加入一个回测，
This commit is contained in:
ddrwode
580
bb_backtest_2025_multi_timeframe.py
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580
bb_backtest_2025_multi_timeframe.py
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"""
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布林带延迟反转策略回测 - 2025年多周期测试
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测试1分钟和15分钟周期的收益对比
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策略规则：
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1. BB(10, 2.5)
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2. 空仓触上轨开空，触下轨开多
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3. 同向加仓最多1次，保证金1%
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4. 延迟反转：触轨不立刻平仓，记录价格，回调到该价再平仓+反向开仓
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5. 中轨平半+回开仓价全平
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回测参数：
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- 本金: 100U
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- 杠杆: 100x
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- 逐仓模式
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- 开仓保证金: 1%
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- 手续费: 0.05% (万五)
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- 返佣: 90%，次日早上8点到账
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"""
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import pandas as pd
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from pathlib import Path
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from peewee import *
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from loguru import logger
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import numpy as np
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# 数据库配置
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DB_PATH = Path(__file__).parent / 'models' / 'database.db'
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db = SqliteDatabase(str(DB_PATH))
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class BitMartETH1M(Model):
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"""1分钟K线模型"""
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id = BigIntegerField(primary_key=True)
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open = FloatField(null=True)
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high = FloatField(null=True)
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low = FloatField(null=True)
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close = FloatField(null=True)
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class Meta:
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database = db
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table_name = 'bitmart_eth_1m'
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class BitMartETH3M(Model):
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"""3分钟K线模型"""
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id = BigIntegerField(primary_key=True)
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open = FloatField(null=True)
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high = FloatField(null=True)
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low = FloatField(null=True)
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close = FloatField(null=True)
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class Meta:
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database = db
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table_name = 'bitmart_eth_3m'
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class BitMartETH5M(Model):
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"""5分钟K线模型"""
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id = BigIntegerField(primary_key=True)
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open = FloatField(null=True)
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high = FloatField(null=True)
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low = FloatField(null=True)
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close = FloatField(null=True)
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class Meta:
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database = db
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table_name = 'bitmart_eth_5m'
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class BitMartETH15M(Model):
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"""15分钟K线模型"""
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id = BigIntegerField(primary_key=True)
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open = FloatField(null=True)
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high = FloatField(null=True)
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low = FloatField(null=True)
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close = FloatField(null=True)
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class Meta:
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database = db
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table_name = 'bitmart_eth_15m'
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class BBDelayReversalBacktest:
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"""布林带延迟反转策略回测"""
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def __init__(self, timeframe='1m'):
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# 策略参数
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self.timeframe = timeframe
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self.bb_period = 10
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self.bb_std = 2.5
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self.initial_capital = 100 # 初始本金100U
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self.leverage = 100 # 100倍杠杆
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self.fee_rate = 0.0005 # 万五手续费
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self.rebate_rate = 0.9 # 90%返佣
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self.margin_ratio = 0.01 # 开仓保证金1%
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self.rebate_credit_hour = 8 # 次日早上8点返佣到账
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# 账户状态
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self.capital = self.initial_capital
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self.position = 0 # 持仓量（正=多，负=空）
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self.position_count = 0 # 持仓次数（0=空仓，1=首次，2=加仓）
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self.entry_price = 0 # 开仓均价
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self.total_margin = 0 # 总保证金
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# 延迟反转状态
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self.delay_reverse_price = None
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self.delay_reverse_type = None
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self.delay_reverse_kline_index = None
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# 中轨平仓记录
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self.mid_closed_half = False
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# 交易记录
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self.trades = []
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self.pending_rebates = []
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self.total_rebate_credited = 0.0
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def calculate_bollinger_bands(self, df):
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"""计算布林带（整体右移1根，避免使用当前K收盘价）"""
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df['sma'] = df['close'].rolling(window=self.bb_period).mean()
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df['std'] = df['close'].rolling(window=self.bb_period).std()
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df['upper'] = (df['sma'] + self.bb_std * df['std']).shift(1)
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df['lower'] = (df['sma'] - self.bb_std * df['std']).shift(1)
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df['middle'] = df['sma'].shift(1)
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return df
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def schedule_rebate(self, fee, timestamp):
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"""登记返佣到账时间（次日08:00，上海时间）"""
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rebate = fee * self.rebate_rate
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if rebate <= 0:
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return
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trade_utc = pd.Timestamp(timestamp, tz='UTC')
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trade_local = trade_utc.tz_convert('Asia/Shanghai')
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credit_local = (trade_local + pd.Timedelta(days=1)).normalize() + pd.Timedelta(hours=self.rebate_credit_hour)
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credit_utc = credit_local.tz_convert('UTC').tz_localize(None)
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self.pending_rebates.append({
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'credit_time': credit_utc,
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'amount': rebate,
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'trade_time': trade_utc.tz_localize(None),
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})
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def apply_pending_rebates(self, current_time):
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"""处理当前时刻前应到账的返佣"""
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if not self.pending_rebates:
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return
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remaining = []
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for item in self.pending_rebates:
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if item['credit_time'] <= current_time:
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amount = item['amount']
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self.capital += amount
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self.total_rebate_credited += amount
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else:
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remaining.append(item)
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self.pending_rebates = remaining
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def clear_delay_reversal(self):
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"""清理延迟反转状态"""
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self.delay_reverse_price = None
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self.delay_reverse_type = None
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self.delay_reverse_kline_index = None
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def mark_delay_reversal(self, reverse_type, trigger_price, kline_index):
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"""记录延迟反转触发信息"""
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self.delay_reverse_type = reverse_type
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self.delay_reverse_price = trigger_price
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self.delay_reverse_kline_index = kline_index
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def check_delay_reversal_signal(self, i, row, prev_row):
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"""检查延迟反转是否成立"""
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if self.position == 0 or self.delay_reverse_price is None or self.delay_reverse_kline_index is None:
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return None
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offset = i - self.delay_reverse_kline_index
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if offset <= 0:
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return None
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high = row['high']
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low = row['low']
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if self.delay_reverse_type == 'long_to_short':
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# 多转空：回调确认
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if offset == 1 and low <= self.delay_reverse_price:
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return 'short', self.delay_reverse_price, "次K回调确认"
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if offset >= 2 and prev_row is not None:
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prev_upper = prev_row['upper']
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prev_touch_upper = pd.notna(prev_upper) and prev_row['high'] >= prev_upper
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if prev_touch_upper:
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if low <= prev_upper:
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return 'short', prev_upper, "上一根触上轨后回调确认"
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else:
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prev_body_low = min(prev_row['open'], prev_row['close'])
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if low <= prev_body_low:
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return 'short', prev_body_low, "跌破上一根实体确认"
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elif self.delay_reverse_type == 'short_to_long':
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# 空转多：反弹确认
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if offset == 1 and high >= self.delay_reverse_price:
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return 'long', self.delay_reverse_price, "次K反弹确认"
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if offset >= 2 and prev_row is not None:
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prev_lower = prev_row['lower']
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prev_touch_lower = pd.notna(prev_lower) and prev_row['low'] <= prev_lower
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if prev_touch_lower:
