Add new strategy files

2025-05-26 11:59:46 +08:00
parent 3f16a5e6ce
commit 0cc19132eb
12 changed files with 287 additions and 0 deletions
@@ -0,0 +1,83 @@
+{
+    "$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": false,
+    "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": false,
+        "listen_ip_address": "127.0.0.1",
+        "listen_port": 8811,
+        "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
+    }
+}
@@ -0,0 +1,204 @@
+# --- Do not remove these libs ---
+from statistics import median
+from freqtrade.strategy import IStrategy
+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 ChanLun_Classifier import ChanLunClassifier
+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
+from datetime import datetime, timedelta
+from freqtrade.persistence import Trade
+from typing import Optional
+import logging
+logger = logging.getLogger(__name__)
+### Now you can use logger.info('asfd') to log
+# freqtrade plot-dataframe --strategy ChanLun_BTC_15 --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_15.json --timerange=20250309-
+
+# freqtrade trade -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies
+# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies --timerange=20250416-
+# freqtrade download-data -c ./user_data/Chan/config/ChanLun_BTC_15.json -t 1m --pairs BTC/USDT:USDT --timerange=20250405-
+# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi stoploss --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies -c ./user_data/Chan/config/ChanLun_BTC_15.json -e 200 --timerange=20250201-20250401
+
+# sudo docker compose run --rm chan_btc backtesting -c ./user_data/Chan/config/ChanLun_SOL.json --strategy ChanLun_SOL --strategy-path ./user_data/Chan/strategies --timerange=20250101-
+# sudo docker compose run --rm chan_btc download-data -c ./user_data/Chan/config/ChanLun_BTC_15.json --pairs BTC/USDT:USDT -t 1m --timerange 20240101-
+# sudo docker compose run --rm chan_btc trade -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies
+
+class ChanLun_BTC_15(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": 0.30,
+		"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_2 = {
+		"0": 0.10,
+		"1200": 0.05,
+		"2400": 0.025,
+		"3600": 0
+	}
+	can_short = True
+	lev = 20.0
+	stoploss = -0.3
+	trailing_stop = False
+	trailing_stop_positive = 0.025
+	trailing_stop_positive_offset = 0.045
+	trailing_only_offset_is_reached = False
+
+	position_adjustment_enable = True
+	startup_candle_count = 600
+
+	time5 = 5
+	time15 = 15
+	time30 = 30
+	time60 = 60
+	time4h = 240
+	time5 = 15
+	last_time = datetime.now()
+	chan = ChanLun()
+	classifier = ChanLunClassifier(None)
+	def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+		
+		# resample our dataframes
+		dataframe_5 = resample_to_interval(dataframe, self.get_ticker_indicator() * 5)
+		dataframe_15 = resample_to_interval(dataframe, self.get_ticker_indicator() * 15)
+		dataframe_30 = resample_to_interval(dataframe, self.get_ticker_indicator() * 30)
+		dataframe_60 = resample_to_interval(dataframe, self.get_ticker_indicator() * 60)
+		dataframe_4h = resample_to_interval(dataframe, self.get_ticker_indicator() * 240)
+		
+		#dataframe_1d = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe='1d')
+		#dataframe_1w = resample_to_interval(dataframe_1d, self.get_ticker_indicator() * 10080)
+		#dataframe_1m = resample_to_interval(dataframe_1d, self.get_ticker_indicator() * 43200)
+
+		dataframe_1d = resample_to_interval(dataframe, self.get_ticker_indicator() * 1440)
+		#dataframe_1w = resample_to_interval(dataframe, self.get_ticker_indicator() * 10080)
+		#dataframe_1m = resample_to_interval(dataframe, self.get_ticker_indicator() * 43200)
+		dataframe = self.add_indicators(dataframe)
+		dataframe_5 = self.add_indicators(dataframe_5)
+		dataframe_30 = self.add_indicators(dataframe_30)
+		dataframe_60 = self.add_indicators(dataframe_60)
+		dataframe_4h = self.add_indicators(dataframe_4h)
+		dataframe_1d = self.add_indicators(dataframe_1d)
+		#self.chan.plot_dual(dataframe_5, dataframe_30)
+		dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+
+		state_list, fx_list = self.chan.get_klc_strength_list(dataframe_15)
+		dataframe_15['state'] = state_list
+		dataframe_15['fx'] = fx_list
+		klc_list = self.chan.get_klc_list(dataframe_15)
+		bi_list = self.chan.cal_bi_list(klc_list)
+		if self.last_time + timedelta(minutes=1) < datetime.now():
+			print(state_list[-1], state_list[-2], state_list[-3], state_list[-4], state_list[-5])
+			print(fx_list[-1], fx_list[-2], fx_list[-3], fx_list[-4], fx_list[-5])
+			print(klc_list[-1].klc_fx_type, klc_list[-2].klc_fx_type, klc_list[-3].klc_fx_type, klc_list[-4].klc_fx_type, klc_list[-5].klc_fx_type)
+			print("-------------------------------------------------------------------------------")
+			self.last_time = datetime.now()
+		#dataframe = resampled_merge(dataframe, dataframe_5)
+		dataframe = resampled_merge(dataframe, dataframe_15)
+		#dataframe = resampled_merge(dataframe, dataframe_30)
+		#dataframe = resampled_merge(dataframe, dataframe_60)
+		#dataframe = resampled_merge(dataframe, dataframe_4h)
+		return dataframe
+	
+	def add_indicators(self, df):
+		fast = 8
+		slow = 16
+		period = 6
+		macd = ta.MACD(df, fastperiod=fast, slowperiod=slow, signalperiod=period)
+		df['macd'] = macd['macd']
+		df['macdsignal'] = macd['macdsignal']
+		df['macdhist'] = macd['macdhist']
+		df['ma5'] = ta.MA(df, timeperiod=5)
+		df['ma10'] = ta.MA(df, timeperiod=10)
+		df['ma30'] = ta.EMA(df, timeperiod=30)
+		df['ma250'] = ta.MA(df, timeperiod=250)
+		df['rsi'] = ta.RSI(df, timeperiod=14)
+		df['volume_ratio'] = self.cal_volume_ratio(df)
+		return df
+	def cal_volume_ratio(self, dataframe, window=10):
+		df = dataframe.copy()
+		# 计算过去N根K线的平均成交量
+		df['avg_volume'] = df['volume'].rolling(window=window).mean()
+		# 计算量比
+		df['volume_ratio'] = df['volume'] / df['avg_volume']
+		# 填充缺失值（前N根K线）
+		df['volume_ratio'] = df['volume_ratio'].fillna(1.0)
+		return df['volume_ratio']
+	def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+		state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time5)
+		fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time5)
+		dataframe.loc[
+			(
+				#(dataframe['state'] == "-30")
+				(dataframe[state_str].shift(self.time5*2) > 1.0) &
+				(dataframe[fx_str].shift(self.time5*2) == -1)
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10") &
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "-10") &
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10")
+				#(qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal'])) 
+			),
+			['enter_long', 'enter_tag']] = (1, 'long_signal_chan')
+		dataframe.loc[
+			(
+				#(dataframe['state'] == "-30")
+				(dataframe[state_str].shift(self.time5*2) > 1.0) &
+				(dataframe[fx_str].shift(self.time5*2) == 1)
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10") &
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "-10") &
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10")
+				#(qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal'])) 
+			),
+			['enter_short', 'enter_tag']] = (1, 'short_signal_chan')
+		return dataframe
+	def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+		state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time5)
+		fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time5)
+		dataframe.loc[
+			(
+				#(dataframe['state']== "30")
+				(dataframe[state_str].shift(self.time5*2) > 1.0) &
+				(dataframe[fx_str].shift(self.time5*2) == 1)
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "10") &
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time60)] == "10")
+			),
+			['exit_long', 'exit_tag']] = (1, 'long_close_signal_chan')
+		dataframe.loc[
+			(
+				#(dataframe['state']== "30")
+				(dataframe[state_str].shift(self.time5*2) > 1.0) &
+				(dataframe[fx_str].shift(self.time5*2) == -1)
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "10") &
+				#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time60)] == "10")
+			),
+			['exit_short', 'exit_tag']] = (1, 'short_close_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])