Trading Bias: 30 Psychology Biases And Strategies to Overcome Them
Trading bias or behavioral mistakes, 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.
Trading bias is also called cognitive dissonance bias and mental accounting bias.
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:
Optimism/Pessimism Bias
Your past and recent results heavily influence your trading. If you have done well, you feel great and optimistic and fall prey to the optimism bias. 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.
Overconfidence bias
Most of us tend to overrate our knowledge and capabilities – something called overconfidence bias. 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. We are liable to the Dunning-Kruger Effect bias in trading.
Another effect of the overconfidence bias is the clustering illusion bias in trading. When you are overconfident, you see patterns in random data. This also happens when you experience the hot hand fallacy.
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. This is also called the outcome bias in trading.
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.
Self attribution bias
Self-Attribution Bias in Trading: This bias occurs when traders credit their successes to personal skill while blaming failures on external factors. It can lead to overconfidence, poor decision-making, and a failure to learn from mistakes. Traders often misjudge their abilities, which can result in unnecessary risk-taking and repeated errors.
Overcoming this bias requires self-awareness, maintaining a trading journal, and seeking external feedback to foster better decision-making and long-term success. A bias a bit similar to self serving bias is the self attribution bias. Self-attribution bias leads traders to credit personal skills for successes while blaming external factors for failures, hindering learning and effective decision-making. This is a very common bias in all aspects of life.
Anchoring Bias
Anchoring Bias in trading 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.
Anchoring bias occurs when traders fixate on initial data, like the purchase price of a stock, which influences future decisions. This bias leads to irrational choices, such as holding onto losing positions or ignoring new market conditions. To counteract anchoring bias, traders should diversify their information sources, use rule-based trading, and conduct thorough research to ensure objective decision-making.
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.
Recency bias
Recency bias is the tendency to focus on the latest piece of information and ignore older. Recency bias in trading refers to the cognitive tendency to place too much emphasis on recent market events when making decisions. This can lead traders to react impulsively to short-term fluctuations, causing them to abandon long-term strategies.
To overcome this bias, traders are encouraged to focus on historical data, maintain a disciplined approach, diversify their portfolios, and use systematic trading methods. Financial advisors and AI-driven tools can also help mitigate the influence of recency bias in trading decisions. We forget the past faster than we like to admit.
Availability Bias in Trading
Availability bias in trading refers to the tendency to make decisions based on recent or easily accessible information rather than thorough analysis. This bias can lead traders to overreact to recent market events, skewing their risk perception and decision-making.
To counter this, traders should diversify information sources, set predefined trading rules, and focus on systematic decision-making processes. Recognizing the bias and employing strategies to mitigate it can help improve long-term trading outcomes.
Availability Heuristic Bias In Trading
Availability bias in trading refers to the tendency to make decisions based on recent or easily accessible information rather than thorough analysis. This bias can lead traders to overreact to recent market events, skewing their risk perception and decision-making.
To counter this, traders should diversify information sources, set predefined trading rules, and focus on systematic decision-making processes. Recognizing the bias and employing strategies to mitigate it can help improve long-term trading outcomes.
Time Horizon bias
Time Horizon Bias in Trading refers to the tendency of investors to focus on short-term gains at the expense of long-term wealth accumulation. This bias is often driven by emotional reactions to market fluctuations, such as present bias, recency bias, and loss aversion.
To mitigate this bias, strategies include setting clear investment goals, diversifying portfolios, and using digital advice tools to maintain a long-term perspective. Overcoming time horizon bias leads to more disciplined and consistent investment outcomes.
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.
Loss aversion is a behavioral economic concept that refers to the human tendency to strongly prefer avoiding losses to acquiring equivalent gains. In other words, the pain of losing money is much greater than the pleasure of gaining an equivalent amount. This can lead to traders and investors making irrational decisions based on the fear of losing money, rather than a rational analysis of market conditions.
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.
Why does loss reversion happen?
It happens because it can be traced back to our evolutionary history, where avoiding losses was a survival mechanism. However, this tendency can lead to suboptimal decision-making in modern financial markets. In trading, loss aversion can cause traders to hold on to losing positions for too long, or to sell winning positions too early, in an attempt to avoid further losses.
