添加 cat-fly 自动化交易报告系统

新增文件:
- cat-fly/auto_report.py: 自动化交易报告系统（独立版）

功能:
1. 自动获取近2个月创业板50指数30分钟K线数据
2. 运行多空双向策略回测
3. 生成详细HTML/文本交易报告
4. 支持邮件推送报告

策略参数:
- 仓位: 100%
- 止损: 0.8%
- 止盈: 2.0%
- 最大持仓: 16周期(8小时)
- 信号强度: 3个指标确认

定时任务:
- 已设置10个定时任务（工作日A股开盘时间每半小时）
- 上午: 9:30, 10:00, 10:30, 11:00, 11:30
- 下午: 13:00, 13:30, 14:00, 14:30, 15:00

使用说明:
1. 修改 auto_report.py 中的 EMAIL_CONFIG 配置
2. 手动运行: python cat-fly/auto_report.py
3. 定时任务会自动执行并发送邮件

cat-fly/auto_report.py

@@ -0,0 +1,566 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+创业板50指数 - 自动化交易报告系统 (独立版)
+功能：
+1. 获取近2个月数据
+2. 运行策略回测
+3. 生成详细报告
+4. 发送邮件通知
+
+执行频率：A股开盘时间每半小时（9:30-11:30, 13:00-15:00）
+"""
+
+import pandas as pd
+import numpy as np
+import akshare as ak
+import warnings
+import os
+import smtplib
+import ssl
+from datetime import datetime, timedelta
+from email.mime.text import MIMEText
+from email.mime.multipart import MIMEMultipart
+from email.header import Header
+warnings.filterwarnings('ignore')
+
+# ==================== 邮件配置 ====================
+# 请修改以下配置为你的邮箱信息
+EMAIL_CONFIG = {
+    "smtp_server": "smtp.qq.com",      # SMTP服务器
+    "smtp_port": 465,                   # SMTP端口
+    "sender_email": "your_email@qq.com", # 发件人邮箱
+    "sender_password": "your_auth_code",  # 邮箱授权码（不是登录密码）
+    "receiver_email": "your_email@qq.com" # 收件人邮箱
+}
+
+def send_email(subject, html_content, text_content=""):
+    """发送邮件"""
+    try:
+        msg = MIMEMultipart('alternative')
+        msg['Subject'] = Header(subject, 'utf-8')
+        msg['From'] = EMAIL_CONFIG['sender_email']
+        msg['To'] = EMAIL_CONFIG['receiver_email']
+        
+        # 纯文本版本
+        text_part = MIMEText(text_content, 'plain', 'utf-8')
+        msg.attach(text_part)
+        
+        # HTML版本
+        html_part = MIMEText(html_content, 'html', 'utf-8')
+        msg.attach(html_part)
+        
+        # 发送邮件
+        context = ssl.create_default_context()
+        with smtplib.SMTP_SSL(EMAIL_CONFIG['smtp_server'], EMAIL_CONFIG['smtp_port'], context=context) as server:
+            server.login(EMAIL_CONFIG['sender_email'], EMAIL_CONFIG['sender_password'])
+            server.sendmail(
+                EMAIL_CONFIG['sender_email'],
+                EMAIL_CONFIG['receiver_email'],
+                msg.as_string()
+            )
+        print(f"✅ 邮件发送成功: {subject}")
+        return True
+    except Exception as e:
+        print(f"❌ 邮件发送失败: {e}")
+        print(f"   请检查EMAIL_CONFIG配置是否正确")
+        return False
+
+
+# ==================== 数据获取 ====================
+class DataFetcher:
+    """数据获取类"""
+    
+    @staticmethod
+    def fetch_recent_2months():
+        """获取近2个月数据"""
+        end_date = datetime.now()
+        start_date = end_date - timedelta(days=70)  # 2个月+10天缓冲
+        
+        print(f"获取数据: {start_date.strftime('%Y-%m-%d')} 至 {end_date.strftime('%Y-%m-%d')}")
+        
+        try:
+            # 使用akshare获取30分钟K线
+            df = ak.index_zh_a_hist_min_em(
+                symbol="399673",
+                period="30",
+                start_date=start_date.strftime('%Y%m%d%H%M%S'),
+                end_date=end_date.strftime('%Y%m%d%H%M%S')
+            )
+            
+            if df is None or len(df) == 0:
+                print("❌ 未获取到数据")
+                return None
+            
+            # 标准化列名
+            df = df.rename(columns={
+                '时间': 'datetime',
+                '开盘': 'open',
+                '收盘': 'close',
+                '最高': 'high',
+                '最低': 'low',
+                '成交量': 'volume'
+            })
+            
+            df['datetime'] = pd.to_datetime(df['datetime'])
+            df = df.set_index('datetime').sort_index()
+            
+            # 只保留最近2个月的数据用于回测
+            backtest_start = end_date - timedelta(days=60)
+            df_backtest = df[df.index >= backtest_start]
+            
+            print(f"✅ 数据获取成功: 共{len(df_backtest)}条30分钟K线")
+            print(f"   数据区间: {df_backtest.index[0]} 至 {df_backtest.index[-1]}")
+            
+            return df_backtest
+            
+        except Exception as e:
+            print(f"❌ 数据获取失败: {e}")
+            return None
+
+
+# ==================== 策略类 ====================
+class CatFlyStrategy:
+    """cat-fly策略简化版 - 基于30分钟K线"""
+    
+    def __init__(self, config=None):
+        self.config = config or {
+            'initial_capital': 1000000,
+            'position_size_pct': 1.0,
+            'stop_loss_pct': 0.008,
+            'take_profit_pct': 0.02,
+            'max_hold_bars': 16,
+            'min_signal_strength': 3
+        }
+        self.initial_capital = self.config['initial_capital']
+    
+    def calculate_indicators(self, df):
+        """计算技术指标"""
+        # RSI
+        delta = df['close'].diff()
+        gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
+        loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
+        rs = gain / loss
+        df['RSI'] = 100 - (100 / (1 + rs))
+        
+        # 移动平均线
+        df['MA5'] = df['close'].rolling(5).mean()
+        df['MA20'] = df['close'].rolling(20).mean()
+        df['MA60'] = df['close'].rolling(60).mean()
+        
+        # 布林带
+        df['BB_middle'] = df['close'].rolling(20).mean()
+        bb_std = df['close'].rolling(20).std()
+        df['BB_upper'] = df['BB_middle'] + 2 * bb_std
+        df['BB_lower'] = df['BB_middle'] - 2 * bb_std
+        
+        # MACD
+        ema12 = df['close'].ewm(span=12).mean()
+        ema26 = df['close'].ewm(span=26).mean()
+        df['MACD'] = ema12 - ema26
+        df['MACD_signal'] = df['MACD'].ewm(span=9).mean()
+        
+        return df
+    
+    def generate_signals(self, df):
+        """生成交易信号"""
+        df = self.calculate_indicators(df)
+        df['signal'] = 0
+        df['signal_strength'] = 0
+        
+        for i in range(60, len(df)):
+            row = df.iloc[i]
+            strength = 0
+            
+            # RSI超卖/超买
+            if row['RSI'] < 30:
+                strength += 1
+            elif row['RSI'] > 70:
+                strength -= 1
+            
+            # 均线多头排列/空头排列
+            if row['close'] > row['MA5'] > row['MA20']:
+                strength += 1
+            elif row['close'] < row['MA5'] < row['MA20']:
+                strength -= 1
+            
+            # 布林带
+            if row['close'] < row['BB_lower']:
+                strength += 1
+            elif row['close'] > row['BB_upper']:
+                strength -= 1
+            
+            # MACD金叉/死叉
+            if i > 0:
+                prev_macd = df['MACD'].iloc[i-1]
+                prev_signal = df['MACD_signal'].iloc[i-1]
+                curr_macd = row['MACD']
+                curr_signal_line = row['MACD_signal']
+                
+                if prev_macd < prev_signal and curr_macd > curr_signal_line:
+                    strength += 1
+                elif prev_macd > prev_signal and curr_macd < curr_signal_line:
+                    strength -= 1
+            
+            df.iloc[i, df.columns.get_loc('signal_strength')] = strength
+            
+            # 生成交易信号
+            if strength >= self.config['min_signal_strength']:
+                df.iloc[i, df.columns.get_loc('signal')] = 1  # 做多
+            elif strength <= -self.config['min_signal_strength']:
+                df.iloc[i, df.columns.get_loc('signal')] = -1  # 做空
+        
+        return df
+    
+    def backtest(self, df):
+        """回测"""
+        df = self.generate_signals(df)
+        
+        trades = []
+        capital = self.initial_capital
+        position = 0
+        entry_price = 0
+        entry_time = None
+        holding_bars = 0
+        
+        for i in range(60, len(df)):
+            current_bar = df.iloc[i]
+            price = current_bar['close']
+            current_time = current_bar.name
+            
+            # 无持仓时检查开仓信号
+            if position == 0:
+                if current_bar['signal'] == 1:  # 做多
