Trading biases refer to psychological tendencies and irrational behaviors that may affect traders' actions. These biases can lead to poor decision-making and significantly impact trading outcomes. We will explore the most common trading biases below, including what they are and how they can negatively affect your strategy.

What is anchoring bias?
Anchoring bias is a cognitive bias that occurs when traders rely too heavily on a single piece of information or past experiences when making decisions. In simple terms, it is a tendency to form further perceptions based on first impressions.

Anchoring (also known as the anchoring effect) is part of behavioral finance, which studies how emotions and other external factors influence economic choices.

Anchoring bias example
The trader buys the UK 100 index CFD. The market is bullish at the start of the trading session. Since the trader mainly relies on information regarding the 'bull market' received earlier that day, he is confident that the market will continue to rise that day. Even when there are obvious signs of market weakness, they still maintain a bullish outlook.

What is confirmation bias?
Confirmation bias is a cognitive bias that affects how we process information. It was first identified by the Greek philosopher Thucydides, but the term was coined by British psychologist Peter Wason in the 1960s.

The experiments at the time revealed that people tend to favor information that confirms their existing beliefs. Subsequently, this phenomenon was redefined as a tendency to test hypotheses in a one-sided manner, focusing only on one outcome while ignoring other facts.

Confirmation bias example
The trader holds a long position in Tesla. Despite ongoing news about Tesla's capacity issues and increasing competition, the trader chooses to focus on Elon Musk's bullish tweets because one of his previous tweets led to a price increase.

What is familiarity bias?
Familiarity bias, as a cognitive bias, leads people to prefer information or items that are familiar to them.

In trading, this means that traders are more likely to make trading decisions based on their experiences rather than objectively assessing the situation. For example, familiarity bias may mean that you only trade stocks of companies located in your country, in familiar industries, or globally recognized companies.

Familiarity bias example
The UK trader's stock portfolio is entirely composed of UK stocks, as he sees more news coverage about UK stocks. This may mean that the trader misses out on potentially more lucrative areas for diversification (such as certain emerging markets).

What is herding bias?
Herding bias refers to the tendency of people to rationalize a certain behavior based on the fact that many others are doing the same thing. From the perspective of trading psychology, this may manifest as trading an asset simply because other traders consider it a hot asset, which may lead to asset bubbles.

The herd mentality can also lead to panic buying (or selling) when more and more people are doing the same thing.

Traders with herding bias believe that the more people there are, the safer it is, and that following the crowd will yield the desired results. The herding mentality is deeply rooted in us; no one deliberately goes with the flow.

Herding bias example
During the late 1990s to early 2000s dot-com bubble, many people went crazy for tech companies related to the U.S. internet while ignoring the fundamentals of these companies. As a result, tech stock prices soared sharply and then crashed.

What is hindsight bias?
Hindsight bias refers to the tendency for people to exaggerate their original guesses about an event after learning the outcome. It is also known as 'the hindsight effect' or 'the Monday morning quarterback effect.' It can occur in various situations, from sports events to elections to weather, and can influence trading psychology.

Trading involves making a multitude of predictions about market directions, which assets to invest in, and what types of derivatives to trade. Traders may need to make hundreds of decisions in a short period. If only a few predictions are accurate, the hindsight effect may lead traders to believe they have a golden touch, while in reality, their prediction accuracy may be quite low.

Hindsight bias example
Inexperienced traders made money on their initial trades. This could be due to their possession of helpful information, good luck, or their actual shrewdness. However, traders do not truly understand why the market is moving as it is.

Regardless of the true reasons for a trader's initial success, they believe their good fortune is inevitable, leading them to take unnecessary risks, which in turn signifies the beginning of losses.

What is negative bias?
A simple definition of negative bias is when traders remember and overly focus on negative trading outcomes, allowing emotions like fear and anxiety to influence future decisions.

Negative bias is part of behavioral finance, which studies how emotions and other external factors influence economic choices.

Negative bias example
The trader previously opened a long position in Apple CFDs. Due to various factors, the trade ended in a loss. As a result, the trader became overly fixated on the loss outcome, leading them to make decisions based on fear and irrational assumptions rather than market trends and analysis. Thus, even when market conditions improved, the trader refused to trade again.

What is overconfidence bias?
Overconfidence bias refers to the tendency of people to overestimate their abilities and knowledge, leading to excessive confidence in decision-making. Overconfidence in financial trading can be detrimental to traders and lead them to make mistakes, resulting in losses.

Overconfidence example
An example of overconfidence bias in trading is when, despite receiving negative news or signals, traders still believe that asset prices will continue to move in their favor.

