{x} | Trading.live

The price distribution on the K-line chart shown in the figure is similar to what we discussed earlier. Traders have to make a decision based on the current price whether to sell for a regression or buy for appreciation.
Research has found that most untrained traders tend to use outcome-oriented strategies when making this decision. As we mentioned earlier, this type of strategy is the least effective and has the highest probability of consecutive losses and consecutive profits. Continuous losses can easily affect a trader's emotions, leading to an increase in position size, a reduction in the trading sample, and ultimately causing a margin call. This is the trilogy of death for novice traders.
Why is there such a high likelihood of consecutive losses when using outcome-oriented strategies? First, let's explain what an outcome-oriented strategy is using the figure shown earlier. The figure is an updated version with more historical data. Traders use this chart to analyze past performance and predict future market trends, often focusing on the outcomes of their previous trades rather than the strategies they used.

When analyzing the price trends on K-line charts between points D and A, traders face the difficult decision of whether to buy or sell at the market price. Simply examining the K-line shape between these points provides some basis for choosing to buy or sell, but traders' minds are conflicted. In such decision-making contexts, traders usually reference more historical data. As shown in the chart, making decisions based only on data from points D to A is difficult, and traders naturally seek to analyze data from before point D, such as from point B to point D.
However, incorporating this segment of the K-line chart from point B to point D can create an illusion of clearer decision-making. The K-line chart itself is like a Rorschach inkblot test, and the more K-line data traders have, the more ideas they project into the market. As our trading coach says, this is being hypnotized by the market!
The so-called result-oriented approach is when traders attempt to summarize significant and effective judgment patterns from analyzing past historical market data. In other words, if the market has been moving with a certain price fluctuation pattern in the previous period, traders can easily extract it from historical data and use it as a reference for current decision-making.
However, this approach can lead to a problem: the more significant the fluctuation pattern, the more likely it is to approach failure. Traders generally prefer to adopt those significant fluctuation patterns from history because they look good in the data, similar to how a very optimistic person might jump from the top floor of the World Trade Center believing they will not die. This result-oriented approach can lead to losses in the world of trading, as illustrated in the chart.

The chart above depicts the daily trading activity of Tencent Holdings. After analyzing historical market and fundamental data from point A to point B, traders believed that the strong trend in the AB wave would continue in the future, leading to a strategy of buying on dips. However, after experiencing four consecutive stop-losses during the actual trading process, the trader began to question their previous trading beliefs. They inferred from the previous stop-loss results that the future market was dangerous (usually due to negative information about the listed company or industry during the dip). As a result, they sold at highs during the subsequent rebound process, as shown by