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去掉没用的代码包括custom_exit和其中roi逻辑

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zhangkun9038@dingtalk.com 2025-10-15 18:35:56 +00:00
parent b368bd88d4
commit 9d8177afcb
1 changed files with 0 additions and 51 deletions
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freqtrade/templates/freqaiprimer.py
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@ -108,10 +108,6 @@ class FreqaiPrimer(IStrategy):
stake_divisor = DecimalParameter(2, 4, decimals=3, default=2.867, optimize=True, load=True, space='buy') # 加仓金额分母
step_coefficient = DecimalParameter(0.5, 1.5, decimals=2, default=0.92, optimize=True, load=True, space='buy') # 加仓金额分母
# 线性ROI参数 - 用于线性函数: y = (a * (x + k)) + t
roi_param_a = DecimalParameter(-0.0002, -0.00005, decimals=5, default=-0.0001, optimize=True, load=True, space='sell') # 系数a
roi_param_k = IntParameter(20, 150, default=50, optimize=True, load=True, space='sell') # 偏移量k
roi_param_t = DecimalParameter(0.02, 0.18, decimals=3, default=0.06, optimize=True, load=True, space='sell') # 常数项t
# 出场条件阈值参数
exit_bb_upper_deviation = DecimalParameter(0.98, 1.02, decimals=2, default=1.0, optimize=True, load=True, space='sell')
exit_volume_multiplier = DecimalParameter(1.5, 3.0, decimals=1, default=2.0, optimize=True, load=True, space='sell')
@ -563,53 +559,6 @@ class FreqaiPrimer(IStrategy):
return -1.2 * atr / current_rate # 基础1.2倍ATR止损
return self.stoploss
def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
current_profit: float, **kwargs) -> float:
if trade.is_short:
return 0.0
trade_age_minutes = (current_time - trade.open_date_utc).total_seconds() / 60
if trade_age_minutes < 0:
trade_age_minutes = 0
# 使用可优化的线性函数: y = (a * (x + k)) + t
a = self.roi_param_a.value # 系数a (可优化参数)
k = self.roi_param_k.value # 偏移量k (可优化参数)
t = self.roi_param_t.value # 常数项t (可优化参数)
dynamic_roi_threshold = (a * (trade_age_minutes + k)) + t
# 确保ROI阈值不小于0
if dynamic_roi_threshold < 0:
dynamic_roi_threshold = 0.0
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
current_state = dataframe['market_state'].iloc[-1] if 'market_state' in dataframe.columns else (
'strong_bull' if dataframe['sma'].diff().iloc[-1] > 0.01 else 'weak_bull' if dataframe['sma'].diff().iloc[-1] > 0 else 'neutral'
)
entry_tag = trade.enter_tag if hasattr(trade, 'enter_tag') else None
profit_ratio = current_profit / dynamic_roi_threshold if dynamic_roi_threshold > 0 else 0
exit_ratio = 0.0
if profit_ratio >= 1.0:
if current_state == 'strong_bull':
exit_ratio = 0.5 if profit_ratio < 1.5 else 0.8
elif current_state == 'weak_bull':
exit_ratio = 0.6 if profit_ratio < 1.2 else 0.9
else:
exit_ratio = 1.0
if entry_tag == 'strong_trend':
exit_ratio *= 0.8
if dynamic_roi_threshold < 0:
exit_ratio = 1.0
#logger.info(f"[{pair}] 动态止盈: 持仓时间={trade_age_minutes:.1f}分钟, 当前利润={current_profit:.2%}, "
# f"动态ROI阈值={dynamic_roi_threshold:.4f}, 利润比值={profit_ratio:.2f}, "
# f"市场状态={current_state}, entry_tag={entry_tag}, 退出比例={exit_ratio:.0%}")
return exit_ratio
def adjust_trade_position(self, trade: 'Trade', current_time, current_rate: float,
current_profit: float, min_stake: float, max_stake: float, **kwargs) -> float: