添加新策略用第三类买卖点
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@@ -126,7 +126,8 @@ class ChanLun():
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def get_bsp_state(self, dataframe):
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return self.tf_df.get_bsp_state(dataframe)
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def get_structure_zones(self, current_price=None, config=None):
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if config is None:
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@@ -157,7 +157,40 @@ class TF_DF():
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klu_state_list.append("00")
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print(klu_state_list[:20])
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return klu_state_list
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def get_bsp_state(self, dataframe):
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klu_list = self.get_klu_list(dataframe)
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klc_list = self.get_klc_list(klu_list)
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bi_list = self.cal_bi_list(klc_list)
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seg_list = self.get_seg_list(bi_list)
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bi_zs_list = self.cal_bi_zs(seg_list)
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bsp_list = self.find_all_bsp(bi_list, bi_zs_list)
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bsp_state_list = [0] * len(dataframe)
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klc_index = 0
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for index in range(0, len(dataframe)):
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if klc_index == len(klc_list):
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klc_index = len(klc_list) - 1
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klc = klc_list[klc_index]
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if klc.end_klu and klc.end_klu.idx == index:
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if klc.klc_fx_type == Chan_KLC_FX.TOP2:
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bi = klc.bi.pre
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if bi and bi.is_sure and bi.end_klc.bsp_type == Chan_BSP_TYPE.B3:
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# 第三类买点
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bsp_state_list[index] = -1
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#print(klc.end_time, "B3")
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else:
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bsp_state_list[index] = 0
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elif klc.klc_fx_type == Chan_KLC_FX.BOTTOM2:
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bi = klc.bi.pre
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if bi and bi.is_sure and bi.end_klc.bsp_type == Chan_BSP_TYPE.S3:
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# 第三类卖点
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bsp_state_list[index] = 1
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#print(klc.end_time, "S3")
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else:
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bsp_state_list[index] = 0
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klc_index += 1
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else:
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bsp_state_list[index] = 0
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return bsp_state_list
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def get_ema_state(self, dataframe):
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klu_list = self.get_klu_list(dataframe)
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klc_list = self.get_klc_list(klu_list)
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@@ -947,7 +980,7 @@ class TF_DF():
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bi_list = []
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last_top = None
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last_bottom = None
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bi_klc_min = 3
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bi_klc_min = 4
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last_fx_klc = None
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for klc in klc_list:
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if last_fx_klc:
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@@ -0,0 +1,89 @@
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{
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"$schema": "https://schema.freqtrade.io/schema.json",
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"max_open_trades": 1,
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"stake_currency": "USDT",
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"stake_amount": "unlimited",
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"tradable_balance_ratio": 0.99,
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"fiat_display_currency": "USD",
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"dry_run": true,
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"db_url": "sqlite:///tradesv3.chanlun_btc_1m.sqlite",
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"dry_run_wallet": 1000,
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"cancel_open_orders_on_exit": true,
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"trading_mode": "futures",
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"margin_mode": "isolated",
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"can_short" : true,
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"timeframe" : "1m",
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"process_only_new_candles" : false,
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"unfilledtimeout": {
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"entry": 1,
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"exit": 1,
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"exit_timeout_count": 5,
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"unit": "minutes"
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},
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"order_types": {
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"entry": "limit",
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"exit": "limit",
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"stoploss": "limit",
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"stoploss_on_exchange": false
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},
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"entry_pricing": {
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"price_side": "same",
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"use_order_book": true
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},
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"exit_pricing": {
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"price_side": "same",
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"use_order_book": true
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},
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"exchange": {
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"name": "binance",
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"key": "hvoXanRExQvcN4tyGFvEnsSF4gqxXp6ZJnBu5lnhvlVuHaDbj2PhLBQGCLkkyeI8",
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"secret": "3UKA2oyDj7OoXrausmnaLwLlNfXmlNf2imBdmQqqKHArcJfk6X9xjaUF19wzu82l",
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"ccxt_config": {
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"proxies": {
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"http": "http://127.0.0.1:7897",