+                    position_size = int(capital * self.config['position_size_pct'] / price)
+                    if position_size > 0:
+                        position = position_size
+                        entry_price = price
+                        entry_time = current_time
+                        holding_bars = 0
+                        
+                elif current_bar['signal'] == -1:  # 做空
+                    position_size = int(capital * self.config['position_size_pct'] / price)
+                    if position_size > 0:
+                        position = -position_size
+                        entry_price = price
+                        entry_time = current_time
+                        holding_bars = 0
+            
+            # 有持仓时检查平仓
+            else:
+                holding_bars += 1
+                exit_signal = False
+                exit_reason = ""
+                
+                if position > 0:  # 做多持仓
+                    if price <= entry_price * (1 - self.config['stop_loss_pct']):
+                        exit_signal = True
+                        exit_reason = "止损"
+                    elif price >= entry_price * (1 + self.config['take_profit_pct']):
+                        exit_signal = True
+                        exit_reason = "止盈"
+                    elif holding_bars >= self.config['max_hold_bars']:
+                        exit_signal = True
+                        exit_reason = "时间止损"
+                    elif current_bar['RSI'] > 70:
+                        exit_signal = True
+                        exit_reason = "信号消失(RSI超买)"
+                
+                else:  # 做空持仓
+                    if price >= entry_price * (1 + self.config['stop_loss_pct']):
+                        exit_signal = True
+                        exit_reason = "止损"
+                    elif price <= entry_price * (1 - self.config['take_profit_pct']):
+                        exit_signal = True
+                        exit_reason = "止盈"
+                    elif holding_bars >= self.config['max_hold_bars']:
+                        exit_signal = True
+                        exit_reason = "时间止损"
+                    elif current_bar['RSI'] < 30:
+                        exit_signal = True
+                        exit_reason = "信号消失(RSI超卖)"
+                
+                # 执行平仓
+                if exit_signal:
+                    if position > 0:
+                        pnl = (price - entry_price) * position
+                        pnl_pct = (price - entry_price) / entry_price * 100
+                    else:
+                        pnl = (entry_price - price) * abs(position)
+                        pnl_pct = (entry_price - price) / entry_price * 100
+                    
+                    capital += pnl
+                    
+                    trades.append({
+                        '方向': '做多' if position > 0 else '做空',
+                        '开仓时间': entry_time,
+                        '平仓时间': current_time,
+                        '开仓价': entry_price,
+                        '平仓价': price,
+                        '持仓数量': abs(position),
+                        '盈亏金额': pnl,
+                        '盈亏百分比': pnl_pct,
+                        '退出原因': exit_reason,
+                        '持仓周期': holding_bars,
+                        '平仓后资金': capital
+                    })
+                    
+                    position = 0
+                    entry_price = 0
+                    entry_time = None
+                    holding_bars = 0
+        
+        return df, pd.DataFrame(trades), capital
+
+
+# ==================== 报告生成 ====================
+def generate_report(trades_df, final_capital, initial_capital=1000000):
+    """生成详细报告"""
+    
+    if len(trades_df) == 0:
+        html = "<html><body><h1>创业板50交易报告</h1><p>近2个月无交易信号</p></body></html>"
+        text = "近2个月无交易信号"
+        return html, text
+    
+    total_return = (final_capital - initial_capital) / initial_capital * 100
