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 is 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
What are trading biases? A definition of a trading bias
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.
Let’s list the most common trading biases:
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:
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.
Practical trading bias example: optimism/pessimism bias
Let’s shed some light on a practical example of both optimism/pessimism bias and loss aversion (see more on loss aversion below). The text below was written by Oddmund Groette on his personal blog in 2012:
The optimism/pessimism bias is a common one among traders. After a good run, you feel great and optimistic and increase your size.
Opposite, after a bad run of “luck”, you feel pessimistic and reduce your size. However, good and bad runs happen all the time in trading. I have myself been prone to this bias many times. Here’s an example from my own trading:
Back in 2007, I had a very nice run over the summer where my trading performed very well. I felt good, I was very optimistic, and increased the size to make more money. I was greedy.
Then, out of the blue, some Black Swan event happened, which my backtest never captured. I suffered my biggest loss where two months’ profits were wiped out in two minutes.
Out of fear, the next day I reduced my position size as much as I could. Unfortunately, the next day was a quadruple-witching day where all options and futures contracts expire. Historically, these days have frequently been “monster” days contributing to a huge portion of my profits. Perhaps needless to say, the day turned out to be one of those monster days. If I had traded my normal size, I would have made 3x the loss the day before and had my best trading day ever.
Likewise, one of the best mutual funds from 2000 until 2010, Ken Heebner’s CGM Focus fund, gained 18.2% annually while the typical investor lost 11% annually. How is this possible? That’s because the “dollar-weighted returns” take into account the capital inflows and outflows. Investors typically bought into the fund after it had a strong run and then sold as it went down. In 2007 the fund surged 80% and it attracted huge amounts of inflows, while many of those sold during the GFC in 2008/09 when prices went down. Hebner said:
A huge amount of money came in right when the performance of the fund was at a peak. I don’t know what to say about that. We don’t have any control over what investors do.
The conclusion is simple: It doesn’t matter how good your trading systems are if you can’t execute and trade them properly. The main obstacle for traders is their own mental biases.
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. Things are often not as obvious as it seems at first glance.
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 (a strongly recommended book) 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.
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.
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 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.
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”.
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. Charlie Munger says that if you don’t change 180 degrees on something important every year, you are not thinking hard enough.
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.
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.
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.
Perhaps our cheap Trading Edges might give you some new and fresh ideas?
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 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.
How To Overcome Trading Biases (Tips, Tricks, And Hacks)
How to overcome trading biases is one of the most important things in trading. Mankind has come a long way in problem solving and technical advancements, but most of us still suck when it comes to financial planning and managing our investments. Why is that?
We have created artificial intelligence and we send people to outer space, yet most of us are hopeless when it comes to decision making. A lot of research determines that the average DIY investor underperforms the indices by a wide margin. Why is that? Because they do behavioral mistakes.
How can you overcome your trading biases? You can overcome your trading biases by trading smaller than you like, using mechanical trading rules, and implementing checklists. Let’s explain:
Scientists argues evolution has made us prone to fast decision making. Our brains are designed to keep us safe from risk and dangers to survive, and this is a different matter than what is required in the financial markets.
Don’t get us wrong, you first need to survive in the financial marketplace before making any money. But to survive on the savanna and in the markets requires different skillsets. On the savanna, you can’t sit down to evaluate the pros and cons when you face danger – you use your intuition to get away as fast as possible. In the markets, it pays off to do a little thinking, the so-called System 2:
Daniel Kahneman’s System 1 and System 2 explained
Daniel Kahneman, a pioneer in behavioral studies, calls the two different types of thinking for System 1 and System 2. System 1 is fast and intuitive while System 2 is the slow and analytical one. This is how Kahneman defines his two systems in his bestselling book Thinking, Fast And Slow:
System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control. System 2 allocates attention to the effortful mental activities that demand it, including complex computations. The operations of System 2 are often associated with the subjective experience of agency, choice, and concentration.
