Funds Management Under Three Scenarios

1. High-Precision Entry Points

Since an entry point is a precise "point" rather than a broad "area," and it is highly accurate, funds management—when controlling risk—restricts the rare high-return expectations associated with such precision. Therefore, when a high-precision entry point appears, funds management loses its role in risk control. High precision is derived from long-term historical probability statistics, with a probability exceeding 95%.

2. Relatively Precise Entry Points

Relative precision comes from long-term historical probability statistics, with probabilities ranging between 70% and 95%. There are three possibilities: upward, downward, or sideways movement. Thus, when a relatively precise entry point appears, the risk control represented by funds management becomes especially critical. Based on a downward expectation, a scientifically derived allocation—grounded in historical data—minimizes losses from incorrect directional expectations while maximizing gains when the direction is correct. If funds management is ignored and allocations are made randomly, losses from incorrect expectations may amplify unpredictably. For example, going all-in on a wrong long position leads to maximum loss rates, zero recovery ability, and leaves only passive measures like stop-loss or long-term holding.

3. Random Funds Management

This refers to an allocation method detached from probability statistics and unrelated to entry points. Typically, it involves increasing positions when the direction is correct and reducing them when wrong. Since human judgment dominates decisions on position sizing, randomness is heavily influenced by psychological factors, making it difficult to adhere to objective rules consistently. Mistakes can easily lead to negative impacts, affecting future performance. A common approach is dividing funds into three or two equal parts.