phyer/myTestFreqAI
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

全新的策略

Browse Source
This commit is contained in:
zhangkun9038@dingtalk.com 2025-08-30 11:21:02 +08:00
parent 9351d8b6dd
commit 7d5a14d9ec
1 changed files with 64 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

74
freqtrade/templates/freqaiprimer.py
View File

@ -3,13 +3,13 @@ from pandas import DataFrame
import pandas_ta as ta
from freqtrade.exchange import timeframe_to_minutes
class FreqaiPrimer(IStrategy):
class ShortTermMultiTimeframeStrategy(IStrategy):
# 策略参数
minimal_roi = {
"0": 0.04, # 4% ROI（10 分钟内）
"60": 0.02, # 2% ROI（1 小时）
"180": 0.01, # 1% ROI（3 小时）
"360": 0.0 # 0% ROI（6 小时）
"0": 0.04, # 4% ROI (10 分钟内)
"60": 0.02, # 2% ROI (1 小时)
"180": 0.01, # 1% ROI (3 小时)
"360": 0.0 # 0% ROI (6 小时)
}
stoploss = -0.015 # 初始止损 -1.5%
@ -27,6 +27,12 @@ class FreqaiPrimer(IStrategy):
rsi_overbought = 70 # RSI 超买阈值
rsi_oversold = 30 # RSI 超卖阈值
def informative_pairs(self):
# 定义辅助时间框架
pairs = self.dp.current_whitelist()
informative_pairs = [(pair, '15m') for pair in pairs] + [(pair, '1h') for pair in pairs]
return informative_pairs
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# 计算 3m 周期的指标
bb_3m = ta.bbands(dataframe['close'], length=self.bb_length, std=self.bb_std)
@ -46,7 +52,12 @@ class FreqaiPrimer(IStrategy):
df_15m['bb_lower_15m'] = bb_15m[f'BBL_{self.bb_length}_{self.bb_std}']
df_15m['bb_upper_15m'] = bb_15m[f'BBU_{self.bb_length}_{self.bb_std}']
df_15m['rsi_15m'] = ta.rsi(df_15m['close'], length=self.rsi_length)
dataframe = self.merge_informative_pair(dataframe, df_15m, self.timeframe, '15m')
# 手动合并 15m 数据
df_15m = df_15m[['date', 'bb_lower_15m', 'bb_upper_15m', 'rsi_15m']]
df_15m = df_15m.rename(columns={'date': 'date_15m'})
dataframe = dataframe.merge(df_15m, how='left', left_on='date', right_on='date_15m')
dataframe = dataframe.fillna(method='ffill') # 前向填充缺失值
# 获取 1h 数据
df_1h = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe='1h')
@ -54,12 +65,55 @@ class FreqaiPrimer(IStrategy):
df_1h['bb_lower_1h'] = bb_1h[f'BBL_{self.bb_length}_{self.bb_std}']
df_1h['bb_upper_1h'] = bb_1h[f'BBU_{self.bb_length}_{self.bb_std}']
df_1h['rsi_1h'] = ta.rsi(df_1h['close'], length=self.rsi_length)
dataframe = self.merge_informative_pair(dataframe, df_1h, self.timeframe, '1h')
# 手动合并 1h 数据
df_1h = df_1h[['date', 'bb_lower_1h', 'bb_upper_1h', 'rsi_1h']]
df_1h = df_1h.rename(columns={'date': 'date_1h'})
dataframe = dataframe.merge(df_1h, how='left', left_on='date', right_on='date_1h')
dataframe = dataframe.fillna(method='ffill') # 前向填充缺失值
# K线形态：看涨吞没
dataframe['bullish_engulfing'] = (
(dataframe['close'].shift(1) < dataframe['open'].shift(1)) & # 前一根是阴线
(dataframe['close'] > dataframe['open']) & # 当前是阳线
(dataframe['close'] > dataframe['open'].shift(1)) & # 吞没前一根
(dataframe['close'].shift(1) < dataframe['open'].shift(1)) &
(dataframe['close'] > dataframe['open']) &
(dataframe['close'] > dataframe['open'].shift(1)) &
(dataframe['open'] < dataframe['close'].shift(1))
)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# 做多条件
dataframe.loc[
(
(dataframe['close'] <= dataframe['bb_lower_3m']) &
(dataframe['rsi_3m'] < self.rsi_oversold) &
(dataframe['rsi_15m'] < self.rsi_oversold) &
(dataframe['close'] <= dataframe['bb_lower_1h']) &
(dataframe['bullish_engulfing']) &
(dataframe['volume'] > dataframe['volume_ma'])
),
'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# 做多退出
dataframe.loc[
(
(dataframe['close'] >= dataframe['bb_upper_3m']) |
(dataframe['rsi_3m'] > self.rsi_overbought)
),
'exit_long'] = 1
return dataframe
def custom_stoploss(self, pair: str, trade: 'Trade', current_time, current_rate: float,
current_profit: float, **kwargs) -> float:
# 动态止损基于 ATR
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
last_candle = dataframe.iloc[-1]
atr = last_candle['atr']
if atr > 0:
return -1.5 * atr / current_rate # 动态止损为 1.5 倍 ATR
return self.stoploss # 回退到固定止损