Timeframe
5m
Direction
Long Only
Stoploss
-10.0%
Trailing Stop
No
ROI
0m: 10.0%, 60m: 5.0%, 120m: 2.0%
Interface Version
3
Startup Candles
N/A
Indicators
3
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
"""
MACD Cross Strategy
A strategy based on MACD (Moving Average Convergence Divergence) indicator.
Entry: When MACD line crosses above signal line
Exit: When MACD line crosses below signal line or profit target reached
"""
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
import numpy as np
import pandas as pd
from pandas import DataFrame
from typing import Optional
import talib.abstract as ta
from freqtrade.strategy import IStrategy
class MACDCrossStrategy(IStrategy):
"""
MACD Cross Strategy
Uses MACD indicator for entry/exit signals.
"""
INTERFACE_VERSION = 3
timeframe = '5m'
can_short: bool = False
# ROI table
minimal_roi = {
"0": 0.10, # 10% profit target
"60": 0.05, # 5% after 60 minutes
"120": 0.02 # 2% after 120 minutes
}
stoploss = -0.10 # 10% stop loss
trailing_stop = False
process_only_new_candles = False
use_exit_signal = True
exit_profit_only = False
ignore_roi_if_entry_signal = False
startup_candle_count: int = 200
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Add indicators to the dataframe.
Args:
dataframe: DataFrame with OHLCV data
metadata: Pair metadata
Returns:
DataFrame with indicators added
"""
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
# RSI for confirmation
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
# Volume SMA for volume confirmation
dataframe['volume_sma'] = ta.SMA(dataframe['volume'], timeperiod=20)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Populate entry signals.
Entry when:
- MACD crosses above signal line
- MACD histogram is positive
- RSI is not overbought (< 70)
"""
dataframe.loc[
(
(dataframe['macd'] > dataframe['macdsignal']) &
(dataframe['macd'].shift(1) <= dataframe['macdsignal'].shift(1)) &
(dataframe['macdhist'] > 0) &
(dataframe['rsi'] < 70) &
(dataframe['volume'] > dataframe['volume_sma'] * 0.8)
),
'enter_long'
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Populate exit signals.
Exit when:
- MACD crosses below signal line
- MACD histogram turns negative
"""
dataframe.loc[
(
(dataframe['macd'] < dataframe['macdsignal']) &
(dataframe['macd'].shift(1) >= dataframe['macdsignal'].shift(1))
) |
(
(dataframe['macdhist'] < 0) &
(dataframe['macdhist'].shift(1) >= 0)
),
'exit_long'
] = 1
return dataframe