Strategy 3: MomentumDaily RSI momentum + EMA200 confirmation + BTC regime filter. Enters when RSI crosses above 50 in macro uptrend.
Timeframe
1d
Direction
Long Only
Stoploss
-5.0%
Trailing Stop
No
ROI
0m: 0.0%, 1440m: 4.0%, 2880m: 2.0%, 4320m: 1.0%
Interface Version
3
Startup Candles
250
Indicators
4
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
from freqtrade.strategy import IStrategy, DecimalParameter, IntParameter
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
class MomentumDaily(IStrategy):
"""
Strategy 3: MomentumDaily
RSI momentum + EMA200 confirmation + BTC regime filter.
Enters when RSI crosses above 50 in macro uptrend.
"""
INTERFACE_VERSION = 3
minimal_roi = {
"0": 0.08,
"1440": 0.04,
"2880": 0.02,
"4320": 0.01,
"0": 0
}
stoploss = -0.05
can_short = False
timeframe = '1d'
startup_candle_count = 250
trailing_stop = False
use_custom_stoploss = False
rsi_entry = IntParameter(40, 60, default=50, space="buy")
rsi_exit = IntParameter(40, 70, default=50, space="sell")
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['ema200'] = ta.EMA(dataframe['close'], timeperiod=200)
dataframe['ema200_slope'] = dataframe['ema200'].diff(5)
# RSI
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
# MACD for momentum confirmation
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macd_signal'] = macd['macdsignal']
dataframe['macd_hist'] = macd['macdhist']
# Volume check
dataframe['volume_sma20'] = ta.SMA(dataframe['volume'], timeperiod=20)
dataframe['volume_ok'] = dataframe['volume'] > dataframe['volume_sma20'] * 0.3
# BTC regime filter
try:
btc_df = self.dp.get_pair_dataframe("BTC/USDT:USDT", "1d")
btc_df['btc_ema200'] = ta.EMA(btc_df['close'], timeperiod=200)
dataframe['btc_ema200'] = btc_df['btc_ema200'].reindex(dataframe.index, method='ffill')
dataframe['btc_close'] = btc_df['close'].reindex(dataframe.index, method='ffill')
except Exception:
dataframe['btc_ema200'] = 0
dataframe['btc_close'] = 999999
dataframe['macro_uptrend'] = dataframe['btc_close'] > dataframe['btc_ema200']
# Momentum entry: RSI crossing above 50 with MACD confirmation
dataframe['momentum_entry'] = (
(dataframe['rsi'] > self.rsi_entry.value) &
(dataframe['rsi'].shift(1) <= self.rsi_entry.value) &
(dataframe['macd'] > dataframe['macd_signal']) &
(dataframe['close'] > dataframe['ema200']) &
(dataframe['ema200_slope'] > 0)
)
# Exit: RSI dropping below exit threshold, loss of momentum
dataframe['momentum_exit'] = (
(dataframe['rsi'] < self.rsi_exit.value) &
(dataframe['macd'] < dataframe['macd_signal'])
)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['momentum_entry']) &
(dataframe['macro_uptrend']) &
(dataframe['volume_ok']) &
(dataframe['volume'] > 0)
),
['enter_long', 'enter_tag']
] = (1, 'momentum_daily_long')
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['momentum_exit']) |
(~dataframe['macro_uptrend'])
),
['exit_long', 'exit_tag']
] = (1, 'momentum_daily_exit')
return dataframe