freqtrade-实战 8- 回溯、绘图和策略分析
一、说明
Configuring settings for FreqUI
配置 FreqUI 的设置
Running backtests directly from the web interface
直接从 Web 界面运行回测
Reviewing backtest results with a visual summary
使用可视化摘要查看回溯测试结果
Plotting indicators for better analysis
绘制指标以便更好地分析
Comparing multiple strategies side by side
并排比较多种策略
二、可视化
# Freqtrade UI Guide
## 1. To generate a secure password, best use a password manager, or use the below code.
import secrets
secrets.token_hex()
## 2. Webserver mode
freqtrade webserver --config user_data/config_binance_spot.json
## 3. FreqUI
https://www.freqtrade.io/en/develop/freq-ui/
## 4. Advanced plot configuration
https://www.freqtrade.io/en/develop/plotting/#advanced-plot-configurationconfig_binance_spot.json 配置文件：
{
"max_open_trades": 5,
"stake_currency": "USDT",
"stake_amount": "unlimited",
"tradable_balance_ratio": 0.99,
"fiat_display_currency": "USD",
"available_capital": 1000,
"dry_run": true,
"dry_run_wallet": 1000,
"cancel_open_orders_on_exit": false,
"trading_mode": "spot",
"margin_mode": "",
"unfilledtimeout": {
"entry": 10,
"exit": 10,
"exit_timeout_count": 0,
"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": "",
"secret": "",
"ccxt_config": {},
"ccxt_async_config": {},
"pair_whitelist": [
"BTC/USDT",
"ETH/USDT",
"BNB/USDT",
"SOL/USDT",
"XRP/USDT",
"ADA/USDT",
"AVAX/USDT",
"DOGE/USDT",
"TRX/USDT",
"DOT/USDT",
"LINK/USDT",
"MATIC/USDT",
"ICP/USDT"
],
"pair_blacklist": [
]
},
"pairlists": [
{
"method": "StaticPairList"
}
],
"telegram": {
"enabled": false,
"token": "",
"chat_id": ""
},
"api_server": {
"enabled": true,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "error",
"enable_openapi": false,
"jwt_secret_key": "46207b46b8be80742e89ceb4b491f6f9734ac61b5b9ea79a6ec5f107dc9a8d76",
"ws_token": "BS5QfNYaeZutNyu46Sm4ucmjrCVLAB9JQg",
"CORS_origins": [],
"username": "Freqtrader",
"password": "!QAZ2wsx"
},
"bot_name": "freqtrade",
"initial_state": "running",
"force_entry_enable": false,
"internals": {
"process_throttle_secs": 5
}
}AwesomeStrategy3.json 配置文件：
{
"strategy_name": "AwesomeStrategy3",
"params": {
"trailing": {
"trailing_stop": false,
"trailing_stop_positive": null,
"trailing_stop_positive_offset": 0.0,
"trailing_only_offset_is_reached": false
},
"max_open_trades": {
"max_open_trades": 5
},
"buy": {
"buy_adx": 21.9,
"buy_adx_enabled": true,
"buy_rsi": 29,
"buy_tema": 18
},
"sell": {
"sell_rsi": 82
},
"protection": {},
"roi": {
"0": 0.464,
"313": 0.184,
"923": 0.08,
"1855": 0
},
"stoploss": {
"stoploss": -0.332
}
},
"ft_stratparam_v": 1,
"export_time": "2024-09-12 04:40:45.652026+00:00"
}AwesomeStrategy3.py 策略文件：
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np
import pandas as pd
from pandas import DataFrame
from datetime import datetime
from typing import Optional, Union
from functools import reduce
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IntParameter, IStrategy, merge_informative_pair)
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import pandas_ta as pta
from technical import qtpylib
class AwesomeStrategy3(IStrategy):
"""
This is a strategy template to get you started.