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if high >= prev_lower:
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return 'long', prev_lower, "上一根触下轨后反弹确认"
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else:
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prev_body_high = max(prev_row['open'], prev_row['close'])
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if high >= prev_body_high:
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return 'long', prev_body_high, "突破上一根实体确认"
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return None
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def open_position(self, price, direction, timestamp, reason):
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"""开仓或加仓"""
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if self.position_count not in (0, 1):
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return False
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if self.position_count == 1:
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current_direction = 'long' if self.position > 0 else 'short'
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if direction != current_direction:
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return False
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margin = self.capital * self.margin_ratio
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if margin <= 0:
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return False
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position_size = margin * self.leverage / price
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fee = position_size * price * self.fee_rate
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required = margin + fee
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if self.capital < required:
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return False
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self.capital -= required
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self.schedule_rebate(fee, timestamp)
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if self.position_count == 0:
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self.position = position_size if direction == 'long' else -position_size
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self.entry_price = price
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self.total_margin = margin
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self.position_count = 1
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else:
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old_size = abs(self.position)
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new_size = old_size + position_size
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old_value = old_size * self.entry_price
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new_value = position_size * price
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self.entry_price = (old_value + new_value) / new_size
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self.position = new_size if direction == 'long' else -new_size
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self.total_margin += margin
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self.position_count = 2
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self.mid_closed_half = False
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self.trades.append({
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'timestamp': timestamp,
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'action': f'开{direction}' if self.position_count == 1 else f'加{direction}',
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'price': price,
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'size': position_size,
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'margin': margin,
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'fee': fee,
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'capital': self.capital,
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'reason': reason
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})
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return True
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def close_position(self, price, ratio, timestamp, reason):
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"""平仓"""
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if self.position == 0:
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return False
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ratio = min(max(ratio, 0.0), 1.0)
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if ratio == 0:
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return False
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close_size = abs(self.position) * ratio
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if self.position > 0:
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pnl = close_size * (price - self.entry_price)
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else:
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pnl = close_size * (self.entry_price - price)
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fee = close_size * price * self.fee_rate
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released_margin = self.total_margin * ratio
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self.capital += released_margin + pnl - fee
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self.schedule_rebate(fee, timestamp)
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if ratio >= 0.999:
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self.position = 0
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self.position_count = 0
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self.total_margin = 0
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self.entry_price = 0
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self.mid_closed_half = False
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self.clear_delay_reversal()
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else:
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self.position *= (1 - ratio)
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self.total_margin *= (1 - ratio)
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self.trades.append({
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'timestamp': timestamp,
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'action': f'平仓{int(ratio*100)}%',
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'price': price,
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'size': close_size,
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'pnl': pnl,
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'fee': fee,
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'capital': self.capital,
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'reason': reason
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})
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return True
