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添加均线策略

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jackyu66git
2026-02-11 19:31:28 +08:00
parent 10b8ba398b
commit 13c226ee6c
2 changed files with 283 additions and 0 deletions
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config/ChanLun_EMA_Align.json
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{
"$schema": "https://schema.freqtrade.io/schema.json",
"max_open_trades": 1,
"stake_currency": "USDT",
"stake_amount": "unlimited",
"tradable_balance_ratio": 0.99,
"fiat_display_currency": "USD",
"dry_run": true,
"db_url": "sqlite:///tradesv3.chanlun_btc_15.sqlite",
"dry_run_wallet": 1000,
"cancel_open_orders_on_exit": true,
"trading_mode": "futures",
"margin_mode": "isolated",
"can_short" : true,
"timeframe" : "1m",
"process_only_new_candles" : false,
"unfilledtimeout": {
"entry": 1,
"exit": 1,
"exit_timeout_count": 5,
"unit": "minutes"
},
"entry_pricing": {
"price_side": "same",
"use_order_book": true,
"order_book_top": 1,
"price_last_balance": 0.0,
"check_depth_of_market": {
"enabled": false,
"bids_to_ask_delta": 1
}
},
"exit_pricing":{
"price_side": "same",
"use_order_book": true,
"order_book_top": 1
},
"exchange": {
"name": "binance",
"key": "hvoXanRExQvcN4tyGFvEnsSF4gqxXp6ZJnBu5lnhvlVuHaDbj2PhLBQGCLkkyeI8",
"secret": "3UKA2oyDj7OoXrausmnaLwLlNfXmlNf2imBdmQqqKHArcJfk6X9xjaUF19wzu82l",
"ccxt_config": {},
"ccxt_async_config": {},
"pair_whitelist": [
"BTC/USDT:USDT"
],
"pair_blacklist": [
"BNB/.*"
]
},
"pairlists": [
{
"method": "StaticPairList",
"number_assets": 1,
"sort_key": "quoteVolume",
"min_value": 0,
"refresh_period": 1800
}
],
"telegram": {
"enabled": true,
"token": "7677670958:AAFL_jgZvNUTPR3R3vWieREX_tDVi9w2C1Y",
"chat_id": "580807463"
},
"api_server": {
"enabled": true,
"listen_ip_address": "0.0.0.0",
"listen_port": 8820,
"verbosity": "error",
"enable_openapi": false,
"jwt_secret_key": "14d3510740e2c39a973a8895f1aa2704d98d08b86170260085709fa5ea48251d",
"ws_token": "dtKKDnafBrX4icq_ZCw7acJTahTK4h_yvg",
"CORS_origins": [],
"username": "freqtrader",
"password": "FreqTrade007"
},
"bot_name": "freqtrade",
"initial_state": "running",
"force_entry_enable": false,
"internals": {
"process_throttle_secs": 2
}
}
strategies/ChanLun_EMA_Align.py
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# --- Do not remove these libs ---
from statistics import median
from freqtrade.strategy import IStrategy, stoploss_from_absolute
import sys
import os
# 添加父目录到系统路径
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from ChanLun import ChanLun
from ChanEnum import Chan_FX_TYPE, Chan_KLC_FX, Chan_BI_DIR, Chan_KLC_FX
# --------------------------------
from technical.util import resample_to_interval, resampled_merge
import talib.abstract as ta
from pandas import DataFrame
import pandas as pd
from datetime import datetime, timedelta
from freqtrade.persistence import Trade, Order
from typing import Optional
import logging
logger = logging.getLogger(__name__)
"""
大周期：1h
小周期：15m，30m
大周期EMA156以下找做空机会
找到最近的中枢，中枢下跌以后穿过EMA156，EMA52均线，形成死叉，macd黄白线穿越0轴
EMA24，EMA52，EMA104，EMA156成下跌趋势依次排列（EMA156 > EMA104 > EMA52 > EMA24）
做空
1. 做空开始点位条件：
确定下跌周期，价格在大于大周期的时间周期找到MACD归零轴+EMA52阻力线，按照K线动能理论，小周期确认是否背驰，背驰则开仓并且MACD穿零轴
止损放到最近的顶分型高点或者价格突破EMA156
2. 开始点位止盈策略
计算盈亏比方式：至少1:2，到达1:2后平仓一半，移动止损到开仓价，1:3再平仓剩下的一半仓位，依次类推
如果大周期遇到底背离可以平完所有仓位
