Anchoring bias occurs when traders fixate on a specific reference point — such as their entry price, an all-time high, or a round number — and make subsequent decisions relative to that anchor rather than evaluating current market conditions objectively. This bias leads to irrational behaviour such as refusing to sell a losing position because the anchor (entry price) feels more 'real' than the current price.
Entry price anchor: evaluating a position based on entry cost rather than current risk/reward. Historical anchor: fixating on an asset's all-time high or a previous price as the 'correct' value. Round-number anchor: giving undue significance to prices like 100, 1000, or 50000. Adjustment failure: insufficient adjustment from the initial anchor when new information arrives. Anchoring affects both entry and exit decisions.
Before entering, ask: 'Would I enter this trade if the price had always been at this level?' Remove historical context from your analysis of the current setup. Use objective criteria (momentum, structure, volume) rather than comparisons to past prices. Evaluate risk/reward from the current price, not from where the asset 'used to be'.
Manage trades based on current technical levels and risk/reward, not on your entry price. Delete entry-price lines from your chart to reduce the anchor's visual pull. Reassess positions weekly by asking: 'If I had no position, would I enter here now?' Use predetermined stop levels that are set before entry and not adjusted after.
Applicable across all timeframes and during all trade management decisions
The most insidious form of anchoring in crypto is fixating on an asset's all-time high — buying an asset at 90% below ATH feels like a bargain, but it tells you nothing about current value or risk. Train yourself to analyse every chart as if you are seeing the asset for the first time. Use checklists and pre-defined criteria to reduce the influence of anchors on your decision-making.
Recency bias is the tendency to overweight recent events and outcomes when making decisions, while underweighting longer-term data. In trading, this manifests as assuming recent market conditions will persist indefinitely — expecting further gains after a rally or further losses after a crash. Recency bias creates a dangerous feedback loop where traders chase recent performance rather than evaluating current probabilities objectively.
The disposition effect describes the well-documented tendency of traders to sell winning positions too early to lock in profits while holding losing positions too long in the hope that they will recover. This behaviour, rooted in loss aversion and mental accounting, systematically reduces profitability by cutting winners short and letting losers run — the exact opposite of what profitable trading requires.
The overconfidence effect causes traders to overestimate their knowledge, skill, and ability to predict market outcomes. After a winning streak, traders often increase position sizes, ignore their rules, and take trades that don't meet their criteria — believing they have a 'hot hand'. Overconfidence typically precedes the largest drawdowns in a trader's career.
Confirmation bias is the tendency to search for, interpret, and remember information that confirms your existing beliefs while ignoring contradictory evidence. In trading, this means once you form a bullish or bearish view, you unconsciously filter information to support your position — ignoring warning signs and overweighting supportive data.