In trading decisions, the most hidden cognitive trap often comes not from market noise, but from a seemingly unrelated number. Behavioral psychology calls it the Anchoring Effect: When people judge unknown values, they unconsciously rely on the first information they receive (the "anchor"), even if the information has no logical connection with the current situation. Nobel Prize winner Daniel Kahneman pointed out: "Anchoring is one of the most stubborn biases in human intuitive judgment." In financial markets, this mechanism is quietly distorting the risk assessment and entry timing of countless traders.

Wmax behavioral finance series emphasizes: true objectivity does not mean the absence of anchors, but the awareness that one has been anchored.

Where did the anchor come from? Those reference points you were unaware of

The anchoring effect was first revealed experimentally by Tversky and Kahneman (1974): when subjects were "anchored" by random roulette numbers, their estimates of the proportion of African countries in the United Nations were significantly shifted. In trading, anchors are equally ubiquitous and even more confusing.

The most common anchors include:

Opening cost price: Users regard the buying price as a "reasonable benchmark". If the price is lower than this, it is considered "cheap", and if it is higher than this, it is considered "overvalued"; historical highs/lows: such as "gold once reached 2800, and now 2600 is considered low", ignoring that the current supply and demand structure has changed; media quotes or other people's opinions: an analyst's "target 3000" becomes the psychological threshold.

These anchors are not necessarily wrong per se, but the problem is that the brain uses them as a default starting point rather than as a hypothesis to be tested. All subsequent judgments are fine-tuned around this initial value rather than building an independent valuation from scratch.

How do anchors distort stop-loss and take-profit decisions?

The most direct impact of the anchoring effect is reflected in the exit strategy. When many traders set stop loss levels, they do not base them on volatility or support levels, but simply use "leave if you lose 5%" - this 5% is often derived from a certain past experience or other people's advice, and has nothing to do with the characteristics of the current variety.

What is more typical is the "obsession to get back money": after a position suffers a floating loss, the user keeps a close eye on the opening price, viewing it as the only escape point. Once the price is close to cost, there is a rush to close the position, even if the trend signal is still strong. On the contrary, if the profit does not reach the "expected target" (such as "earn at least 10%"), even if the technical situation weakens, you will refuse to leave the market. The anchor becomes an emotional switch at this moment, rather than a basis for decision-making.

Research shows (Kaustia et al., 2014) that investors' reliance on anchor prices is negatively correlated with their trading experience - novices are more likely to be dominated by a single number in their judgment.

Why do more “rational” people find it harder to break free from anchors?

Ironically, knowledge and experience sometimes strengthen anchoring. Experienced traders often build complex models, but if the initial parameters (such as valuation centers, fluctuation ranges) are based on outdated data, the entire system is built on quicksand. They use more logic to "prove" the rationality of the anchor, but in fact they fall into a double closed loop of confirmation bias and anchoring effect.

For example: A user regards 1900 as the long-term resistance of gold due to the experience of "strong U.S. dollar = weak gold" during the 2023 Federal Reserve interest rate hike cycle. Even if structural changes such as the central bank's gold purchase, de-dollarization, and negative real interest rates in 2025 have reshaped the pricing logic, it still insists that "a breakthrough of 1900 is not sustainable." The new reality cannot enter the cognitive framework until the old anchor is removed.

How to identify and weaken anchoring effects?

Counterattack anchoring cannot rely on “thinking harder”, but requires the introduction of an external constraint mechanism:

1. Actively question the initial reference value

Ask yourself: "Where does this number come from? Does it apply to the current market structure?" If the source is memory, hearsay, or historical experience, re-verify its validity.

2. Use multi-anchor cross-validation

Don’t rely on a single point of reference. For example, when evaluating the price of a product, consider also:

Price comparison of similar assets (cross-market anchor); cost curve and production capacity data (fundamental anchor); volatility quantile (statistical anchor).

Multiple anchors can dilute the dominance of a single anchor.

3. Use “blind judgment” exercises

Before looking at current prices, independently estimate a reasonable range based on the latest data. Then compare the actual price and observe the direction of deviation. Long-term training reduces reliance on explicit numbers.

Conclusion: Let the price speak, rather than let the memory speak for itself.

The market has no obligation to return to a certain number you have in mind. True objectivity is the recognition that all reference points are temporary and revisable assumptions, not sacrosanct coordinates. Wmax Behavioral Finance Series Reminder: When you find yourself repeatedly saying "it should go back to XX", maybe it's not that the market is wrong, but that your anchor is too heavy.

Only by letting go of your obsession with specific numbers can you hear the true signal sent by the price itself.