Risk Aversion Bias
Risk aversion bias leads traders to prioritize capital preservation over potential returns, often resulting in missed opportunities. This bias is rooted in the fear of losses and the preference for low-risk investments, such as bonds or dividend-paying stocks.
Overcoming risk aversion involves strategies like diversification, setting rational goals, and leveraging technology for more objective decision-making. Continuous education and awareness of this bias can help traders make more balanced, informed decisions.
The Disposition Effect in Trading
As a result of loss aversion, you might be liable to the Disposition Effect in Trading. The disposition effect in trading is when investors sell winning stocks too soon and keep losing ones for too long. The Disposition Effect is a behavioral bias where investors sell assets that have appreciated too quickly while holding onto depreciating ones for too long. This happens due to emotional factors such as loss aversion and regret avoidance.
To overcome this bias, investors can set clear goals, regularly monitor portfolios, and use automated trading tools to minimize emotional decision-making, leading to more rational investment choices.
Escalation Of Commitment Bias In Trading
Escalation of commitment bias in trading occurs when traders continue with a losing position due to prior investments, leading to greater financial losses. This bias is driven by psychological factors like self-justification, emotional attachment, and fear of admitting mistakes.
To avoid it, traders should set clear exit points, regularly review their trading strategies, and utilize tools like trading algorithms and risk management systems to maintain objectivity. Recognizing this bias is crucial for making rational trading decisions.
Volatility aversion
Volatility aversion 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 in Trading
Confirmation bias in trading is a cognitive bias where traders seek out and emphasize information that confirms their preexisting beliefs, leading to skewed decision-making and ignoring contradictory evidence.
This bias can result in overconfidence, selective memory, and poor trading outcomes. To combat confirmation bias, traders should seek diverse perspectives, establish structured decision-making frameworks, and use unbiased research tools. Managing emotions like fear and greed is also critical for avoiding this bias in trading decisions.
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.
Illusion of Control in Trading Bias
The Illusion of Control in trading bias refers to a cognitive bias where traders overestimate their influence over market outcomes. This bias can lead to overconfidence, excessive risk-taking, and poor decision-making.
Traders often misinterpret random events as patterns they can control, resulting in misguided strategies. To mitigate this bias, it’s important to adopt evidence-based decision-making, critical thinking, and mindfulness practices to stay objective and improve trading performance.
Framing Effect in Trading Bias
The framing effect in trading bias refers to how decisions are influenced by how information is presented rather than its content. Traders might make different choices when the same data is framed positively (gains) or negatively (losses).
This bias can lead to risk-aversion in positive frames and risk-seeking behavior in negative ones, impacting decision-making. To mitigate this bias, traders should practice critical thinking and rely on credible advice to avoid emotional responses to framing.
Gambler’s fallacy
The Gambler’s Fallacy in trading bias is a cognitive bias where traders mistakenly believe that past events influence future outcomes, leading to poor decision-making. For instance, traders may expect a market reversal after a streak of gains or losses, even though each trade is independent. This fallacy can cause premature exits from profitable trades or doubling down on losing positions.
To counteract this bias, traders should focus on systematic analysis, risk management, and avoiding the influence of past events. 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.
Related Reading: Trading Psychology
The bandwagon effect bias in trading
The bandwagon effect bias in trading occurs when investors follow the crowd, often leading to inflated asset prices and market bubbles. Driven by psychological factors like the fear of missing out (FOMO) and a desire for social acceptance, traders may make impulsive decisions without conducting independent analysis.
To avoid this bias, traders should prioritize thorough research, maintain a well-defined trading plan, and remain skeptical of popular trends.
FOMO in Trading
FOMO in Trading refers to the fear traders experience when they worry about missing out on profitable opportunities in the market. This emotional response often leads to impulsive decisions, such as chasing trends or entering trades without proper analysis. FOMO traders tend to ignore their trading plans, leading to poor risk management and potential losses.
Overcoming FOMO requires discipline, sticking to a well-defined strategy, and managing emotions like greed and envy to avoid destructive trading habits.
Herding bias
Herding bias in trading occurs when investors follow the actions of the majority, often driven by emotion and instinct, rather than conducting their own independent analysis. This behavior can lead to suboptimal decisions, market inefficiencies, and contribute to bubbles or crashes.
