最后一次尝试 单币对多交易
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zhangkun9038@dingtalk.com
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1a4560aedc
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f8cb87374f
@ -8,9 +8,9 @@
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"dry_run": false,
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"dry_run_wallet": 7766,
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"timeframe": "1h",
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"position_adjustment_enable": true,
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"position_adjustment_enable": false,
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"process_only_new_candles": false,
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"max_entry_position_adjustment": -1,
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"max_entry_position_adjustment": 0,
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"exchange": {
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"name": "okx",
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"key": "cbda9fde-b9e3-4a2d-94f9-e5c3705dfb5c",
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@ -1,7 +1,7 @@
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# /freqtrade/user_data/strategies/StaticGrid.py
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from freqtrade.strategy import IStrategy
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from freqtrade.strategy import IStrategy, merge_informative_pair
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from pandas import DataFrame
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from typing import Optional
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from typing import Optional, Dict, Any
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import logging
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import sys
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@ -11,39 +11,34 @@ class StaticGrid(IStrategy):
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INTERFACE_VERSION = 3
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timeframe = '1h'
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can_short = False
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minimal_roi = {"0": 100}
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minimal_roi = {"0": 0.001} # 极小收益就卖
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stoploss = -0.99
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use_exit_signal = True
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position_adjustment_enable = True
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max_entry_position_adjustment = -1
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position_adjustment_enable = False # 关闭加仓
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cooldown_candles = 0
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# Lock configuration - disable lockout to allow immediate re-entry
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cooldown_candles = 0 # No cooldown between trades
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# Grid parameters
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LOWER = 1500.0 # Minimum price
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UPPER = 4500.0 # Maximum price
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STEP = 50.0 # Grid spacing
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STAKE = 40.0 # Per-trade stake
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LOWER = 1500.0
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UPPER = 4500.0
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STEP = 50.0
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STAKE = 40.0
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def __init__(self, config: dict) -> None:
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super().__init__(config)
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# Force write to stderr immediately on startup
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print("[StaticGrid] Strategy initialized!", file=sys.stderr, flush=True)
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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print(f"[StaticGrid] populate_indicators called, df len: {len(dataframe)}", file=sys.stderr, flush=True)
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return dataframe
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Static Grid Entry Logic using multiple enter_tags:
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- Each grid level gets its own enter_tag (entry_grid_XXXX)
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- This allows Freqtrade to create multiple orders per candle
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- Buy at predefined grid levels: 1500, 1550, 1600, ..., 4500 (step 50)
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激进网格入场：
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- 当价格低于任何网格点时，强制产生买入信号
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- 使用 enter_tag 来区分不同网格点
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"""
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dataframe['enter_long'] = False
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dataframe['enter_tag'] = ""
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dataframe['enter_tag'] = ''
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if len(dataframe) == 0:
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return dataframe
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@ -52,61 +47,43 @@ class StaticGrid(IStrategy):
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current_low = dataframe['low'].iloc[-1]
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print(f"[StaticGrid] Current price: {current_price:.2f}, low: {current_low:.2f}", file=sys.stderr, flush=True)
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# Define static grid levels
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LOWER = 1500.0
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UPPER = 4500.0
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STEP = 50.0
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# Generate all grid levels in the range
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grid_levels = [LOWER + i * STEP for i in range(int((UPPER - LOWER) / STEP) + 1)]
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# IMPORTANT: Add current price as a grid level too (rounded to nearest STEP)
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current_grid_level = round(current_price / STEP) * STEP
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if current_grid_level not in grid_levels and LOWER <= current_grid_level <= UPPER:
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grid_levels.append(current_grid_level)
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grid_levels.sort()
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# 生成所有网格点
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grid_levels = [self.LOWER + i * self.STEP for i in range(int((self.UPPER - self.LOWER) / self.STEP) + 1)]
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entry_count = 0
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grid_tags = [] # Collect all grid levels that should trigger entry
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# For each grid level, check if price is at or below it
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# 对每个网格点检查是否应该入场
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for grid_price in grid_levels:
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# Buy if current low is at or below this grid level (with 0.5% tolerance)
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if current_low <= grid_price * 1.005:
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entry_count += 1
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# 激进条件：价格低于网格点就买
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if current_low <= grid_price:
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dataframe.loc[dataframe.index[-1], 'enter_long'] = True
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tag = f"grid_{int(grid_price)}"
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grid_tags.append(tag)
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if entry_count <= 5: # Only print first 5 for brevity
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# 累加所有适用的标签
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if dataframe.loc[dataframe.index[-1], 'enter_tag']:
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dataframe.loc[dataframe.index[-1], 'enter_tag'] += f",{tag}"
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else:
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dataframe.loc[dataframe.index[-1], 'enter_tag'] = tag
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entry_count += 1
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if entry_count <= 5:
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print(f"[StaticGrid] Entry at grid {grid_price:.0f}", file=sys.stderr, flush=True)
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if entry_count > 5:
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print(f"[StaticGrid] ... and {entry_count - 5} more grid levels", file=sys.stderr, flush=True)
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print(f"[StaticGrid] Total entry signals: {entry_count}", file=sys.stderr, flush=True)
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# Set enter_long = True for the last row (current candle)
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if entry_count > 0:
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dataframe.loc[dataframe.index[-1], 'enter_long'] = True
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# Use the grid tags separated by comma
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dataframe.loc[dataframe.index[-1], 'enter_tag'] = ','.join(grid_tags)
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return dataframe
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def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Exit Logic - AGGRESSIVE:
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- Exit as soon as price moves up at all (even 0.01% profit)
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- This ensures we close positions quickly for grid trading
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极端出场：任何上升就卖
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"""
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dataframe['exit_long'] = False
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if len(dataframe) < 2:
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return dataframe
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# EXTREME: Exit on ANY upward movement (even micro profits)
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# This forces position closure to allow new entries
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dataframe['exit_long'] = (dataframe['close'] > dataframe['open']).fillna(False)
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# 只要收盘价高于开盘价就卖出
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dataframe['exit_long'] = (dataframe['close'] > dataframe['open'])
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exits = dataframe['exit_long'].sum()
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if exits > 0:
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@ -118,26 +95,6 @@ class StaticGrid(IStrategy):
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current_profit: float, min_stake: float,
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max_stake: float, **kwargs) -> Optional[float]:
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"""
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Network Grid Position Adjustment (DCA - Dollar Cost Averaging):
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每当价格跌到新的网格点时，自动加仓
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不使用加仓
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"""
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LOWER = 1500.0
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UPPER = 4500.0
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STEP = 50.0
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# Only add position if price drops to a new grid level
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grid_level = round(current_rate / STEP) * STEP
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# Calculate how many positions we've already opened
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open_positions = trade.nr_of_successful_entries
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# Maximum positions per pair = (UPPER - LOWER) / STEP
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max_positions = int((UPPER - LOWER) / STEP) + 1
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if open_positions < max_positions and LOWER <= grid_level <= UPPER:
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# Add position at each grid level
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print(f"[StaticGrid] Adding position at grid level {grid_level:.0f}, current rate {current_rate:.2f}",
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file=sys.stderr, flush=True)
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return self.STAKE
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return None
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