Suppose a trader made a profit while going long on an Amazon CFD. He is confident that prices will continue to rise, leading to holding the position for too long, which means that when the price trajectory changes, he may suffer significant losses.

What is recency bias?
Recency bias refers to the tendency of people to focus solely on recent performance or outcomes when judging the quality of an asset. In other words, traders with this bias tend to consider recent price movements, news, or information while ignoring or not considering historical situations.

Recency bias example
An inexperienced trader decides to start trading stocks. After doing some research, he identifies 3 companies to invest in. Based on the data from these companies over the past 10 years, their average annual returns were 20%, 30%, and 50%, respectively.

The preferred choice should be companies with a 50% return over the past decade. However, the trader decided to abandon this company because he learned that an investor from the group had recently invested in a company that ultimately went bankrupt.

Despite the lack of any connection between bankrupt companies and companies with a 50% return, a negative association was created in the trader's mind, influencing his decision.

What is self-attribution bias?
Self-attribution bias, also known as self-serving bias, is a cognitive bias in trading where a person attributes positive outcomes to their own abilities while blaming losses on bad luck or other uncontrollable factors.

Self-attribution bias in trading can lead to overconfidence and blind risk-taking, as traders may overestimate their abilities during winning streaks and refuse to acknowledge their mistakes during losses.

Self-attribution bias example
In trading, some examples of self-attribution bias include overly crediting victories to one’s own abilities, blaming losses on external factors, exhibiting excessive confidence, and ignoring past mistakes. This bias can lead to over-risk-taking behavior, refusal to learn, hindsight bias, confirmation bias, inaccurate self-assessment, and overemphasis on short-term results.

What is survivorship bias?
In finance, survivorship bias refers to the tendency of people to view 'surviving' stocks as representative of overall performance, while ignoring those that failed or exited the market due to poor performance or other factors. This can lead traders to make erroneous decisions.

Survivorship bias example
In 2020, trader and software developer Michael Harris tested and wrote an article about the effect of survivorship bias on cross-sectional momentum on the Price Action Lab blog.

He tested a trend-following strategy and applied it to two sets of historical stock market data: one set containing delisted stocks and another set without. Since delisted stocks typically perform poorly before delisting, excluding these stocks made the test results appear more favorable. However, this practice introduced survivorship bias, making the strategy's performance seem better than it actually was. Based on this finding, Harris concluded:

Not considering survivorship bias can lead to extremely misleading results. In many cases, when survivorship bias and other sources of bias are compounded, the actual outcomes are random.

What is loss aversion bias?
Loss aversion is a cognitive bias that refers to the tendency to experience greater negative emotions and psychological distress when losing something compared to the positive emotions associated with gaining something. In trading, a simple definition of loss aversion bias is the tendency to focus on avoiding losses rather than trying to achieve equal gains.

Loss aversion bias example
The trader holds a long position in Meta CFDs. The stock starts to decline. Driven by loss aversion, the trader becomes overly fixated on the losing position. Even though the market shows clear signs of a long-term bearish trend beginning, the trader refuses to close the position to minimize losses and decides to hold on until prices recover. However, the stock continues to decline, and the trader suffers greater losses. This behavior is often referred to as the 'sunk cost fallacy.'

How to minimize trading biases
Regardless of the bias, you can take steps to minimize its impact. The following suggestions can help you trade more objectively, reducing the influence of emotions and misleading data.

Seek diverse information: Refer to various information sources rather than relying solely on one data point or news headline. This helps to more comprehensively and accurately predict trading potential. Learn more about the market and how to trade through our market guide.

Follow trading rules: Establishing strict trading rules can help avoid impulsive or irrational decisions. For example, you can set a percentage limit for the allocation of a single asset in your portfolio.

Diversified portfolio: Diversifying your portfolio by trading various assets or instruments helps avoid over-reliance on any particular position.

Control your emotions: Maintain discipline. Trading can be a highly emotional activity, especially when sudden market news leads to drastic fluctuations.

Use a systematic approach: Implementing a systematic trading approach can reduce the overall impact of emotional biases. This approach may involve establishing a clear set of trading criteria and adhering to them rather than relying on intuition or subjective judgment.

Keep a trading journal: A trading diary or log can help you track your decision-making process and your gains and losses, thereby identifying trading mistakes and analyzing whether anchoring bias exists.

Even if the impact of biases on your trading may not be significant, you still need to develop a solid strategy. Understand your trading strategy in detail. Not ready to enter real trading? Practice trading risk-free with a demo account.