More information in https://www.freqtrade.io/en/latest/strategy-customization/
You can:
:return: a Dataframe with all mandatory indicators for the strategies
- Rename the class name (Do not forget to update class_name)
- Add any methods you want to build your strategy
- Add any lib you need to build your strategy
You must keep:
- the lib in the section "Do not remove these libs"
- the methods: populate_indicators, populate_entry_trend, populate_exit_trend
You should keep:
- timeframe, minimal_roi, stoploss, trailing_*
"""
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 3
# Optimal timeframe for the strategy.
timeframe = '5m'
# Can this strategy go short?
can_short: bool = False
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"60": 0.01,
"30": 0.02,
"0": 0.04
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.10
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Run "populate_indicators()" only for new candle.
process_only_new_candles = True
# These values can be overridden in the config.
use_exit_signal = True
exit_profit_only = False
ignore_roi_if_entry_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 150
# Strategy parameters
buy_rsi = IntParameter(10, 40, default=30, space="buy")
sell_rsi = IntParameter(60, 90, default=70, space="sell")
buy_adx_enabled = BooleanParameter(default=True, space="buy")
# buy_adx_enabled = CategoricalParameter([True, False], default=True, space="buy")
buy_adx = DecimalParameter(20, 40, decimals=1, default=30.1, space="buy")
buy_tema = IntParameter(5, 30, default=9, space="buy")
# Optional order type mapping.
order_types = {
'entry': 'limit',
'exit': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'entry': 'GTC',
'exit': 'GTC'
}
@property
def plot_config(self):
plot_config = {
"main_plot": {
f"tema_{self.buy_tema.value}": {
"color": "red",
"type": "line"
},
"bb_upperband": {
"color": "#008af4",
"type": "line",
"fill_to": "bb_lowerband"
},
"bb_middleband": {
"color": "#ffd700",
"type": "line"
},
"bb_lowerband": {
"color": "#008af4",
"type": "line"
}
},
"subplots": {
"RSI": {
"rsi": {
"color": "#ff8000",
"type": "line"
}
},
"ADX": {
"adx": {
"color": "#ff0000",
"type": "line"
}
}
}
}
return plot_config
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# ADX
dataframe['adx'] = ta.ADX(dataframe)
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
dataframe['buy_rsi'] = self.buy_rsi.value
dataframe['sell_rsi'] = self.sell_rsi.value
# Bollinger Bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
dataframe["bb_percent"] = (
(dataframe["close"] - dataframe["bb_lowerband"]) /
(dataframe["bb_upperband"] - dataframe["bb_lowerband"])
)
dataframe["bb_width"] = (
(dataframe["bb_upperband"] - dataframe["bb_lowerband"]) / dataframe["bb_middleband"]
)
# TEMA - Triple Exponential Moving Average
for val in self.buy_tema.range:
dataframe[f'tema_{val}'] = ta.TEMA(dataframe, timeperiod=val)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
conditions = []
if self.buy_adx_enabled.value:
conditions.append(dataframe['adx'] > self.buy_adx.value)
conditions.append(
(
(qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) & # Signal: RSI crosses above buy_rsi
(dataframe[f'tema_{self.buy_tema.value}'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle
(dataframe[f'tema_{self.buy_tema.value}'] > dataframe[f'tema_{self.buy_tema.value}'].shift(1)) & # Guard: tema is raising
(dataframe['volume'] > 0) # Make sure Volume is not 0
)
)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) & # Signal: RSI crosses above sell_rsi
(dataframe[f'tema_{self.buy_tema.value}'] > dataframe['bb_middleband']) & # Guard: tema above BB middle
(dataframe[f'tema_{self.buy_tema.value}'] < dataframe[f'tema_{self.buy_tema.value}'].shift(1)) & # Guard: tema is falling
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'exit_long'] = 1
return dataframe
三、实战
# https://www.freqtrade.io/en/stable/freq-ui/#backtesting
freqtrade webserver --config user_data/config/config_binance_spot.json运行 freqtrade webserver （注意这里不是交易的命令freqtrade trade 命令服务），然后显示回测的界面：
相关文章：
06 Freqtrade UI Guide: Backtesting, Plotting, and Strategy Analysis
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