Files
hummingbot-dashboard/quants_lab/strategy/experiments/macd_bb.py
2023-07-20 21:37:42 +02:00

46 lines
1.8 KiB
Python

import pandas_ta as ta
from pydantic import BaseModel, Field
from quants_lab.strategy.directional_strategy_base import DirectionalStrategyBase
class MACDBBConfig(BaseModel):
exchange: str = Field(default="binance_perpetual")
trading_pair: str = Field(default="ETH-USDT")
interval: str = Field(default="1h")
bb_length: int = Field(default=24, ge=2, le=1000)
bb_std: float = Field(default=2.0, ge=0.5, le=4.0)
bb_long_threshold: float = Field(default=0.0, ge=-3.0, le=0.5)
bb_short_threshold: float = Field(default=1.0, ge=0.5, le=3.0)
fast_macd: int = Field(default=21, ge=2, le=100)
slow_macd: int = Field(default=42, ge=30, le=1000)
signal_macd: int = Field(default=9, ge=2, le=100)
class MacdBollinger(DirectionalStrategyBase[MACDBBConfig]):
def get_raw_data(self):
df = self.get_candles(
exchange=self.config.exchange,
trading_pair=self.config.trading_pair,
interval=self.config.interval,
)
return df
def preprocessing(self, df):
df.ta.bbands(length=self.config.bb_length, std=self.config.bb_std, append=True)
df.ta.macd(fast=self.config.fast_macd, slow=self.config.slow_macd, signal=self.config.signal_macd, append=True)
return df
def predict(self, df):
bbp = df[f"BBP_{self.config.bb_length}_{self.config.bb_std}"]
macdh = df[f"MACDh_{self.config.fast_macd}_{self.config.slow_macd}_{self.config.signal_macd}"]
macd = df[f"MACD_{self.config.fast_macd}_{self.config.slow_macd}_{self.config.signal_macd}"]
long_condition = (bbp < self.config.bb_long_threshold) & (macdh > 0) & (macd < 0)
short_condition = (bbp > self.config.bb_short_threshold) & (macdh < 0) & (macd > 0)
df["side"] = 0
df.loc[long_condition, "side"] = 1
df.loc[short_condition, "side"] = -1
return df