I would like to thank Dr. Enrique Schroth of Cass Business School who agreed on being a supervisor on a topic that is relatively unconventional and rather untypical to be found in a business research project for a master ’ s level. I would like to also thank Dr. Richard Fairchild of University of Bath for supporting the idea and believing in its potential implications. Although I believe that my methodology for testing the hypothesis might be insufficient and in fact could be further developed, I still believe it should be considered as a stepping- stone for future research to take on.
This paper starts off by introducing the efficient market hypothesis, and then moves into the main trading strategies that are being used in equity markets. Trading strategies such as fundamental analysis and technical analysis are introduced. Efforts in behavioral finance are then presented to help explain biases that have impact on stock prices. Then, it alters the main focus of the paper towards understanding the function of clearing prices through the aid of price discovery and matching algorithms in stock exchanges. The hypothesis of having clearing prices as a function of the trading strategies being used in a market place given certain conditions is tested. The method used is a theoretical agent-based model. The paper finds preliminary signs of self-fulfilling prophecy as a phenomenon that seems to prevail in equity markets. Finally, it gives recommendations accordingly regarding new areas of research in financial markets.
Efficient Market Hypothesis (EMH)
Financial markets operate on an automated exchange basis. Early research conducted by Eugene Fama in the 1960s proposed that markets are efficient, and by efficient it meant that the no arbitrage principle would hold, and hence trading would be pointless. The hypothesis suggests that all information is reflected on clearing prices instantaneously, and hence “prices are always right” (Cuthbertson and Nitzsche 2008). EMH implies that no investor would be able to generate consistent abnormal returns in a market place, and hence active management would be worthless. It also suggests if private information were obtained by one investor, then the marginal cost to exploiting such a benefit would offset the benefit itself (Ackert and Deaves 2010).
Supporters of EMH claim that active trading strategies such as fundamental analysis and technical analysis are all ineffective attempts that are just less worth than the passive index-tracking strategies (Cuthbertson and Nitzsche 2008). Early research testing the validity of the Efficient Market Hypothesis have generally supported its claims, however more recent research has shown contradicting results and anomalies that are against what the efficient market model suggests (Shiller 2003). Such results were in the form of finding excessive volatility in stock prices due to excessive trading taking place. Moreover it has been observed that some stock prices move for non-economic reasons. The gap between what should be happening in financial markets according to EMH and what is actually happening is partially explained by efforts conducted in behavioral economics.
Anomalies in the context of financial markets mean any trading behavior that seems to depart from what the standard models expect, and by standard models meaning the efficient market model. Examples of anomalies found through empirical tests were various. One anomaly that would contradict the EMH principles would be the fact that many market players show overreaction and under reaction to economic signals taking place in the market as well as observing a trend-chasing behavior (Cuthbertson and Nitzsche 2008). This is considered to be irrational behavior, however research papers in finance have not strictly agreed on distinguishing between and actually define what should be considered rational and irrational. The impact of such behavior in financial markets leads to changes in price discovery; causing prices to deviate from what standardized models would anticipate.
For the EMH to hold, only one of three propositions needs to be present. The first proposition suggests that market players should be practicing rational behavior through maximizing their expected utilities with the aid of economic models given their limited resources (Ackert and Deaves 2010). Evidence clearly shows otherwise, and in fact it is absurd to believe that each player is strictly a utility maximizing agent (Shiller 2003). Research conducted by Elton, Gruber and Busse in 2004 found that market players have a tendency to hold undiversified portfolios, suffer from company-bias investing and hold losing stocks for too long. Proponents of EMH counter argue with their second proposition claiming that still if irrational behavior is present and random, then the errors produced from such irrational behavior should be uncorrelated and hence offset each other reaching the same good equilibrium (Ackert and Deaves 2010). Unfortunately, it has been proven that significant portion of such irrational behavior tends to be correlated (Ackert and Deaves 2010).
A well-known example of irrational behavior would be the Dot-com bubble in the 1990s. Shiller coined the term feedback dynamics to explain the bubble from a clearing price standpoint. A bubble simply takes place due to early speculative round of price increase, and then attracts another group of investors to buy as well, resulting in another round of price increase and so on. The process could go on for quite some time. Such uninterrupted rounds of price increases initiate the bubble. This phenomenon could be easily explained by a concept in sociology that will be later discussed, which is called a self-fulfilling prophecy. It should be easy to conclude that such trading behavior helps prices depart from fundamental principles suggested by the EMH.
EMH’s third proposition states that even if there are correlated errors, it should create an opportunity for arbitrage in the eyes of traders who are following the fundamental principle, then such smart traders would arbitrage it away immediately and thus reach the good equilibrium (Ackert and Deaves 2010). Research has shown that traders sometimes do not take such opportunities due to the risks they carry (Shiller 2003).