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"https": "http://127.0.0.1:7897"
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}
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},
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"ccxt_async_config": {
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"aiohttp_proxy": "http://127.0.0.1:7897"
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},
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"pair_whitelist": [
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"BTC/USDT:USDT"
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],
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"pair_blacklist": [
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"BNB/.*"
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]
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},
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"pairlists": [
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{
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"method": "StaticPairList",
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"number_assets": 1,
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"sort_key": "quoteVolume",
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"min_value": 0,
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"refresh_period": 1800
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}
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],
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"telegram": {
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"enabled": true,
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"token": "8197349375:AAH208JghCq8raFYF-IpnobYknCr6iGDH_0",
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"chat_id": "580807463"
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},
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"api_server": {
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"enabled": true,
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"listen_ip_address": "0.0.0.0",
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"listen_port": 8814,
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"verbosity": "error",
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"enable_openapi": false,
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"jwt_secret_key": "14d3510740e2c39a973a8895f1aa2704d98d08b86170260085709fa5ea48251d",
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"ws_token": "dtKKDnafBrX4icq_ZCw7acJTahTK4h_yvg",
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"CORS_origins": [],
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"username": "freqtrader",
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"password": "FreqTrade007"
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},
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"bot_name": "freqtrade",
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"initial_state": "running",
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"force_entry_enable": false,
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"internals": {
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"process_throttle_secs": 1
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}
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}
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@@ -0,0 +1,133 @@
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# --- Do not remove these libs ---
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from statistics import median
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from freqtrade.strategy import IStrategy, stoploss_from_absolute
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import sys
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import os
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# 添加父目录到系统路径
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from ChanLun import ChanLun
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from ChanEnum import Chan_FX_TYPE, Chan_KLC_FX, Chan_BI_DIR, Chan_KLC_FX, Chan_BSP_TYPE
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# --------------------------------
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from technical.util import resample_to_interval, resampled_merge
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import talib.abstract as ta
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from pandas import DataFrame
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import pandas as pd
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from datetime import datetime, timedelta
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from typing import Optional
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import logging
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logger = logging.getLogger(__name__)
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### Now you can use logger.info('asfd') to log
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# freqtrade plot-dataframe --strategy ChanLun_BTC_1m --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_30.json --timerange=20250309-
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# freqtrade trade -c ./user_data/Chan/config/ChanLun_BTC_1m.json --strategy ChanLun_BTC_1m --strategy-path ./user_data/Chan/strategies
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# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_BTC_1m.json --strategy ChanLun_BTC_1m --strategy-path ./user_data/Chan/strategies --timerange=20260501-
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# freqtrade download-data -c ./user_data/Chan/config/ChanLun_BTC_1m.json -t 1m 1m 1h 1d 1M --pairs BTC/USDT:USDT --timerange=20250405-
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# freqtrade download-data -c ./user_data/Chan/config/ChanLun_BTC_1m.json -t 1m 1h 1d 1M --pairs BTC/USDT --timerange=20170101-
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi --strategy ChanLun_BTC_1m --strategy-path ./user_data/Chan/strategies -c ./user_data/Chan/config/ChanLun_BTC_1m.json -e 200 --timerange=20250201-20250901
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# freqtrade edge -c ./user_data/Chan/config/ChanLun_BTC_1m.json --strategy ChanLun_BTC_1m --strategy-path ./user_data/Chan/strategies --timerange 20250721-20250901
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# freqtrade plot-dataframe -c ./user_data/Chan/config/ChanLun_BTC_1m.json --strategy ChanLun_BTC_1m --strategy-path ./user_data/Chan/strategies --timerange 20250721-20250901
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# sudo docker compose run --rm chanlun_btc backtesting -c ./user_data/Chan/config/ChanLun_BTC_1m.json --strategy ChanLun_BTC_1m --strategy-path ./user_data/Chan/strategies --timerange=20250721-
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# sudo docker compose run --rm chanlun_btc download-data -c ./user_data/Chan/config/ChanLun_BTC_1m.json --pairs BTC/USDT:USDT -t 1m --timerange 20240101-
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# sudo docker compose run --rm chanlun_btc trade -c ./user_data/Chan/config/ChanLun_BTC_1m.json --strategy ChanLun_BTC_1m --strategy-path ./user_data/Chan/strategies
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class ChanLun_BTC_1m(IStrategy):
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"""
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交易核心(缠论):
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- 仅在缠论一/二/三类买卖点出现时交易。
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- 信号触发条件:前一笔被确认(bi.is_sure)时,该笔 end_klc 已被标记为 B1/B2/B3 或 S1/S2/S3。
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- 不使用未确认笔,不使用“状态猜测”列。
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"""
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INTERFACE_VERSION: int = 3
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# Minimal ROI designed for the strategy.