Avoiding herding bias requires thorough research, creating a personalized trading plan, and maintaining a long-term perspective to make informed, independent decisions. Recognizing the psychological drivers behind herding behavior is essential for improving trading outcomes.
Decoy Effect Bias in Trading
The decoy effectt bias in tradingis a cognitive bias that occurs when traders are influenced by an additional, less attractive option (the decoy) in decision-making. This decoy is strategically placed to make another option appear more appealing by comparison. In trading, the decoy effect can distort choices between investments or strategies, pushing traders to select an option that they may not have considered otherwise. Recognizing this bias is crucial to avoid making irrational decisions based on artificially skewed comparisons.
The decoy effect bias influences decision-making by introducing a less appealing option that makes one of the other choices seem more attractive, leading to potentially irrational trading decisions. The opportunity cost is always big in trading. Why go for a second alternative when you have a potentially better alternative? The decoy effect applies to all aspects of life and decision-making.
Sample Size Neglect Bias in Trading
Sample size neglect bias occurs when traders draw conclusions based on small data sets, often overestimating short-term performance or fund manager skills. This bias leads to misguided decisions and portfolio instability.
To mitigate this, investors should use larger data samples, employ statistical methods, and seek diverse perspectives for more accurate analysis.
An example includes the dot-com bubble, where small sample data led to unrealistic expectations and significant losses. Recognizing this bias is crucial for informed trading decisions.
Narrative bias in trading
Narrative Bias in Trading refers to the tendency of investors to prioritize compelling stories over factual data when making investment decisions. This bias can lead to poor financial choices as investors may be swayed by emotional narratives rather than objective analysis.
Recognizing and mitigating narrative bias through data-driven approaches and long-term goals can improve decision-making. Financial advisors can also help by distinguishing between factual insights and engaging stories.
Familiarity bias in trading
Familiarity bias occurs when traders prefer familiar investments, like domestic stocks or their employer’s stock, leading to reduced diversification and increased risk. This bias limits portfolio growth opportunities and exposes traders to concentrated risks. To overcome it, strategies like diversification, financial advisors, and continuous education are essential. Recognizing the psychological influence of familiarity bias helps traders make more balanced, informed decisions, improving long-term portfolio performance.
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?
Hindsight Bias in Trading
Hindsight bias in trading leads traders to overestimate their predictive abilities after an event has occurred, often resulting in overconfidence and risky decisions. It distorts memory, making past outcomes seem inevitable. To counter this bias, traders can keep an investment diary, conduct thorough data-driven analyses, and consider alternative scenarios to maintain objectivity in future decisions.
Recognizing and addressing hindsight bias is essential for making more informed and balanced trading decisions. Everything looks easy in hindsight, you “knew it” all along, but we tend to forget it wasn’t so evident before it happened.
Survivorship bias in trading
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 in trading
Status quo bias is the tendency to stick with familiar investments or strategies, even when better opportunities are available. In trading, this bias leads to missed opportunities and suboptimal performance due to a resistance to change. Investors often prefer the comfort of known options and fear potential losses, which can hinder growth.
Overcoming this bias requires diversification, leveraging data, and regularly reviewing portfolios to ensure alignment with financial goals and current market conditions. 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
The Law of Small Numbers Bias in trading refers to the tendency of traders to draw broad conclusions from small data samples. This bias can lead to overconfidence in short-term trading results or unreliable backtest outcomes, as small samples often do not accurately represent long-term performance. Traders affected by this bias may misinterpret randomness as patterns, making decisions based on insufficient evidence. Recognizing and avoiding this bias is key to making more informed and reliable trading decisions.
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).
Endowment Effect in Trading
The Endowment Effect in Trading refers to the phenomenon where individuals assign a higher value to an item they already own, compared to a similar item they do not own. This is because people tend to feel an emotional attachment to items they possess, leading them to place a higher value on it.
The endowment effect was first demonstrated in a seminal experiment by behavioral economists Daniel Kahneman, Jack Knetsch, and Richard Thaler (the pioneers of behavioral finance). They gave a group of participants coffee mugs and then asked them to value the mugs compared to a similar item, a pen. The results showed that participants placed a higher value on the mugs they already possessed compared to the pens.
