Introduction: The Theory
Gamblers fallacy is an argument that bases its argument on the occurrence of random events, in that if the occurrence of a certain event is frequent currently the there will be an infrequent occurrence in the future. The fallacy depicts that if something happens more often or if there is a positive performance, there will be a rare occurrence in the future, or the performance will be negative. The fallacy is based on independent events where the outcome of one event does not influence the other also called random events. The fallacy argues that if a certain outcome is favored then as you progress the chances of obtaining the same outcome are minimized (Cowan, J. E., 2001). For example if a mother has given birth to four girls in the previous births the chances of giving birth to a girl in the fifth birth are minimal or that the outcome will be negative which is that she will give birth to a boy.
The fallacy is argued by the use of an unbiased coin whereby through tossing the coin and obtaining the outcomes of whatever face that lands on the top the probability of obtaining the same outcome decreases after two consecutive outcomes that are similar are obtained. For example, the probability of getting a head in the first toss is 50% and decreases to 25% in the second toss since the fallacy argues that a negative outcome is expected (Cowan, J. E., 2001).
The fallacy is applicable in independent events where the results of one event are not influenced by the others outcome. However, in certain instances the outcome could be due to certain externalities, for example, if a firm makes losses for two consecutive years then this may be attributed to outside factors that are beyond the firms’ control. The fallacy argues on the basis of probability obtained from auto-correlated situations that the negative outcome is expected after successive occurrence of the event. This is evident by obtaining the probability of the results of rolling the dice if the number, say four, appears three consecutive times then the probability of obtaining a different number is higher as the number of rolls increase (Oppenheimer, D. M., & Monin, B., 2009).
The Evolving of the Theory into the Present State
The general thinking among people is that random events are related, and this correlation determines the probabilities of each of the event taking place depending on the occurrence of related events. The gambler’s fallacy theory as explained above considers this generality as the basis of its argument. People tend to think that even for random events, there is a correlation between events and thus there is a possibility of predicting the next outcome dependent on the patterns of occurrence of previous outcomes (Ayton, P., & Fischer, I., 2004). This scenario has been a common idea among many investors world. Since investors are well informed about the ongoing market trends, they tend to think they have enough experience top enable them make the most appropriate decision through a consideration of the previous trends. There experience in the market is considered a key factor in such situations.
However, it is important to note that the market structure and behavior are unpredictable. This unpredictability arises from the very fact that the market is controlled by internal and external factors. The internal factors can easily be controlled, but the external factors are less likely to be controlled. When controlled, these external factors will already have caused significant changes in the market structure and trends (Gilson et al., 2003). Such uncertainties make the market trends random in terms of the expected results. This randomness has led to making of wrong decisions by the investors who rely on their experience in the market.
In the contemporary society, the business field is dynamic. With the emergence of technology, there is availability of information about events occurring around the world in the world of business. This is just by a click of a button. This availability of information has meant that anyone involved is well informed about the best performing trends. In this case, the investors will most likely consider the options ahead by applying the gambler’s fallacy theory. This is the perception that since a certain ‘aspect’ has performed well over a defined period of time, its likelihood of performing well in the near future is very low. The best decision would, therefore, be to relinquish or liquidate the ‘aspect’.
The generality of the ending of a streak is frequently applied in the investment sector. Investors will tend to anchor their next plan of action on new markets opportunities as soon as the current well-performing opportunity is deemed too risky to invest. This scenario, more often than not leads to wrong decision making. An opportunity could remain relevant over a period of time. There are more complications that result from such an occurrence. The investors could result to mind reconstruction as soon as they realize they made the wrong decision on the past. This reconstruction is based on the belief that they had predicted such an occurrence just before they took the seemingly wrong decision (Gilson et al., 2003). This leads then to the situation of regret. The regret theory applies in two perspectives. In one, the investor made a decision to forego the opportunity. Afterwards, there was a significant rise in the value of this opportunity. In the second perspective, the investor undertook the initiative of investing in the currently well-performing opportunity but later there was a decline in the returns. In both scenarios, there is a case of regret. This is the randomness with which the investment market reconstructs itself depending on internal and external controls.
However, the investors prefer to apply the gambler’s fallacy theory even after it has been proven to be dangerous. This is certainly due to the misconception that the economic models of predicting future opportunities and market trends are bureaucratic in nature and extremely engaging. The easier option is to rely on experience and relate the past patterns with the current to predict the future. The fact that some decisions based on gambler’s fallacy have gone the investors’ way in the past has been a key pillar to its application even after it has been found risky in business. This is what is used as the validity illusion for the gambler’s fallacy. The returns are always priced high, and the instances when such predictions have gone the right way form the blueprint for its implementation (Ayton, P., & Fischer, I., 2004).