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# This attribute will be overridden if the config file contains "minimal_roi"
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# 30m and 1h
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minimal_roi = {
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"0": 0.05,
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"60": 0.03,
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"120": 0.01,
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"180": 0
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}
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# 5m and 15m
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minimal_roi_1 = {
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"0": 0.1,
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"60": 0.05,
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"120": 0.02,
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"240": 0
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}
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# 15m and 30m
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minimal_roi_1 = {
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"0": 0.1,
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"240": 0.05,
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"480": 0.03,
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"600": 0
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}
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minimal_roi_1 = {
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"0": 1.50,
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"120": 0.05,
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"240": 0.025,
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"360": 0
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}
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can_short = True
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lev = 1.0
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stoploss = -0.3 # 设置为很大的负值,让custom_stoploss来控制
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trailing_stop = False
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trailing_stop_positive = 0.03
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trailing_stop_positive_offset = 0.06
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trailing_only_offset_is_reached = False
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# 关闭分批止盈/仓位调整
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startup_candle_count = 500
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# 以 1m 为基础周期时,1h = 60 根K线(用于读取 resample_60_* 列并做确认延迟)
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chan = ChanLun()
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe = self.add_indicators(dataframe)
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dataframe['bsp_state'] = self.chan.get_bsp_state(dataframe)
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return dataframe
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def add_indicators(self, df):
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fast = 12
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slow = 26
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period = 9
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macd = ta.MACD(df, fastperiod=fast, slowperiod=slow, signalperiod=period)
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df['atr'] = ta.ATR(df, timeperiod=14)
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df['macd'] = macd['macd']
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df['macdsignal'] = macd['macdsignal']
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df['macdhist'] = macd['macdhist']
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df['ema24'] = ta.EMA(df, timeperiod=24)
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df['ema52'] = ta.EMA(df, timeperiod=52)
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return df
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe.loc[
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(
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(dataframe['bsp_state'].shift(1) == -1)
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),
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['enter_long', 'enter_tag']] = (1, 'long_signal_chan')
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dataframe.loc[
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(
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(dataframe['bsp_state'].shift(1) == 1)
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),
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['enter_short', 'enter_tag']] = (1, 'short_signal_chan')
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return dataframe
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def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# 出场和进场共用同一套“确认笔 + end_klc 买卖点”语义。
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dataframe.loc[
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(
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(dataframe['bsp_state'].shift(1) == 1)
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),
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['exit_long', 'exit_tag']] = (1, 'long_signal_chan')
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dataframe.loc[
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(
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(dataframe['bsp_state'].shift(1) == -1)
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),
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['exit_short', 'exit_tag']] = (1, 'short_signal_chan')
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return dataframe
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def leverage(self, pair: str, current_time: datetime, current_rate: float,
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proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str,
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**kwargs) -> float:
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return self.lev
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def get_ticker_indicator(self):
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return int(self.timeframe[:-1])
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@@ -564,6 +564,7 @@ def analyze_chan(df, symbol=None, timeframe=None):
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bsp_list = []
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if len(bi_zs_list) > 0:
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bsp_list = chan.find_all_bsp(bi_list, bi_zs_list)
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#bsp_state_list = chan.get_bsp_state(df)
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#for bsp in bsp_list:
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#print(bsp.end_time, bsp.type, bsp.dir)
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# 添加买卖点识别
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