OPEN-SOURCE SCRIPT
[blackcat] L1 Buy Back
已更新
Level 1
Background
This indicator models the situation before big money or whales lurking, buying chips, and about to pull up.
Function
When is the time to buy, even if you know that whales are accumulating, but how long it needs to be lurking, and when it will rise is unknown. This indicator has been conditionally modeled through statistical high probability events, and the main judgment is that it is the key to step back before rising The bit, once the signal appears, will be pulled up.
This includes: using a moving average of custom parameters (the parameters of this key moving average need to be found through backtesting for different markets and trading varieties) as the basis for the main characterization of large-capacity trading behavior. Then build a model through the volume-price relationship:
1. There is a feature that the lowest price is lower than the moving average after the downward pressure of large funds.
2. The closing price must effectively stand above the moving average.
3. The ratio of closing prices for two consecutive days is less than the moving average value.
4. The moving average is just above the heavy volume, and the volume ratio meets certain requirements, indicating that it is a feature of heavy volume. (Amplified volume is an important manifestation of banker fund action)
Remarks
Feedbacks are appreciated.
Background
This indicator models the situation before big money or whales lurking, buying chips, and about to pull up.
Function
When is the time to buy, even if you know that whales are accumulating, but how long it needs to be lurking, and when it will rise is unknown. This indicator has been conditionally modeled through statistical high probability events, and the main judgment is that it is the key to step back before rising The bit, once the signal appears, will be pulled up.
This includes: using a moving average of custom parameters (the parameters of this key moving average need to be found through backtesting for different markets and trading varieties) as the basis for the main characterization of large-capacity trading behavior. Then build a model through the volume-price relationship:
1. There is a feature that the lowest price is lower than the moving average after the downward pressure of large funds.
2. The closing price must effectively stand above the moving average.
3. The ratio of closing prices for two consecutive days is less than the moving average value.
4. The moving average is just above the heavy volume, and the volume ratio meets certain requirements, indicating that it is a feature of heavy volume. (Amplified volume is an important manifestation of banker fund action)
Remarks
Feedbacks are appreciated.
版本注释
Add the missing selling points开源脚本
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