Anchoring Bias: When Your Average Entry Becomes the Market's Benchmark
If you have thought, 'I bought at $3,200, so I only need it to return to $3,200 to break even,' you have experienced anchoring. It is the psychological tendency for an initial number to become a fixed reference for every later judgment. The problem is that this reference may have no connection to the market. The market does not know what you paid.
Where do anchors come from?
Trading anchors usually come from one of these four sources. They are all numbers from the past, without a causal connection to future prices.
1. Your average entry
'I bought at $3,200' → below is a loss; above is a gain.
2. A previous high or low
'This coin once reached $4,800' → $2,000 now looks cheap.
3. The first price you saw
The price when you first became interested is imprinted as the 'normal price.'
4. Someone else's target
A claim you saw that it will reach '$10,000' remains your benchmark.
These numbers are dangerous because they become benchmarks without verification. A previous high of $4,800 is only a record that trades once occurred there. It does not establish fair value or a reason for price to return. Once the anchor is fixed, however, every current quote is automatically translated into 'how cheap it is compared with $4,800.'
How an average-entry anchor changes decisions
The most damaging anchor is often your own average entry. It exists only in your account, yet once it becomes an anchor, your entire trading judgment reorganizes around it.
Current price: $2,800; downtrend; support broken
No anchor: someone considering a new entry
'The trend is down. This is no place to open a long.' → Wait.
Anchored: someone holding at a $3,200 average
'It is 12% cheaper than $3,200. Buying more lowers my average.' → Add.
→ Opposite conclusions from the same chart.
The difference is not market information but one personal entry price.
This produces the phrase, 'I will sell as soon as I break even.' It effectively delegates the exit condition to your account instead of the market. Whether the market has any reason to revisit $3,200 is no longer examined; only waiting for that price remains. Combined with loss aversion, this can make taking a stop almost impossible.
The next stage is averaging down. A lower average entry lowers the breakeven price, so the situation looks improved relative to the anchor. What improves is only one number, while the potential loss and exposure grow. The calculation is covered in averaging down.
First purchase: 1 ETH at $3,200 → current value $2,800; loss -$400
Second purchase: add 1 ETH at $2,800 → average $3,000; holding 2 ETH
Anchored view: breakeven falls from $3,200 → $3,000: an improvement.
Actual account: loss remains -$400; committed capital rises from $3,200 → $6,000.
After another 10% decline:
• Without averaging down: -$680
• With averaging down: -$1,200
→ The average-entry number improves, while actual risk grows.
The previous-high anchor: the illusion of cheapness
This anchor often operates when selecting assets. A large percentage decline from the high is automatically read as undervaluation.
Coin A: high $100 → now $10, down 90%
Coin B: high $12 → now $10, down 17%
Anchored view: A looks much cheaper.
What is actually known: both currently cost $10.
For A to return to $100, it needs +900%.
Recovering a 90% decline is very different from recovering a 50% decline, which needs +100%.
→ Recovery difficulty increases nonlinearly as losses deepen.
The same asymmetry applies to account losses. Losing 50% requires a 100% gain to recover; losing 80% requires 400%. See drawdown for the structure. 'It has fallen a lot, so it will rise soon' expresses distance from an anchor, not evidence.
How to weaken the anchor
Anchoring is a cognitive habit, so deciding to ignore it does not make it disappear. It is more realistic to exclude it from the decision structure than to try to erase it.
1. Write exit criteria before entering.
Fix stop and target beforehand → less opportunity for the entry price to become an anchor.
2. Ask, 'Would I buy now if I had no position?'
If not, the anchor may be the only reason for holding.
3. Express P&L in R instead of percentages.
Think '-1R' instead of '-12%' → use risk as the reference.
4. Reduce the display of average entry and P&L.
Do not look at position information while assessing the chart.
5. Write scenarios in advance.
'Exit if $2,900 breaks' → remove room for reinterpretation afterward.
The second question is especially practical: 'If I held nothing right now, would I open this direction at this price?' If the answer is no, the reason for keeping the position may be the average-entry anchor, rather than market evidence. That is attachment rather than analysis.
The third response changes the anchor's unit. Showing P&L as a multiple of the risk you agreed to accept, R, shifts the reference from 'the price I paid' to 'the amount I chose to risk.' See expectancy and R-multiples for the calculation. Position sizing determines the amount represented by 1R.
Records reveal the anchor
Anchoring does not feel like a bias to the person experiencing it. At the time, it feels rational. This makes reviewing written records afterward one of the few practical ways to detect it.
1. How many trades had their stop moved after entry?
2. Were most of those moves in the less favorable direction?
3. Do exit reasons contain 'breakeven,' 'average entry' or 'previous high'?
4. Is average P&L on averaged-down trades worse than on single entries?
5. Do longer-held trades have larger losses?
The first two together suggest anchoring is undermining stop rules. The fifth suggests losing positions were held longer, the familiar pattern of short-lived winners and long-lived losers. See keeping a trading journal for recording methods. Writing the entry rationale beforehand also helps expose confirmation bias.
Another approach is to prevent discretionary stop changes. Place the stop order when entering, so it is already in the market before the anchor can intervene. See stop-loss orders for order types and placement methods.
Useful references and unhelpful anchors
Not every reference point is bad. The distinction is whether the number comes from the market or your account.
Market-derived references: usable
• Price zones with concentrated volume
• Support and resistance with repeated bounces or breaks
• Volatility-based stop distances
→ Numbers other participants also observe
Account-derived references: unsuitable
• Your average entry
• Your breakeven price
• The first price you saw
→ Personal numbers the market does not know
Support and resistance matter because many participants watch those prices together. Your average entry is a number you alone focus on, giving the market no reason to react there. Both may look like price reference lines, but their nature differs completely.
Summary
2. Your average entry is a powerful anchor; the market does not know it.
3. 'I will sell at breakeven' delegates the exit condition to the account instead of the market.
4. Averaging down improves the average-entry number while increasing actual risk.
5. A fall from the high is not proof of undervaluation; recovery difficulty is nonlinear.
6. Respond by setting exits before entry, asking whether you would buy now and thinking in R.
7. Detect it in journals by counting stops moved in the unfavorable direction.
8. Use market-derived references and discard account-derived ones.
What you paid has no causal connection to the future price. Simply noticing that the number is influencing your judgment can interrupt one route through which stops are delayed and averaging down begins.
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