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def run_backtest(self, start_date, end_date):
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"""运行回测"""
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# 重置状态
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self.capital = self.initial_capital
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self.position = 0
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self.position_count = 0
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self.entry_price = 0
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self.total_margin = 0
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self.mid_closed_half = False
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self.trades = []
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self.pending_rebates = []
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self.total_rebate_credited = 0.0
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self.clear_delay_reversal()
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logger.info(f"{'='*80}")
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logger.info(f"开始回测: {start_date} ~ {end_date} | 周期: {self.timeframe}")
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logger.info(f"初始资金: {self.initial_capital}U | 杠杆: {self.leverage}x | BB({self.bb_period}, {self.bb_std})")
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logger.info(f"{'='*80}")
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# 从数据库加载数据
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start_dt = pd.Timestamp(start_date)
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end_dt = pd.Timestamp(end_date)
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if isinstance(end_date, str) and len(end_date) <= 10:
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end_dt = end_dt + pd.Timedelta(days=1) - pd.Timedelta(milliseconds=1)
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start_ts = int(start_dt.timestamp() * 1000)
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end_ts = int(end_dt.timestamp() * 1000)
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# 根据周期选择数据表
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model_mapping = {
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'1m': BitMartETH1M,
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'3m': BitMartETH3M,
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'5m': BitMartETH5M,
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'15m': BitMartETH15M,
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}
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Model = model_mapping.get(self.timeframe)
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if Model is None:
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logger.error(f"不支持的周期: {self.timeframe}")
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return None
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query = Model.select().where(
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(Model.id >= start_ts) & (Model.id <= end_ts)
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).order_by(Model.id)
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data = []
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for row in query:
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data.append({
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'timestamp': row.id,
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'open': row.open,
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'high': row.high,
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'low': row.low,
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'close': row.close
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})
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if not data:
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logger.error("没有找到数据！")
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return None
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df = pd.DataFrame(data)
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df['datetime'] = pd.to_datetime(df['timestamp'], unit='ms')
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logger.info(f"加载数据: {len(df)} 根K线")
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logger.info(f"时间范围: {df['datetime'].min()} ~ {df['datetime'].max()}")
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# 计算布林带
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df = self.calculate_bollinger_bands(df)
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if len(df) <= self.bb_period + 1:
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logger.error("数据不足，无法执行回测")
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return None
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# 逐根K线回测
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for i in range(self.bb_period, len(df)):
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row = df.iloc[i]
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prev_row = df.iloc[i-1] if i > 0 else None
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signal_dt = row['datetime']
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signal_ts = signal_dt.strftime('%Y-%m-%d %H:%M')
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high = row['high']
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low = row['low']
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close = row['close']
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upper = row['upper']
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lower = row['lower']
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middle = row['middle']
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# 处理返佣到账
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self.apply_pending_rebates(signal_dt)
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if pd.isna(upper) or pd.isna(lower) or pd.isna(middle):
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continue
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# 检查延迟反转确认
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if self.delay_reverse_price is not None:
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reversal_signal = self.check_delay_reversal_signal(i, row, prev_row)
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if reversal_signal is not None and self.position != 0:
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new_direction, reversal_price, reason = reversal_signal
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self.close_position(reversal_price, 1.0, signal_ts, f"{reason}-平仓")
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self.open_position(reversal_price, new_direction, signal_ts, f"{reason}-开仓")
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self.mid_closed_half = False
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self.clear_delay_reversal()
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continue
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# 中轨平仓逻辑
