Say No To “Monte Carlo Fallacy”

Joseph and Stephen are at the stadium watching a cricket match.

Joseph: “Roger has come for batting. He has not hit one century from the last 7 matches. I bet he will hit a century this match.

Stephen: ” Why? I think he is going through a rough patch. He will probably be able to hit a century today.”

Joseph: “No way, Stephen. I have looked at his batting stats. He has hit one century every 8 matches from the past 2 years. Since he has not scored a single century from the last 7 matches, he will have to hit a century this time. I am betting $1000 on him.”

Stephen: “Are you sure?”

Joseph: “I am damn sure. Roger is due for a century.”

This is a typical example of a “Monte Carlo Fallacy”. It is also called “The Gambler’s Fallacy”. This is called the Monte Carlo Fallacy because it occurred in Monte Carlo Casino in Las Vegas in 1913. Let’s not dig deep into history. But let us understand what is Monte Carlo Fallacy and why as investors we need to say no to MONTE CARLO FALLACY.

Monte Carlo Fallacy is an erroneous belief that a certain event will more likely to happen or less likely to happen, considering the previous event or series of events. This line of thinking is incorrect since past events do not have a connection to the events which will occur in the future.

There are 2 common ways this fallacy is committed. In both cases, an individual is assuming that some result is “due” because of the previous event of a series of events.

  • Events whose probabilities of occurring are independent of one another

For example, one toss of a coin doesn’t affect the next toss of the coin. Each time the coin is tossed there is 50% chance of it landing heads and 50% chance of landing tails. Suppose a person tosses a coin 8 times and gets head each time. If he concludes the next toss will be tails because the tail is due, then he has committed the Gambler’s fallacy. This is because the results of previous tosses have no influence on the outcome of the 9th toss.

  • Events whose probabilities of occurring are dependent on one another

For example, a horse has won 50% of his races over the past 3 years. Suppose the horse has lost the last 8 races and has 8 left. If the person believes that the horse will win the next 8 races because the horse has used up his losses and is due for a victory, then the person betting on that horse would have committed the Gambler’s Fallacy. The person might be ignoring the facts that the result of one race can influence the result of the next one. For example, the horse might have been injured in one match which would lower chances of winning in the next races.

This can be extended to investing as some investors believe that they should liquidate a position after it has gone up in a series of subsequent trading sessions. This is because they would have committed the Gambler’s Fallacy by not believing that the position is likely to continue going up. Another Gambler’s Fallacy what investors commit is by holding onto the losing stock thinking that the position has gone down in a series of trading sessions and there is a high chance of stock to go up.

Not all predictions are fallacious. If the predictions are backed by the right rationale, then they will be reasonable to accept. Hence, determining whether or not the “Monte Carlo Fallacy” is being committed requires some basic understanding of the laws of probability. This article will help the investors to reckon his action is a fallacy or a rationale based decision.

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