Trading Bias – The Most Common Trading Biases (How To Deal With Them) – Quantified Strategies For Traders And Investors

Last Updated on September 19, 2022

Trading bias, you better have an understanding of the most common ones. When your money is at risk, you easily get fooled by your behavioral biases. Trading is about decision-making, and you better understand your strengths, weaknesses, and what puts your emotions on fire.

This article explains the most common trading biases, why it’s essential to understand them, and how you can deal with and minimize your trading biases. We suggest a quantitative approach is the best way to minimize emotions from trading.

Finding profitable edges and strategies are just one part of three in becoming a profitable trader:

Finding good strategies and trading edges.
Having proper risk management. Even good strategies lead to an increased risk of ruin with the wrong capital allocations.
Knowing yourself and minimizing behavioral mistakes.

Biases fall in category number three. You will not make it as a trader by relying on just one of the three pillars – all of them are equally important to succeed.

The first principle is that you must not fool yourself and you are the easiest person to fool.

– Richard Feynman

Trading biases defined:

Investing is not the study of finance. It’s the study of how people behave with money.

– Morgan Housel

A bias is a cognitive error or behavioral mistake. When a trader is biased, it limits rational decision-making because feelings and emotions intervene. Your judgment deteriorates because the decision is based on emotions and not quantitative or fundamental reasoning.

Rolf Dobelli defines cognitive errors well in his book The Art Of Thinking Clearly:

The failure to think clearly, or what experts call a “cognitive error”, is a systematic deviation from logic – from optimal, rational, reasonable thought and behaviour. By “systematic” I mean that these are not just occasional errors in judgement, but rather routine mistakes, barriers to logic we stumble over time and again, repeating patterns through generations and through the centuries. For example, it is much more common that we overestimate our knowledge than that we underestimate it. Similarly, the danger of losing something stimulates us much more than the prospect of making a similar gain. In the presence of other people we tend to adjust our behaviour to theirs, not the opposite. Anecdotes make us overlook the statistical distribution (base rate) behind it, not the other way around.

Why is it important to know about our trading biases?

As mentioned above, knowing your biases is essential to understand your limits, possibilities, and how to improve your trading. Furthermore, knowing the collective forces in the markets gives you an edge. Mark Douglas writes this on page 56 in The Disciplined Trader:

Understanding yourself is synonymous with understanding the markets because as a trader you are part of the collective force that moves prices. How could you begin to understand the dynamics of group behaviour well enough to extract money from the group, as a result of their behaviour, if you don’t understand the inner forces that affect your own?

You can be sure that the majority of traders are averse to losses, the majority tends to “anchor”, and we all suffer from confirmation bias. The more you know about biases, the better you understand the market.

The most common trading biases:

Below we have summarized what we consider the most relevant trading biases. There exists almost an unlimited number of trading biases and the ones below are just a few. They are not ranked in any particular order:

Optimism/Pessimism Bias:

Your past and recent results heavily influence your trading. If you have done well, you feel great and optimistic. If you have performed poorly, you are pessimistic. This rollercoaster, of course, influences your trading. Being pessimistic can even make you stop trading or tinkering with your systems – at the exact wrong time.

Many have an “all or nothing” approach: if you fall short of your expectations, you see yourself as a failure.

Overconfidence bias:

Most of us tend to overrate our knowledge and capabilities. If we ask you how a zipper works, most confirm they do know how it works. However, if we ask you to make a technical drawing and a written instruction, hardly anyone does it correctly.

We do the same in the markets. We believe we understand what’s going on, but most of us have no clue.

Self-serving bias – “resulting”:

This is the habit of taking credit for positive outcomes but blaming others when the outcome is negative. Annie Duke writes in Thinking In Bets that we tend to attribute a good result to skills and a negative outcome to bad luck.

Furthermore, we judge the quality of the decision on the outcome, which, of course, is wrong. Good decisions often lead to bad outcomes, and a good outcome could be the result of a bad decision. Be careful to pat yourself on the back. The markets are a lot more random than we think. Think in probabilities.

Anchoring:

Most of us tend to focus on certain types of information and ignore other sources. Likewise, we anchor the share price and wait for the stock to drop down to a previous level – that might never come. Anchoring often leads to the Martingale bias: to lower the cost price, you use a double down trading strategy. Unfortunately, the market has no memory so it won’t care about your cost price.

Recency bias:

This is the tendency to focus on the latest piece of information and ignore older. We forget the past faster than we like to admit.