The gambler’s fallacy takes into consideration only the possibility of gains and avoids as much as possible the fact that losses are part of the market structure that cannot be wished away. This is the bias which in the long term hurts the investment plan based on the fallacy since there are little measures that the fallacy accepts are important in the case of a loss (Gilson et al., 2003).
Applications of the Gambler’s Fallacy in Real Life
In real life, situations there are many instances and decisions that are driven by fallacy. Many exemplars in the contemporary world enormously drive to a belief that Gambler’s fallacy is applied. In life, we are faced by decisions to make whereby we weigh options. In any case, decision-making has some aspect of uncertainty. Humanity has a deeply entrenched notion that pattern and hence prediction can be derived from random events or occurrences. Random events do not follow a given pattern. As such, a previous outcome, can affect a second is a total myth or fallacy. Gamble’s fallacy in our daily lives has the effect of making us believe that we can create patterns and build predictions from events that are probability-driven. For instance, it would be termed as gambler’s fallacy to believe that if the head appears in three consecutive tosses of a coin, chances are high that the fourth toss will be the tail. Such biases have continued to affect human decision making in economics, finance and behavior (RABIN, M., & VAYANOS, D., 2010).
Lottery playing and casinos are scenarios where gambler’s fallacy has proved to work. A typical example of this is in slot machines. It is very common to hear or see people sticking to one machine for hours, carrying the notion that, with every loss, they come closer to hitting the jackpot. The probability of winning or losing at the slot machine is fifty-fifty. This means that, with a single pull, one could hit the jackpot. This is just but an example of gambler’s fallacy applying in the contemporary society. In the trade industry, one may be subjected to long streaks of making huge gains and subsequently, a trader is compelled to believe that a long streak of making gains, an equally long streak of losing awaits and as such, the trader opts to cut down his/her investment in which ever trading activity. The reverse of this also happens whereby after a long streak of losing a trader may be convinced to pump more resources into the trade awaiting the profit-making streak (Oppenheimer, D. M., & Monin, B., 2009).
There are many examples in the business world where gambler’s fallacy seems to be operational. In the stock exchange, there can be many exemplars of gamble’s fallacy. In an instance where, the company is performing exceedingly well in the stock markets, investors in the company may be compelled to dispose of their shares. It is the gambler’s fallacy effect, which works to the conviction that, after a good performance in the stock, the shares of such a company would start to perform poorly (RABIN, M., & VAYANOS, D., 2010). To avoid the effects of the anticipated downfall of the company’s shares in the stock, investors start to dispose of their shares. This means that such investors believe that, after a long favorable period, there are high chances that an unfavorable event is set to proceed. The performance of the company’s shares in the stock is solely determined by economic trends in the industry that it operates. This means that mythical beliefs drive the decisions of such investors. Stock exchange aside, strategists and financial advisors hugely fall victim of gambler’s fallacy. Financial advisors and strategists develop patterns using past happenings> they study the dynamics of the market and related events. However, chances of the future taking the course of the pattern are equally probable (Cowan, J. E., 2001).
In casinos and roulette, players usually fall victim of bad betting. To win or lose in a casino is determined by probability, and there is no pattern that the roulette board follows. In many times, people wait for a long streak of one color, say, black. When black hits four times, then players believe that chances of roulette hitting on red are high. If for the fifth time, black hits, players increase their bet on red. The casino is a matter of probability and gambling one may end up losing a lot of money.
Conclusion
The gambler's fallacy is experienced on the day to day basis. Human have naturally formed a habit of trying to form patterns based on past happenings. Except for events that are mutually exclusive, predictive patterns built can be out of the gambler’s fallacy. In daily decision-making processes, it is wise to base decisions on realities or principles that define the happening of events. For instance in the stock exchange it is recommendable to base decisions on the concepts of the stock exchange other than basing decisions on myths or fallacies.
References
Ayton, P., & Fischer, I. (2004). The hot hand fallacy and the gambler’s fallacy: Two faces of subjective randomness? Memory & Cognition.
Cowan, J. E. (2001). Gambler's fallacy. Erin, Ont: Porcupine's Quill.
Gilson, R. J., Kraakman, R. H., & John M. Olin Center for Law, E. (2003). The mechanisims [sic] of market efficiency twenty years later: The hindsight bias. Cambridge, MA: Harvard Law School, John M. Olin Center for Law, Economics, and Business.
Oppenheimer, D. M., & Monin, B. (2009). The retrospective gambler's fallacy: Unlikely events, constructing the past, and multiple universes.
RABIN, M., & VAYANOS, D. (2010). The Gambler's and Hot‐Hand Fallacies: Theory and Applications. Review of Economic Studies.
