Understand behavioral science and psychology to boost your consistency

Trading Psychology | Overconfidence Bias – How Can I Ever Be Wrong?

Overconfidence is the unwarranted faith in one’s intuitive reasoning, judgments, and cognitive abilities. Studies conducted have shown that people overestimate both their own predictive abilities and the precision of information that they have been given. In addition, people are poorly calibrated in estimating probabilities – events which they think are certain to happen are often less than 100% certain to happen.

 

Overconfidence Bias – How Can I Ever Be Wrong?

 

In short, people think that they are smarter and have better information than they actually do. For example, they may get a tip from a broker or read something off the internet, and they’re ready to take action, such as placing a trade, based on the perceived knowledge advantage. If there is no logical basis for the advantage, then this perceived edge does not exist at all, despite what the trader thinks he knows.

There are two kinds of overconfidence – prediction overconfidence and certainty overconfidence. In prediction overconfidence, the confidence intervals that traders assign to their predictions are too narrow. An example of this is when gurus try to forecast precise price targets. In certainty overconfidence, traders are too certain of their judgments. For example, after entering a “sure-win” trade, traders become blind to the prospect of a loss, and then feel disappointed or surprised that the trade performs poorly. Always keep in mind that trading is a game of probabilities, and nothing is 100%.

How does this affect your trading?

“Too many people overvalue what they are not and undervalue what they are.”
– Malcolm S. Forbes

Trading Psychology | How to Think Like a Trader – Changing your Frame

If we look at the collective participation in the markets, we find many different kinds of people, different kinds of beliefs, and different kinds of theories. These differences create price movements and patterns. To understand and exploit these opportunities, we first need to understand ourselves. We will then be able to choose the kind of strategy best suited to our personality, and at the same time avoid behavioral biases by being aware of them.

 

How to Think Like a Trader – Changing your Frame

 

The theory of limited arbitrage shows that if irrational traders cause deviations from fundamental value, rational traders will often be powerless to do anything about it. In order to say more about the structure of these deviations, behavioural models often assume a specific form of irrationality. For guidance on this, economists turn to the extensive experimental evidence compiled by cognitive psychologists on the systematic biases that arise when people form beliefs, and on people’s preferences. Here are some of them:

Beliefs

A crucial component of any model of financial markets is a specification of how agents form expectations. We now summarize what psychologists have learned about how people appear to form beliefs in practice.

Overconfidence

Extensive evidence shows that people are overconfident in their judgments. This appears in two guises. First, the confidence intervals people assign to their estimates of quantities – the level of the Dow in a year, say – are far too narrow. Their 98% confidence intervals, for example, include the true quantity only about 60% of the time. Second, people are poorly calibrated when estimating probabilities: events they think are certain to occur actually occur only around 80% of the time, and events they deem impossible occur approximately 20% of the time.

Optimism and wishful thinking

Most people display unrealistically rosy views of their abilities and prospects. Typically, over 90% of those surveyed think they are above average in such domains as driving skill, ability to get along with people and sense of humor. They also display a systematic planning fallacy: they predict that tasks (such as writing survey papers) will be completed much sooner than they actually are.

Belief perseverance

There is much evidence that once people have formed an opinion, they cling to it too tightly and for too long. At least two effects appear to be at work. First, people are reluctant to search for evidence that contradicts their beliefs. Second, even if they find such evidence, they treat it with excessive skepticism. Some studies have found an even stronger effect, known as confirmation bias, whereby people misinterpret evidence that goes against their hypothesis as actually being in their favor. In the context of academic finance, belief perseverance predicts that if people start out believing in the Efficient Markets Hypothesis, they may continue to believe in it long after compelling evidence to the contrary has emerged.