The marketplace is complex and full of noise and randomness and thus ut rarely helps to make knee-jerk decisions. Our investing instincts are mostly flawed, unfortunately.
The famous financial writer Morgan Housel once said that investing is not the study of finance, it’s the study of how people behave with money. Housel’s definition explains why we often get it so wrong when money is at stake.
A bias is a behavioral mistake – a cognitive error. In The Art Of Thinking Clearly, Rolf Dobelli defines cognitive errors as systematic deviations from logic and rational behavior. Dobelli uses the word “systematic” because these are not occasional mistakes we make, but barriers to logic we stumble upon over and over again. This is not something that has happened recently, but it’s ingrained mistakes done through generations and centuries.
Here are two examples of biases: we are much more likely to overestimate our knowledge than we are to underestimate it. Likewise, we repeatedly make statistical errors that overlook the most basic statistical distributions to jump to the wrong conclusions.
How to overcome trading biases
To diagnose the problem we first need to understand why we have biases. In medicine, you can take pills to relieve pain, but the pills only treat the symptoms – not the cause. In trading, you don’t have a pain killer. You have to go to the root of the problem and look at the cause (which should be more used in health and medicine as well). Once you understand how your behavior influences your trading, you can overcome or minimize them to increase your profits.
Is it possible to completely remove behavioral mistakes? Probably not. But you get a long way by addressing the issues so you can minimize the damage done by knee-jerk decisions. Just by being aware of them is a great start.
No detachment to money reduces behavioral biases
Almost all the behavioral mistakes come from detachment to money. Anyone can be successful trading a paper account. But the problem is that a paper or demo account never resembles real trading with real money. You have no skin in the game.
To make it worse, most traders use leverage and this magnifies your detachment to money. With real money, you are more likely to tweak or stop trading a strategy in the midst of drawdown, something you wouldn’t do in a demo account. Most traders fold at drawdowns more than 20%.
Trade smaller than you like
How do you execute a strategy properly? You do that by trading small. This is not contradictory. By trading small, you remove or reduce emotions. Trading small is an efficient way of reducing detachment to money!
Moreover, by trading small you reduce the risk of ruin. If you trade big using leverage and get run over by a black swan, you might lose a huge portion of your account.
Trade small and make your are diversified in terms of asset classes, strategies, and time frames.
Quantified strategies – algorithmic trading
Most likely, you will never overcome your biases completely, but just knowing them is a great start. Thus, the goal should be to minimize 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.
Quantitative trading reduces your biases and errors because the computer creates a “layer” between you and your trading. The computer doesn’t think and is not susceptible to emotions – a computer only does what it’s told.
Using a checklist minimizes unforced errors
Morningstar once had a checklist for minimizing cognitive errors. We can’t find the link now, but we’re eager students of the markets and wrote them down:
- Write down your biases on a piece of paper. This makes you aware of them.
- Turn down the noise. Be careful of getting overloaded by social media or the mainstream media.
- Force yourself to make slow decisions. Morningstar called them speed dumps for decisions.
- Look for confronting arguments. Be your own devil’s advocate.
- What is your margin of safety? What can go wrong?
- Thoughtfulness matters.
One of our favorite books is Atul Gawande’s The Checklist Manifesto. A checklist makes you avoid unforced errors, improves your outcome without any increase in skills, and saves you time in the investment process.
Recommended reading to learn about biases
There exists a ton of literature on most of the biases mentioned in this article. If you want an easy read we recommend Rolf Dobelli’s The Art Of Thinking Clearly.
Still, the pioneer in the field of behavioral studies is Daniel Kahneman. His book from 2011, Thinking , Fast And Slow, is brilliant, but a bit more “academic” than Dobelli’s.
The best advice on how to overcome trading biases:
The best advice we can give on how to overcome trading biases is to trade smaller than you like. When you have no detachment to money, the less stress you have about your positions.