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if self.position != 0:
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if self.position > 0:
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# 回到开仓价全平+反手
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if self.mid_closed_half and low <= self.entry_price:
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self.close_position(close, 1.0, signal_ts, "回开仓价全平")
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self.open_position(close, 'short', signal_ts, "回开仓价反手开空")
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self.mid_closed_half = False
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continue
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# 触中轨平半
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if not self.mid_closed_half and low <= middle <= high:
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self.close_position(close, 0.5, signal_ts, "触中轨平50%")
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self.mid_closed_half = True
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continue
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else: # 空仓
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# 回到开仓价全平+反手
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if self.mid_closed_half and high >= self.entry_price:
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self.close_position(close, 1.0, signal_ts, "回开仓价全平")
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self.open_position(close, 'long', signal_ts, "回开仓价反手开多")
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self.mid_closed_half = False
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continue
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# 触中轨平半
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if not self.mid_closed_half and low <= middle <= high:
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self.close_position(close, 0.5, signal_ts, "触中轨平50%")
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self.mid_closed_half = True
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continue
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|
||||
# 开仓与加仓逻辑
|
||||
if self.position == 0:
|
||||
self.clear_delay_reversal()
|
||||
|
||||
# 触上轨开空
|
||||
if high >= upper:
|
||||
self.open_position(upper, 'short', signal_ts, "触上轨开空")
|
||||
|
||||
# 触下轨开多
|
||||
elif low <= lower:
|
||||
self.open_position(lower, 'long', signal_ts, "触下轨开多")
|
||||
continue
|
||||
|
||||
# 延迟反转触发
|
||||
if self.position > 0 and high >= upper:
|
||||
self.mark_delay_reversal('long_to_short', upper, i)
|
||||
continue
|
||||
|
||||
elif self.position < 0 and low <= lower:
|
||||
self.mark_delay_reversal('short_to_long', lower, i)
|
||||
continue
|
||||
|
||||
# 加仓
|
||||
if self.delay_reverse_price is None and self.position_count == 1:
|
||||
if self.position > 0 and low <= lower:
|
||||
self.open_position(lower, 'long', signal_ts, "触下轨加多")
|
||||
elif self.position < 0 and high >= upper:
|
||||
self.open_position(upper, 'short', signal_ts, "触上轨加空")
|
||||
|
||||
# 回测末尾处理返佣
|
||||
self.apply_pending_rebates(df.iloc[-1]['datetime'])
|
||||
|
||||
# 最后平仓
|
||||
if self.position != 0:
|
||||
final_price = df.iloc[-1]['close']
|
||||
final_time = df.iloc[-1]['datetime'].strftime('%Y-%m-%d %H:%M')
|
||||
self.close_position(final_price, 1.0, final_time, "回测结束平仓")
|
||||
|
||||
# 生成报告
|
||||
return self.generate_report(df)
|
||||
|
||||
def generate_report(self, df):
|
||||
"""生成回测报告"""
|
||||
logger.info(f"\n{'='*80}")
|
||||
logger.info(f"回测报告 - {self.timeframe}")
|
||||
logger.info(f"{'='*80}")
|
||||
|
||||
# 基本统计
|
||||
total_trades = len([t for t in self.trades if '开' in t['action']])
|
||||
win_trades = len([t for t in self.trades if '平' in t['action'] and t.get('pnl', 0) > 0])
|
||||
loss_trades = len([t for t in self.trades if '平' in t['action'] and t.get('pnl', 0) < 0])
|
||||
|
||||
total_pnl = sum([t.get('pnl', 0) for t in self.trades])
|
||||
total_fee = sum([t.get('fee', 0) for t in self.trades])
|
||||
pending_rebate = sum([x['amount'] for x in self.pending_rebates])
|
||||
realized_net_fee = total_fee - self.total_rebate_credited
|
||||
|
||||
final_capital = self.capital
|
||||
roi = (final_capital - self.initial_capital) / self.initial_capital * 100
|
||||
|
||||
logger.info(f"初始资金: {self.initial_capital:.2f}U")
|
||||
logger.info(f"最终资金: {final_capital:.2f}U")
|
||||
logger.info(f"总盈亏: {total_pnl:.2f}U")
|
||||
logger.info(f"总手续费: {total_fee:.2f}U")
|
||||
logger.info(f"返佣已到账: {self.total_rebate_credited:.2f}U")
|
||||
logger.info(f"返佣待到账: {pending_rebate:.2f}U")
|
||||
logger.info(f"已实现净手续费: {realized_net_fee:.2f}U")
|
||||
logger.info(f"净收益: {final_capital - self.initial_capital:.2f}U")
|
||||
logger.info(f"收益率: {roi:.2f}%")
|
||||
logger.info(f"总交易次数: {total_trades}")
|
||||
logger.info(f"盈利次数: {win_trades}")
|
||||
logger.info(f"亏损次数: {loss_trades}")
|
||||
if win_trades + loss_trades > 0:
|
||||
logger.info(f"胜率: {win_trades/(win_trades+loss_trades)*100:.2f}%")
|
||||
|
||||
# 保存交易记录
|
||||
trades_df = pd.DataFrame(self.trades)
|
||||
output_dir = Path(__file__).parent / 'backtest_outputs' / 'trades'
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
output_file = output_dir / f'bb_backtest_2025_{self.timeframe}_trades.csv'
|
||||
trades_df.to_csv(output_file, index=False, encoding='utf-8-sig')
|
||||
logger.info(f"\n交易记录已保存到: {output_file}")
|
||||
|
||||
return {
|
||||
'timeframe': self.timeframe,
|
||||
'initial_capital': self.initial_capital,
|
||||
'final_capital': final_capital,
|
||||
'total_pnl': total_pnl,
|
||||
'total_fee': total_fee,
|
||||
'total_rebate_credited': self.total_rebate_credited,
|
||||
'pending_rebate': pending_rebate,
|
||||
'realized_net_fee': realized_net_fee,
|
||||
'roi': roi,
|
||||
'total_trades': total_trades,
|
||||
'win_trades': win_trades,
|
||||
'loss_trades': loss_trades,
|
||||
'win_rate': win_trades/(win_trades+loss_trades)*100 if (win_trades+loss_trades) > 0 else 0,
|
||||
'trades_file': str(output_file)
|
||||
}
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# 连接数据库
|
||||
db.connect(reuse_if_open=True)
|
||||
|
||||
try:
|
||||
results = []
|
||||
|
||||
for tf in ['1m', '3m', '5m', '15m']:
|
||||
logger.info("\n" + "="*80)
|
||||
logger.info(f"测试 {tf} 周期")
|
||||
logger.info("="*80)
|
||||
backtest = BBDelayReversalBacktest(timeframe=tf)
|
||||
result = backtest.run_backtest('2025-01-01', '2025-12-31')
|
||||
if result:
|
||||
results.append(result)
|
||||
|
||||
# 对比总结
|
||||
if len(results) > 0:
|
||||
logger.info("\n" + "="*80)
|
||||
logger.info("回测对比总结")
|
||||
logger.info("="*80)
|
||||
|
||||
for result in results:
|
||||
logger.info(f"\n【{result['timeframe']}周期】")
|
||||
logger.info(f" 收益率: {result['roi']:.2f}%")
|
||||
logger.info(f" 最终资金: {result['final_capital']:.2f}U")
|
||||
logger.info(f" 总交易次数: {result['total_trades']}")
|
||||
logger.info(f" 胜率: {result['win_rate']:.2f}%")
|
||||
logger.info(f" 净手续费: {result['realized_net_fee']:.2f}U")
|
||||
|
||||
finally:
|
||||
db.close()
|
||||
Reference in New Issue
Block a user