Loss aversion:

Loss aversion is well known among traders, but traders tend to ignore it. What looks good in backtesting, when you know the end result, might be difficult to execute in real trading. We react more negatively to a loss than positively to a similar gain. Likewise, we prefer steady gains instead of bigger lump-sum gains. The difference of making 100 000 five years in a row compared to making 500 000 in year one and nothing in the last four, is huge. The first example gives you five years of joy, while the latter gives you four years of frustration. The sequence of the returns is important.

Volatility aversion:

This is, to our knowledge, not a “formal” bias, or it might go under another bias. But given two equal outcomes, most traders prefer the one with the least volatility, as mentioned above about loss aversion. That is understandable, but the result is that you might skip many strategies that would work well together with other strategies.

But you can’t escape from volatility: A little volatility is good, as long as it doesn’t ruin your mind or bankroll. Volatility makes you more robust in the long run.

Moreover, no or little volatility might suggest you are an accident waiting to happen. Nassim Nicholas Taleb used an interesting analogy on volatility in one of his books:

Italy has had many different administrations and political turmoil since ww2, while Saudi Arabia has had one ruling family during the same period. Does this make Italy riskier than Saudi Arabia? When they do change administration in Saudi Arabia, you can expect it to be bloody (literally). The lack of volatility often ends in “blowing up”.

Confirmation bias:

We stick to information that confirms our beliefs. This is the wrong approach. Whatever you do in life, you should always question your beliefs. You should welcome conflicting evidence and thoughts! Your learning curve improves.

A relative of the confirmation bias is the framing bias: when someone makes a decision because of the way information is presented to them, rather than based just on the facts.

Gambler’s fallacy:

The Gambler’s fallacy is the erroneous belief that if a particular event occurs more frequently than normal during the past it is less likely to happen in the future. As a trader, you need to think in probabilities.

Bandwagon bias (herd mentality):

As of writing, March 2021, the fear of missing out (FOMO) is likely a major cause of the euphoric stock market. FOMO is a potent force. We like to stick to the crowd, even when we are skeptical. The bandwagon bias is tough to resist.

Familiarity bias:

Warren Buffett is famous for investing within his circle of competence. This is, of course, very smart, but you should aim to increase your circle of competence gradually. Traders like to use familiar strategies, but it’s hard to change your habits when the market conditions change. Traders need to adapt and change all the time. It would help if you always were on the lookout for new edges and strategies.

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Hindsight bias:

Everything looks easy in hindsight, you “knew it” all along, but we tend to forget it wasn’t so evident before it happened. How do you deal with hindsight bias?

Write down your reasoning before you make a decision. You’ll be surprised that most things are not as evident as it seems.

Survivorship bias:

Survivorship bias in trading is the systematic overestimation of the chance of success and is pretty similar to selection bias. Both biases suggest we form conclusions on incomplete information.

The bias happens when you make a selection process based on the past but “accidentally” ignore specific data. A good example is backtesting. For example, if you want to check a basket of consumer staples’ performance, you might start by selecting the stocks included in the ETF with ticker code XLP. Unfortunately, you are only looking at the stocks that have thus far turned out to be winners and survivors, and you ignore the ones that might have been kicked out from the ETF, for example, because of poor performance or bankruptcy. You only look at the survivors, not the ones who have failed.

Status quo bias:

Traders stick to what works. But what works today rarely works tomorrow. Most strategies stop working. Status quo is dangerous because you are not preparing for tomorrow. Trading requires constant research for new strategies and styles.

The law of small numbers bias:

Quantitative trading is about the law of large numbers. To better understand the strategy or sample you are investigating, you need a sample size that represents it. You don’t get that by using small sample sizes, perhaps even risking survivorship bias in the selection process. Moreover, strategies that trade just a few times per year might influence your annual return by “outliers”.

The Medallion Fund and Jim Simons use a short time frame in their trades to increase the number of observations (to make it statistically significant).

Understanding the most common trading biases:

Most likely, you will never overcome your biases completely, but just knowing the most common trading biases is a great start. Thus, the goal should be to minimize your trading biases and make your trading as rational as you possibly can.

How do you do that? We believe quantitative trading offers the best way to minimize behavioral mistakes and trading biases. Quantitative trading reduces your trading biases and errors because the computer creates a “layer” between you and the trading. The computer doesn’t think and is not susceptible to emotions – a computer only does what it’s told. And last but not least, always trade smaller than you like.