Cognitive Biases in Stock Market Investing

📌 Confirmation Bias

🔹 Tendency to seek, interpret, and remember information that confirms our pre-existing beliefs while ignoring contradictory data.

📌 Anchoring Bias

🔹 Fixating on an initial reference point (such as a stock’s purchase price) and basing future decisions on that reference, even when conditions have changed.

📌 Representativeness Bias

🔹 Assuming that a past pattern will continue in the future without considering fundamental factors. Example: Believing that a stock that has risen significantly will keep rising indefinitely.

📌 Availability Bias

🔹 Making decisions based on the most easily recalled information rather than the most relevant.

📌 Overconfidence Bia

🔹 Believing that one has above-average skills in predicting the market, which can lead to excessive trading or taking unnecessary risks.

📌 Loss Aversion Bias

🔹 Feeling more pain from a loss than satisfaction from an equivalent gain, leading to irrational decisions such as holding losing stocks too long or panic selling.

📌 Herd Mentality Effect

🔹 Following the majority’s decisions without conducting independent analysis. This contributes to market bubbles and sharp declines.

📌 Status Quo Bias

🔹 Preference for keeping a portfolio unchanged, even when better opportunities exist in the market.

📌 Illusion of Control

🔹 Believing one can control or predict market events that are actually random.

📌 Mental Accounting Bias

🔹 Treating money differently depending on its source or intended use rather than evaluating it globally. Example: Refusing to sell a losing stock while waiting to "recover losses."

📌 Sunk Cost Fallacy

🔹 Clinging to an investment simply because money has already been lost, instead of assessing whether it remains a good choice.

📌 Recency Bias

🔹 Giving more weight to recent information than historical data, potentially leading to impulsive decisions.

📌 Hindsight Bias

🔹 Believing that what happened was "obvious" after the fact, reinforcing overconfidence in future predictions.

📌 Survivorship Bias

🔹 Focusing only on successful cases while ignoring failures, leading to unrealistic expectations.

📌 Disposition Effect

🔹 Selling winning stocks too early while holding onto losing stocks for too long.

📌 Optimism Bias

🔹 Believing things will turn out better than statistically probable, leading to overvaluing investments and taking unnecessary risks.

📌 Pseudo-Certainty Bias

🔹 Preferring investments with guaranteed outcomes (even with low returns) over those with higher potential but more uncertainty.

📌 Halo Effect

🔹 Judging an investment based on a positive characteristic of the company (e.g., a well-known CEO) instead of analyzing it objectively.

📌 Authority Bias

🔹 Blindly trusting expert recommendations without conducting independent analysis.

📌 Familiarity Bias

🔹 Investing only in well-known companies (like Apple, Tesla, etc.) without considering other potentially more profitable opportunities.

📌 Endowment Effect

🔹 Assigning higher value to a stock simply because it is already owned, rather than analyzing it objectively.

📌 Inertia Bias

🔹 Avoiding investment decisions out of fear of making mistakes, even when good opportunities exist.

📌 Money Illusion Bias

🔹 Failing to consider inflation when evaluating investment returns. A 10% gain in a year with 8% inflation is not the same as a 10% gain in a year with 2% inflation.

📌 Illusion of Market Control Bias

🔹 Believing that technical analysis or a specific strategy guarantees control over market behavior.

📌 Anchoring to Initial Information Bias

🔹 Making decisions based on the first piece of information received about a stock without updating the analysis with new data.

📌 Excessive Intuition Bias

🔹 Relying too much on intuition without data to support investment decisions.

📌 Accessibility Bias

🔹 Giving more weight to recent or striking information instead of the most relevant data.

📌 Memory Effect Bias

🔹 Making decisions based on personal past experiences, even when current data suggests otherwise.

📌 Overreaction Bias

🔹 Exaggerating the importance of news or market events and making hasty decisions.

📌 Too Big to Fail Bias

🔹 Believing that a large and well-established company can never go bankrupt or face a crisis.

📌 Self-Attribution Bias

🔹 Attributing stock market successes to personal skill while blaming external factors for losses.

📌 Contagion Effect

🔹 Being emotionally influenced by market sentiment without solid fundamentals.

📌 Surprise Bias

🔹 Ignoring the possibility of unexpected events that can affect the market (black swan events).

📌 External Attribution Bias

🔹 Blaming the government, the Fed, banks, or news for losses instead of reviewing one’s strategy.

📌 "I Don’t Want to Know" Effect

🔹 Avoiding portfolio review to avoid seeing losses, leading to delayed or poor decisions.

📌 Action Bias

🔹 The tendency to feel that "doing something" is better than "doing nothing," even when the best option might be to hold and wait.

📌 Hot-Hand Fallacy

🔹 Believing that because an investment has performed well repeatedly, it will continue to do so in the future.

📌 Reference Point Bias

🔹 Comparing an investment’s performance to an arbitrary benchmark (e.g., comparing a portfolio to the S&P 500 even when it has assets with different risk levels).

📌 All-or-Nothing Bias

🔹 Thinking that an investment is either 100% good or 100% bad, without considering nuances and intermediate risks.

📌 Lottery Fallacy Bias

🔹 Believing that investing in very cheap stocks (penny stocks) will yield massive returns, like a lottery.

📌 Cyclical Behavior Bias

🔹 Believing that past market cycles will repeat exactly the same way in the future, without considering changes in the economy or technology.

📌 Too Good to Be True Effect

🔹 Distrusting a good investment opportunity just because it seems too good, without analyzing it rationally.

📌 False Correlation Bias

🔹 Assuming that two market events are related just because they happened at the same time, without a true causal relationship.

📌 Bandwagon Effect Bias

🔹 Investing in assets just because many others are (market trends like Bitcoin, meme stocks, etc.).

📌 "I Can’t Be Wrong" Bias

🔹 Believing that a strategy that worked in the past will continue to work without adjustments.

📌 Pattern Recognition Illusion Bias

🔹 Seeing patterns in price charts where none actually exist, leading to decisions based on imaginary trends.

📌 Multiple Choice Effect Bias

🔹 Thinking that having more investment options is always better, which can lead to analysis paralysis.

📌 "I Can’t Lose" Bias

🔹 Refusing to accept that an investment may be bad and refusing to sell at a loss, hoping for a recovery that may never come.

📌 Expert Bias

🔹 Believing that because an investor is experienced or famous (like Warren Buffett or Michael Burry), they are always right.

📌 "If Only I Had Stayed" Bias

🔹 Regretting selling a stock before a big price increase, which can lead to emotional decision-making in future investments.

📌 Exaggerated Panic Bias

🔹 Overreacting to negative news and selling prematurely without deep analysis.

📌 Past Performance Trap Bias

🔹 Choosing investments based only on past performance without analyzing future potential.

📌 Quick Money Illusion Bias

🔹 Believing that making easy money in the stock market is always possible with little effort, without considering risks.

📌 Underestimation of Risk Bias

🔹 Ignoring investment risks simply because they have recently performed well.

📌 Novelty Bias

🔹 Overvaluing a company or technology simply because it is new, without assessing its long-term viability.