3. 加仓点位
小周期顶分型+价格接近或突破大周期EMA24但是不突破EMA52后下跌可以加仓到最大仓位+大周期黄白线归零轴/小周期顶分型+小周期EMA52归零轴
大周期顶分型+大周期macd归零轴可以加仓到最大仓位
大周期顶分型或顶分型后，macd穿零轴后价格和macd红绿柱背驰可以加仓到最大仓位
小周期顶分型+大周期macd归零轴
"""
### Now you can use logger.info('asfd') to log
# freqtrade plot-dataframe --strategy ChanLun_BTC --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_30.json --timerange=20250309-
# freqtrade trade -c ./user_data/Chan/config/ChanLun_EMA_Align.json --strategy ChanLun_EMA_Align --strategy-path ./user_data/Chan/strategies
# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_EMA_Align.json --strategy ChanLun_EMA_Align --strategy-path ./user_data/Chan/strategies --timerange=20260101-
# freqtrade download-data -c ./user_data/Chan/config/ChanLun_EMA_Align.json -t 1m 1m 1h 1d 1w 1M --pairs BTC/USDT:USDT --timerange=20240101-
# freqtrade download-data -c ./user_data/Chan/config/ChanLun_EMA_Align.json -t 1m 1h 1d 1M --pairs BTC/USDT --timerange=20170101-
# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi --strategy ChanLun_EMA_Align --strategy-path ./user_data/Chan/strategies -c ./user_data/Chan/config/ChanLun_EMA_Align.json -e 200 --timerange=20250201-20250901
# freqtrade edge -c ./user_data/Chan/config/ChanLun_EMA_Align.json --strategy ChanLun_EMA_Align --strategy-path ./user_data/Chan/strategies --timerange 20250721-20250901
# freqtrade plot-dataframe -c ./user_data/Chan/config/ChanLun_EMA_Align.json --strategy ChanLun_EMA_Align --strategy-path ./user_data/Chan/strategies --timerange 20250721-20250901
# sudo docker compose run --rm chanlun_btc backtesting -c ./user_data/Chan/config/ChanLun_EMA_Align.json --strategy ChanLun_EMA_Align --strategy-path ./user_data/Chan/strategies --timerange=20250721-
# sudo docker compose run --rm chanlun_btc download-data -c ./user_data/Chan/config/ChanLun_EMA_Align.json --pairs BTC/USDT:USDT -t 1m --timerange 20240101-
# sudo docker compose run --rm chanlun_btc trade -c ./user_data/Chan/config/ChanLun_EMA_Align.json --strategy ChanLun_EMA_Align --strategy-path ./user_data/Chan/strategies
class ChanLun_EMA_Align(IStrategy):
INTERFACE_VERSION: int = 3
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
# 30m and 1h
minimal_roi = {
"0": 0.15,
"360": 0.2,
"640": 0.1,
"1200": 0
}
# 5m and 15m
minimal_roi_1 = {
"0": 0.1,
"60": 0.05,
"120": 0.02,
"240": 0
}
# 15m and 30m
minimal_roi_1 = {
"0": 0.1,
"240": 0.05,
"480": 0.03,
"600": 0
}
minimal_roi_1 = {
"0": 1.50,
"120": 0.05,
"240": 0.025,
"360": 0
}
can_short = True
lev = 1.0
stoploss = -0.3 # 设置为很大的负值，让custom_stoploss来控制
use_custom_stoploss = False # 启用自定义止损
trailing_stop = False
trailing_stop_positive = 0.03
trailing_stop_positive_offset = 0.06
trailing_only_offset_is_reached = False
# 关闭分批止盈/仓位调整
position_adjustment_enable = False
# startup_candle_count = 1600
time5 = 15
time15 = 15
time30 = 30
time60 = 60
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe = self.add_indicators(dataframe)
dataframe_5m = resample_to_interval(dataframe, self.get_ticker_indicator() * self.time5)
dataframe_5m = self.add_indicators(dataframe_5m)
dataframe = resampled_merge(dataframe, dataframe_5m)
return dataframe
def add_indicators(self, dataframe):
dataframe['ema24'] = ta.EMA(dataframe, timeperiod=24)
dataframe['dir24'] = dataframe['close'] - dataframe['ema24']
dataframe['ema52'] = ta.EMA(dataframe, timeperiod=52)
