Bear bear-Alpha "Boll" V2.31 For SOL

VX : louiscoin tg : @opsave

Simple strategies create more than simple success stories

FMZ is surrounded by bybit +35%=bearwin-sol Bybit is real Details on the real disk parameters

Let's start with the price.No bargain, not cheapI'm going to buy more that day and send it to my friends.

• 30 days of the month of January
• 365 days a year, one delivery per 1000 u

I've been thinking about this for a long time. Analyze this policy Bear bear-alpha Here, I'm greatly reducing the risk of Martingale exploding.

What I'm talking about is the entry-level model.

Why did you enter? How did I think about building this strategy?

And it's because of the continuous decline in survival rates after the test. This is a game, even though it is a game. If you survive, you will receive a large sum of money. If you do not, you will be returned to nothingness.

Martin he is a double betting strategy So I'm in a situation where I have to be, and I have to be. So I'm going to change his terms! I started with the idea that

One, it's better to bet when you've had a series of failures. It's slowing down the N-word decline.

2, add the reversal signal/average return/break Brin is the main modifier.

Limit the number of purchases to 6-8 units(In fact, it's a lottery entry if you add this condition.)Hemp controls the share of capital

So we need to find the uptrend that's going up. And if you want to keep the market share in line, you're going to see a smaller decline than the decline of the coin. For example, BTC fell 20 percent, and the base of the coin fell 50 percent.

If you don't have a good sense of timing, It's easy to blow your cover. It's like the bottom of a circle, and this is the risk factor that makes the regular martin easy to eat.

The strategy described:

1.	布林帶原理：布林帶（Bollinger Bands）是一種基於價格的波動率指標，透過計算價格的移動平均線（Moving Average, MA）和標準差（Standard Deviation, σ），形成上軌和下軌帶，反映市場波動範圍。
•	上軌： \[ B_{\text{upper}} = MA + k \times \sigma \] 
•	下軌： \[ B_{\text{lower}} = MA - k \times \sigma  \]
•	其中  MA  是移動平均線， \sigma  是標準差， k  是調整係數（通常設定為2）。

2.	均值回歸策略：你的策略基於價格有回歸到均值的假設，當價格偏離均值達到一定程度時，會回到其均值。當價格突破布林帶的上軌或下軌時，根據均值回歸進行反向操作。
•	若價格突破上軌（超買），進行空單操作，預期價格回到均值。
•	若價格跌破下軌（超賣），進行多單操作，預期價格回到均值。

3.	加倉策略（馬丁格爾）：你所採用的馬丁格爾加倉策略是有限次數（8倉），並且每次加倉都伴隨價格進一步偏離均值，倉位大小隨著價格偏離而加倍。
•	加倉次數設定為最多8次，避免無限加倉導致爆倉風險。
•	每次加倉比例為  P_n = P_{n-1} \times 2  （加倍原則），其中  P_n  表示第  n  次加倉的倉位大小。

4.	保證金管理：你建議將保證金控制在 30% 左右，以降低風險，這意味著你的槓桿和倉位會根據資金情況進行動態調整。
•	風險控制公式：假設最大虧損為  L ，槓桿為  Leverage ，初始倉位為  P_0 ，則總風險：

[ R_{\text{total}} = P_0 \times Leverage \times (1 + \text{+{+}}) ] The value of the leverage is given by ] • To ensure that the risk is within control, you will adjust the size of the initial deposit based on the total funds in your account.

5.	風險控制與回測結果：該策略在歷史數據測試中表現穩定，並且在非極端市場情況下（如連續暴跌）有較好的表現。當保證金越高、槓桿越低時，策略的爆倉風險隨之降低。
•	該策略也使用收盤價模型防止過擬合回測讓數據更貼近實盤

BTCUSDT retested resultsResults for the SOLUSDT