The Endowment Effect has the following implications:
For instance, traders may hold onto losing positions for too long, as they may feel an emotional attachment to their investments. This can result in a failure to realize losses, leading to poor investment outcomes.
Similarly, investors may be hesitant to sell winning positions, as they may place a higher value on their investments compared to similar items they do not own. This can lead to missed opportunities to take profits, reducing the overall return on investment.
Regret Aversion Bias in Trading
Regret aversion bias occurs when traders make decisions to avoid future regret rather than following rational strategies. This emotional response leads to risk-avoidant behaviors like holding onto losing stocks or missing out on profitable opportunities.
To combat regret aversion, traders should develop structured plans, leverage automation, and review performance regularly. Understanding and managing this bias can significantly improve decision-making and trading outcomes.
Projection Bias in Trading
Projection bias occurs when traders project their current emotions onto future market conditions, leading to irrational decisions. For example, traders may become overly optimistic during a bull market, assuming their current success will continue indefinitely.
This bias distorts future predictions, affecting long-term financial performance. To mitigate projection bias, traders should adopt structured decision-making processes, use data analysis, and increase self-awareness through journaling. This helps maintain objective, rational trading strategies.
Base Rate Neglect Bias in Trading
Base rate neglect bias is a cognitive bias where traders ignore the overall statistical probability (base rates) and instead focus on specific, vivid instances or recent events. In trading, this often leads to poor decision-making because traders overlook important long-term statistical data in favor of short-term trends or emotional reactions.
For example, during the housing market bubble, many investors ignored economic indicators that predicted a downturn, focusing only on the continued rise of home prices. This resulted in massive losses when the market crashed. To avoid falling into this bias, traders should always incorporate base rates—such as historical averages and probabilities—into their decision-making process, ensuring a more balanced and rational approach to investing.
This bias can be mitigated by relying on data-driven strategies, maintaining a long-term perspective, and avoiding the temptation to react impulsively to recent market events.
Emotional Attachment Bias in Trading
Emotional attachment bias occurs when traders develop a personal connection to their trades or assets, often leading to irrational decision-making. This bias can cause traders to hold onto losing positions for too long or avoid selling winning positions due to a fear of loss or an emotional connection to past decisions.
Overcoming emotional attachment in trading requires a disciplined approach, including setting predefined exit points, regularly reviewing your trading plan, and using objective tools like automated systems to reduce emotional influences. By focusing on data-driven strategies, traders can minimize the negative impact of this bias on their performance.
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 lack of 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.
If you know yourself, can you better understand the markets?
If you know yourself well, you can better understand markets and thus make more money trading or investing. Mark Douglas writes in Disciplined Trader (page 56):
“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?”
A practical example of a behavioral trading mistake
Let’s show you a very personal, costly trading mistake:
I clearly remember two days in August 2007 where I completely screwed up. It was a Thursday, and all my day trading strategies performed badly, ending my day with my biggest financial loss ever. I probably react twice as badly to a loss as I react positively to an equal gain, like most people, and thus, this loss made me feel pretty bad. I have loss aversion.
The next day was the third Friday of the month when options expire. Historically, this has been the best day of the month (for my strategies), but I was so shaken by the loss the day before, so I scaled down all my strategies as much as I could. Needless to say, Friday was a field day and would have generated 2x times the loss from the day before if I had traded my normal size (I managed to recoup just 20% of my losses).
Even with very good strategies, it’s possible to end up losing because of wrong position sizing behavioral mistakes!
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. This is how he defined
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.
FAQ:
– What are trading biases, and why do they impact financial decision-making?
Trading biases are cognitive errors or behavioral mistakes that affect decision-making in financial markets. They often stem from evolutionary factors that prioritize survival over rational financial planning.
– How can trading biases be overcome for better financial outcomes?
Trading biases can be overcome by adopting strategies such as trading smaller than desired, using mechanical trading rules, and implementing checklists. These methods help minimize emotional responses and enhance rational decision-making.
– Why do DIY investors often underperform market indices, and what role do behavioral mistakes play in this underperformance?
DIY investors often underperform due to behavioral mistakes. Research indicates that the average DIY investor’s underperformance is linked to cognitive errors, and addressing these biases is crucial for better financial planning.