dataframe['dir52'] = dataframe['close'] - dataframe['ema52']
dataframe['ema104'] = ta.EMA(dataframe, timeperiod=104)
dataframe['dir104'] = dataframe['close'] - dataframe['ema104']
dataframe['ema156'] = ta.EMA(dataframe, timeperiod=156)
dataframe['dir156'] = dataframe['close'] - dataframe['ema156']
dataframe['dir52_156'] = dataframe['dir52'] - dataframe['dir156']
dataframe['dir52_104'] = dataframe['dir52'] - dataframe['dir104']
dataframe_macd = ta.MACD(dataframe, fast=12, slow=26, signal=9)
dataframe['macdsignal'] = dataframe_macd['macdsignal']
dataframe['macd'] = dataframe_macd['macd']
dataframe['macdhist'] = dataframe_macd['macdhist']
dataframe['ema_align'] = (
((dataframe['ema24'] > dataframe['ema52']) & (dataframe['ema52'] > dataframe['ema104'])) |
((dataframe['ema24'] < dataframe['ema52']) & (dataframe['ema52'] < dataframe['ema104']))
)
return dataframe
def custom_entry_price(self, pair: str, trade: Trade | None, current_time: datetime, proposed_rate: float,
entry_tag: str | None, side: str, **kwargs) -> float:
new_entryprice = proposed_rate
if trade:
if trade.is_short:
new_entryprice = proposed_rate - 50
else:
new_entryprice = proposed_rate + 50
return new_entryprice
def custom_exit_price(self, pair: str, trade: Trade,
current_time: datetime, proposed_rate: float,
current_profit: float, exit_tag: str | None, **kwargs) -> float:
new_exitprice = proposed_rate
if trade:
if trade.is_short:
new_exitprice = proposed_rate + 50
else:
new_exitprice = proposed_rate - 50
return new_exitprice
def adjust_trade_position(self, trade: Trade, current_time: datetime,
current_rate: float, current_profit: float,
min_stake: Optional[float], max_stake: float,
current_entry_rate: float, current_exit_rate: float,
current_entry_profit: float, current_exit_profit: float,
**kwargs) -> Optional[float]:
# 关闭分批止盈，始终不调整仓位
return None
def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
current_profit: float, **kwargs):
# 不做分批止盈/最终止盈处理，退出由策略信号/ROI/止损决定
return None
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
resample_5m_align = 'resample_{}_ema_align'.format(self.get_ticker_indicator() * self.time5)
# 使用高周期的 dir52_156 方向作为多空判定依据
resample_5m_dir = 'resample_{}_dir52_104'.format(self.get_ticker_indicator() * self.time5)
resample_5m_signal = 'resample_{}_macdsignal'.format(self.get_ticker_indicator() * self.time5)
dataframe.loc[
(dataframe[resample_5m_align]) &
(dataframe[resample_5m_dir] < 0) &
(dataframe[resample_5m_signal] > 0),
['enter_long', 'enter_tag']] = (1, 'long_signal_chan')
dataframe.loc[
(dataframe[resample_5m_align]) &
(dataframe[resample_5m_dir] > 0) &
(dataframe[resample_5m_signal] < 0),
['enter_short', 'enter_tag']] = (1, 'short_signal_chan')
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe['dir156'] < 0) &
(dataframe['dir52_156'] < 0) &
(dataframe['macdhist'] < 0),
['exit_long', 'exit_tag']] = (1, 'long_exit_signal_chan')
dataframe.loc[
(dataframe['macd'] > 0) &
(dataframe['dir156'] > 0) &
(dataframe['dir52_156'] > 0) &
(dataframe['macdhist'] > 0),
['exit_short', 'exit_tag']] = (1, 'short_exit_signal_chan')
return dataframe
def leverage(self, pair: str, current_time: datetime, current_rate: float,
proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str,
**kwargs) -> float:
return self.lev
def get_ticker_indicator(self):
return int(self.timeframe[:-1])