Anchoring

When forming estimates, people often start with some initial, possibly arbitrary value, and then adjust away from it. Experimental evidence shows that the adjustment is often insufficient. Put differently, people “anchor” too much on the initial value. In one experiment, subjects were asked to estimate the percentage of United Nations’ countries that are African. More specifically, before giving a percentage, they were asked whether their guess was higher or lower than a randomly generated number between 0 and 100. Their subsequent estimates were significantly affected by the initial random number. Those who were asked to compare their estimate to 10, subsequently estimated 25%, while those who compared to 60, estimated 45%.

Availability biases

When judging the probability of an event – the likelihood of getting mugged in Chicago, say – people often search their memories for relevant information. While this is a perfectly sensible procedure, it can produce biased estimates because not all memories are equally retrievable or “available”. More recent events and more salient events – the mugging of a close friend, say – will weigh more heavily and distort the estimate.

Economists are sometimes wary of this body of experimental evidence because they believe (i) that people, through repetition, will learn their way out of biases; (ii) that experts in a field, such as traders in an investment bank, will make fewer errors; and (iii) that with more powerful incentives, the effects will disappear. While all these factors can attenuate biases to some extent, there is little evidence that they wipe them out altogether.

The effect of learning is often muted by errors of application: when the bias is explained, people often understand it, but then immediately proceed to violate it again in specific applications. Expertise, too, is often a hindrance rather than a help: experts, armed with their sophisticated models, have been found to exhibit more overconfidence than laymen, particularly when they receive only limited feedback about their predictions.

Herd Instinct

If you fall under this category, it means that you follow what the rest of the market is often doing. If there is a new IPO that is hot, or one of the stocks just crashed and word on the streets is that it is a hot buy, or there are rumours flying around of inside news that a certain stock will fly then you will do the same as the rest of the market. This is not always a bad thing because the simple answer to this is: But the market should always be right right? Since everyone is following the market. It is not always true but the market is random and BLINDLY following the market is wrong.

Trading Psychology | The Psychology of the Stoploss – Why is it so Hard?

Many new to trading have the tendency to liquidate positions that show a small profit, yet they keep those positions that show a loss as are unwilling to take a loss, in hope that prices will rebound. Such a counter-intuitive strategy will result in small wins and large losses, but why do people still do it? The new science of behavioral finance psychology may offer an explanation.

 

The Psychology of the Stoploss – Why is it so Hard?

 

1. Disposition Effect

Investors are less willing to recognize losses (which they would be forced to do if they sold assets which had fallen in value), but are more willing to recognize gains. This can be explained by the value function curve, where investors turn more risk-seeking as the stock depreciates. As shown by studies on ex-post returns, it would be more profitable to cut losses fast and let profits run. Hence, investors should treat unrealized losses as a sunk cost, and focus on reducing prospective costs (likelihood of more losses). Unfortunately, irrational hope destroys any edge their analysis provides, thus resulting in an unfair gamble.

2. Loss Aversion / Breakeven Effect

With its roots from prospect theory, this refers to investors’ tendency to strongly prefer avoiding losses to acquiring gains. For loss aversion, investors prefer an uncertain gamble to a certain loss as long as the gamble has the possibility of no loss, even though the expected value of the uncertain loss is lower than the certain loss. For the breakeven effect, investors prefer a gamble that offers the potential of recovering to finish at an aspiration level rather than a certain rate of return.

Some studies suggest that losses are twice as powerful, psychologically, as gains. Hence, investors will cling to the hope (including rationalization) that prices will rebound to their entry price, which they have now established as a reference point. However, this reference point is illogical, since their entry point does not affect the future direction of prices. One question to ask is, “if you don’t have a position now, would you open a new position?”

If prices fall past their stoploss (showing that their analysis was wrong), it means that the odds are now against them. If prices fall but do not hit their stop, and subsequently rises back to breakeven, it actually shows that their initial analysis is still correct (not proven wrong), which means that exiting at breakeven is in fact destroying their winning trades. This will lower their hitrate by causing them to exit winners prematurely.

 

Behavioral Analysis – Value Function Graph

 

How can traders overcome these biases?