 to 1965 (Ellis & Vertin, 2001). Today momentum investing is utilized by many mutual fund managers and private investors. Momentum investing is a widespread investment style in the US and other equity markets (Taffler, 1999). Jeff Saunders, fund manager of the UK Growth Fund and the winner of the 1997 and 1999 Standard and Poor's Micropal award for the best UK mutual fund, publicly attributes his investment success to the principle of running the winners and cutting the losers (Saunders, 2004).
Tom de Lange1 outperformed the FTSE/JSE All Share index over most of the past decade using a unique momentum investing strategy. He also conducted several back tests for different periods on JSE stock price data and found that he could earn abnormal returns in almost every randomly selected period in the history of the JSE, even when taking trading costs into account.
Momentum research to date investigates hypothetical trading strategies that are far from being implementable in practice. There exists sufficient evidence of successful practical implementations of size and value strategies2; but a similar practical implementation of a momentum strategy has never been formally documented (Keim, 2003).
1.2 PURPOSE OF THE STUDY
While the methodologies used by momentum researchers (e.g. Jegadeesh and Titman, 1993; Conrad and Kaul, 1998) to date were found to be able to earn abnormal returns it is questionable whether such strategies can be readily implemented in practice. On the other hand, it is likewise questionable whether practical strategies similar to the one used by De Lange (2009) yield abnormal returns when tested in an academic setting.
This paper will seek to test the practical approach followed by De Lange (2009) which relies on technical indicators and reflects the restrictions imposed by practical portfolio management and taxation considerations within a formal academic framework to establish whether momentum strategies are viable in practice.
While De Lange’s results could be explained by factors such as data mining bias, this paper will seek to design and conduct a robust statistical test of De Lange’s method. This will entail simulating De Lange’s approach on two different sets of historical data and recording returns and risk measures.
This study is very relevant as little or no academic research has taken on such a perspective. Most published momentum studies focus on proving the existence of the momentum anomaly or investigating the sources of momentum profits, rather than testing the performance of realistic and implementable investment strategies based on the momentum effect (Rey & Schmid, 2005).
1.3 RESEARCH QUESTIONS AND HYPHOTHESES
The research questions and hypotheses of the study deal with the profitability of feasible momentum strategies.
Hypotheses:
H0: Feasible momentum strategies do not yield statistically significant abnormal returns.
Ha: Feasible momentum strategies yield statistically significant abnormal returns.
Rejection of the null hypothesis would lead to accepting the alternative hypothesis.
More general research questions pertaining to the subject area include:
- Are feasible momentum strategies profitable across different markets?
- Do the optimized technical momentum indicators used in practice deliver superior portfolio performance as opposed to simply ranking stocks in terms of past performance as done in most academic studies?
- Do the momentum returns persist through time and through different macroeconomic states?
- Are momentum profits robust with regard to trading costs?
The hypotheses and research questions will be refined in Section 6.1 and form the core focus of this dissertation.
1.4 SCOPE OF THE STUDY
This study is conducted in fulfillment of an MSc (Engineering Management) degree, which requires a relatively narrow focus on a subject area. It does not necessitate the creation of new theory. However, a formal framework for testing feasible momentum strategies such as the one used by De Lange (2009) has never been devised before, in essence requiring the creation of new knowledge and a new testing framework.
As this report is compiled from the perspective of engineering management, basic financial concepts terminology will be discussed in more detail than in the case of conventional papers stemming from this context.
Engineering can be defined as: “The application of scientific and mathematical principles to practical ends such as the design, manufacture, and operation of efficient and economical structures, machines, processes, and systems.” Engineering management involves managing engineered solutions. In other words, engineering is concerned with applying theoretical knowledge to a practical problem. Managing portfolios is similar to managing any other complex system. Establishing whether feasible momentum strategies can earn abnormal returns is a practical problem that requires to be substantiated by academic theory in order to arrive at a result that can be used by practitioners.
This dissertation fuses the academic theory around momentum investing with a practical investment strategy and its results have practical and academic implications.
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