134 lines
5.2 KiB
Python
134 lines
5.2 KiB
Python
import csv
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from datetime import datetime, timezone
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import matplotlib.pyplot as plt
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# ---------------- 配置 ----------------
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CSV_FILE = "kline_3.csv" # CSV 文件路径
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LEVERAGE = 100
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CAPITAL = 10000
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POSITION_RATIO = 0.01
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FEE_RATE = 0.0005
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# ---------------- 读取 CSV ----------------
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data = []
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with open(CSV_FILE, 'r') as f:
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reader = csv.DictReader(f)
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for row in reader:
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ts = int(row['id'])
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dt = datetime.fromtimestamp(ts, tz=timezone.utc)
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if dt.year == 2025 and dt.month == 1:
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data.append({
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'time': dt,
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'open': float(row['open']),
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'high': float(row['high']),
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'low': float(row['low']),
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'close': float(row['close']),
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})
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# ---------------- 策略回测 ----------------
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total_profit = 0
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total_fee = 0
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trades = [] # 保存每笔交易详情
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for i in range(len(data) - 1):
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k = data[i]
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k_next = data[i + 1]
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body = abs(k['close'] - k['open'])
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upper_shadow = k['high'] - max(k['close'], k['open'])
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lower_shadow = min(k['close'], k['open']) - k['low']
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position_usdt = CAPITAL * POSITION_RATIO
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leveraged_position = position_usdt * LEVERAGE
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# ---------------- 锤子线 → 做多 ----------------
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if body != 0 and lower_shadow >= 2 * body:
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profit_raw = (k_next['close'] - k['close']) / k['close'] * leveraged_position
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fee_open = leveraged_position * FEE_RATE
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fee_close = leveraged_position * FEE_RATE
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profit_net = profit_raw - fee_open - fee_close
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total_profit += profit_raw
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total_fee += fee_open + fee_close
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trades.append({
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'方向': '多',
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'开仓时间': k['time'].strftime("%Y-%m-%d %H:%M"),
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'开仓价格': k['close'],
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'平仓时间': k_next['time'].strftime("%Y-%m-%d %H:%M"),
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'平仓价格': k_next['close'],
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'本金': position_usdt,
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'杠杆仓位': leveraged_position,
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'开仓手续费': fee_open,
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'平仓手续费': fee_close,
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'原始盈亏': profit_raw,
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'净盈亏': profit_net
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})
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# ---------------- 上吊线 → 做空 ----------------
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elif body != 0 and upper_shadow >= 2 * body:
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profit_raw = (k['close'] - k_next['close']) / k['close'] * leveraged_position
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fee_open = leveraged_position * FEE_RATE
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fee_close = leveraged_position * FEE_RATE
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profit_net = profit_raw - fee_open - fee_close
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total_profit += profit_raw
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total_fee += fee_open + fee_close
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trades.append({
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'方向': '空',
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'开仓时间': k['time'].strftime("%Y-%m-%d %H:%M"),
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'开仓价格': k['close'],
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'平仓时间': k_next['time'].strftime("%Y-%m-%d %H:%M"),
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'平仓价格': k_next['close'],
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'本金': position_usdt,
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'杠杆仓位': leveraged_position,
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'开仓手续费': fee_open,
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'平仓手续费': fee_close,
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'原始盈亏': profit_raw,
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'净盈亏': profit_net
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})
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# ---------------- 输出统计 ----------------
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print(f"1月总原始盈亏: {total_profit:.2f} USDT")
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print(f"1月总手续费: {total_fee:.2f} USDT")
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print(f"1月净盈亏: {total_profit - total_fee:.2f} USDT")
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print("\n交易明细（前10笔示例）:")
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n = 0
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for t in trades:
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if t['原始盈亏'] > 10 or t['原始盈亏'] < -10:
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print(f"{t['方向']}仓 | 开仓: {t['开仓时间']} @ {t['开仓价格']:.2f} | "
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f"平仓: {t['平仓时间']} @ {t['平仓价格']:.2f} | "
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f"本金: {t['本金']:.2f} | 杠杆仓位: {t['杠杆仓位']:.2f} | "
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f"开仓手续费: {t['开仓手续费']:.2f} | 平仓手续费: {t['平仓手续费']:.2f} | "
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f"原始盈亏: {t['原始盈亏']:.2f} | 净盈亏: {t['净盈亏']:.2f}")
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n += t['原始盈亏']
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print(n)
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# # ---------------- 绘制 K 线图 + 交易点 ----------------
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# times = [k['time'] for k in data]
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# closes = [k['close'] for k in data]
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#
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# plt.figure(figsize=(16,6))
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# plt.plot(times, closes, color='black', label='ETH 收盘价')
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#
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# for t in trades:
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# open_time = datetime.strptime(t['开仓时间'], "%Y-%m-%d %H:%M")
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# close_time = datetime.strptime(t['平仓时间'], "%Y-%m-%d %H:%M")
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# if t['方向'] == '多':
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# plt.scatter(open_time, t['开仓价格'], color='green', marker='^', s=100, label='多开' if '多开' not in plt.gca().get_legend_handles_labels()[1] else "")
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# plt.scatter(close_time, t['平仓价格'], color='red', marker='v', s=100, label='多平' if '多平' not in plt.gca().get_legend_handles_labels()[1] else "")
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# else:
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# plt.scatter(open_time, t['开仓价格'], color='red', marker='v', s=100, label='空开' if '空开' not in plt.gca().get_legend_handles_labels()[1] else "")
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# plt.scatter(close_time, t['平仓价格'], color='green', marker='^', s=100, label='空平' if '空平' not in plt.gca().get_legend_handles_labels()[1] else "")
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#
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# plt.xlabel('时间')
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# plt.ylabel('价格(USDT)')
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# plt.title('ETH 永续合约 1 月交易回测（100倍杠杆）')
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# plt.legend()
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# plt.grid(True)
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# plt.gcf().autofmt_xdate()
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# plt.show()
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