ChatGPT trend sniping strategy sharing

Alright, let's build a strategy framework suitable for your current situation with the following goals:

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### 🎯 **Objective Definition**:

* **Low-Frequency**: Avoid losses from high-frequency fluctuations.
* **Long-Term Trend Capture**: Catch large intraday or multi-day swings.
* **High Risk/Reward Ratio**: Let one win cover multiple losses.
* **Automated Signals**: Reduce human intervention and ensure stable execution.
* **Controllable Drawdown**: Don't aim for frequent profits, but strive for steady gains.

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## 🧠 Strategy Logic Framework (Suggested Name: `Trend Sniper-Alpha`)

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### 1. **Timeframe Basis: 15-minute or 30-minute candlesticks**

Less noise compared to 3-minute candlesticks, better suited for trend signal judgment.

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### 2. **Entry Signal Structure (Trend Breakout Confirmation)**:

**Go long only when the following conditions are met simultaneously (and vice versa for short):**

| Condition No. | Long Signal Condition |
| --- | --- |
| ① | Bollinger Bands width (distance between upper and lower bands) is ≥ 1.5 times the previous day's average (indicating increased volatility) |
| ② | Current closing price is above the upper Bollinger Band by \*1% (to prevent immediate pullback upon touching the band) |
| ③ | MA7 (short-term) crosses above MA25 (mid-term) and the slope is positive |
| ④ | ATR(14) > ATR(14) average → current volatility is stronger than the average of the last 2 weeks |
| ⑤ | Trading volume is at least 1.2 times the average of the past 10 candlesticks |

> ✅ Meeting all 5 indicators simultaneously signifies: breakout + trend confirmation + volume surge, suitable for "trend sniping."

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### 3. **Exit and Risk Management Logic (Fixed + Dynamic Combination)**

| Type | Rule |
| --- | --- |
| Stop Loss | Fixed stop loss ratio of -0.008 to -0.012 (select based on the asset's volatility, a slightly wider range is recommended) |
| Take Profit | Fixed profit target of +0.04 (can be dynamically adjusted to 0.05~0.08 based on testing) |
| Trailing Stop Loss | Once a +0.02 profit is reached, dynamically move the take profit line up to +0.01 to enter a break-even state |
| Time-Based Exit | If the position is held for more than 24 hours without reaching take profit/stop loss, automatically close the position |

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### 4. **Execution Frequency and Position Limits**

| Item | Description |
| --- | --- |
| Entry Frequency | Maximum of 1 entry per day (no chasing), each signal requires re-confirmation |
| Position Sizing | Each position should not exceed 20%-30% of total capital |
| Long/Short Switching | Simultaneous long/short positions are not allowed; do not re-enter a trade before the current one is closed |

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### 5. **Asset/Token Selection Suggestions**

This strategy is more suitable for assets with high volatility but also clear "trend impulses," such as:

* BTC (stable volatility)
* ETH (high elasticity)
* SOL, OP, INJ, DOGE (suitable for long trend capture)

📌 Note: Avoid sideways, low-liquidity assets. Prioritize **assets with a daily volatility greater than ±5%**.

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## 📊 Backtesting Metrics (To be collected for each strategy version):

| Metric | Meaning |
| --- | --- |
| Profit/Loss Ratio (P/L) | Profit per win vs. loss per loss, target > 2.5:1 |
| Win Rate | Successful entry rate, a target of 35%-45% is sufficient |
| Average Holding Time | Closer to 12-24 hours indicates a successful capture of the middle part of the trend |
| Maximum Drawdown | Single strategy drawdown should not exceed -3%, system drawdown should not exceed -10% |
| Monthly Net Worth Growth Rate | >=5% indicates a basis for long-term compound growth |

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## 🧩 Sample Signal Visualization Chart (I can help you create one if you'd like):

* Current candlestick breaks above the upper Bollinger Band + high bandwidth + high ATR;
* MA7 crosses above MA25;
* Volume surge;
→ Screen prompt: "Trend Breakout Signal Confirmed: Can go long."

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## 🧰 Technical Implementation Suggestions:

| Tool or Method | Suggestion |
| --- | --- |
| Backtesting Framework | Python + Pandas + Backtrader / Zipline |
| Visualization | Update daily signal chart + historical net worth chart to show system stability |
| Multi-parameter Running Management | Define multiple versions for take profit/stop loss/ATR parameters, and run batch backtesting to compare and select |
| Live Trading | Start with 1x leverage, a simulated account, or a small amount to gradually verify expectations |

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## ✅ Summary:

| Advantage | Risk Mitigation Strategy |
| --- | --- |
| Low frequency reduces fees + slippage | Only one entry per day, clear entry logic |
| High risk/reward ratio, greater fault tolerance | Control drawdown below 3%, diversify across multiple assets |
| Clear logic, visualization boosts confidence | Strengthen record-keeping and periodic evaluation to avoid short-term pessimism |

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If you agree with this direction, I can help you with the next steps:

1. Output a **complete backtesting framework**.
2. Provide **suggestions for parameter combination optimization**.
3. Generate a **recording template in Excel or table format** to help you track the performance of each strategy.

Which step would you like to start with?

[👉 Trading Signal Monitoring Program and Source Code](https://moer.si/p/113 "Trading Signal Monitoring Program and Source Code")

Authored by moersi. Please keep the original link when sharing: ChatGPT trend sniping strategy sharing
This is not investment advice, and we are not liable for any losses.