+    total_trades = len(trades_df)
+    winning_trades = trades_df[trades_df['盈亏金额'] > 0]
+    losing_trades = trades_df[trades_df['盈亏金额'] < 0]
+    
+    win_rate = len(winning_trades) / total_trades * 100 if total_trades > 0 else 0
+    avg_profit = winning_trades['盈亏金额'].mean() if len(winning_trades) > 0 else 0
+    avg_loss = losing_trades['盈亏金额'].mean() if len(losing_trades) > 0 else 0
+    
+    total_profit = winning_trades['盈亏金额'].sum() if len(winning_trades) > 0 else 0
+    total_loss = abs(losing_trades['盈亏金额'].sum()) if len(losing_trades) > 0 else 0
+    profit_factor = total_profit / total_loss if total_loss > 0 else 0
+    
+    max_profit = trades_df['盈亏金额'].max()
+    max_loss = trades_df['盈亏金额'].min()
+    avg_hold_time = trades_df['持仓周期'].mean()
+    
+    long_trades = trades_df[trades_df['方向'] == '做多']
+    short_trades = trades_df[trades_df['方向'] == '做空']
+    exit_reasons = trades_df['退出原因'].value_counts()
+    
+    # 生成HTML报告
+    html = f"""
+    <html>
+    <head>
+        <style>
+            body {{ font-family: Arial, sans-serif; margin: 20px; }}
+            h1 {{ color: #333; border-bottom: 2px solid #007bff; padding-bottom: 10px; }}
+            h2 {{ color: #555; margin-top: 30px; }}
+            table {{ border-collapse: collapse; width: 100%; margin: 15px 0; font-size: 14px; }}
+            th, td {{ border: 1px solid #ddd; padding: 8px; text-align: left; }}
+            th {{ background-color: #007bff; color: white; }}
+            tr:nth-child(even) {{ background-color: #f2f2f2; }}
+            .positive {{ color: green; font-weight: bold; }}
+            .negative {{ color: red; font-weight: bold; }}
+            .summary {{ background-color: #f8f9fa; padding: 15px; border-radius: 5px; margin: 15px 0; }}
+        </style>
+    </head>
+    <body>
+        <h1>🚀 创业板50指数交易报告</h1>
+        <p>生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}</p>
+        <p>数据区间: 近2个月</p>
+        
+        <div class="summary">
+            <h2>📊 总体绩效</h2>
+            <table>
+                <tr><th>指标</th><th>数值</th></tr>
+                <tr><td>初始资金</td><td>{initial_capital:,.0f}元</td></tr>
+                <tr><td>最终资金</td><td>{final_capital:,.0f}元</td></tr>
+                <tr><td>总收益率</td><td class="{'positive' if total_return >= 0 else 'negative'}">{total_return:+.2f}%</td></tr>
+                <tr><td>总交易次数</td><td>{total_trades}笔</td></tr>
+                <tr><td>胜率</td><td>{win_rate:.1f}%</td></tr>
+                <tr><td>盈亏比</td><td>{profit_factor:.2f}</td></tr>
+                <tr><td>平均持仓时间</td><td>{avg_hold_time:.1f}周期 ({avg_hold_time*0.5:.1f}小时)</td></tr>
+            </table>
+        </div>
+        
+        <h2>📈 盈亏统计</h2>
+        <table>
+            <tr><th>指标</th><th>数值</th></tr>
+            <tr><td>总盈利</td><td class="positive">+{total_profit:,.0f}元</td></tr>
+            <tr><td>总亏损</td><td class="negative">-{total_loss:,.0f}元</td></tr>
+            <tr><td>平均盈利</td><td class="positive">+{avg_profit:,.0f}元</td></tr>
+            <tr><td>平均亏损</td><td class="negative">{avg_loss:,.0f}元</td></tr>
+            <tr><td>最大单笔盈利</td><td class="positive">+{max_profit:,.0f}元</td></tr>
+            <tr><td>最大单笔亏损</td><td class="negative">{max_loss:,.0f}元</td></tr>
+        </table>
+        
+        <h2>🔄 多空统计</h2>
+        <table>
+            <tr><th>方向</th><th>交易次数</th><th>胜率</th><th>总盈亏</th></tr>
+            <tr>
+                <td>做多</td>
+                <td>{len(long_trades)}笔</td>
+                <td>{(len(long_trades[long_trades['盈亏金额']>0])/len(long_trades)*100 if len(long_trades)>0 else 0):.1f}%</td>
+                <td class="{'positive' if long_trades['盈亏金额'].sum() >= 0 else 'negative'}">{long_trades['盈亏金额'].sum():+,.0f}元</td>
+            </tr>
+            <tr>
+                <td>做空</td>
+                <td>{len(short_trades)}笔</td>
+                <td>{(len(short_trades[short_trades['盈亏金额']>0])/len(short_trades)*100 if len(short_trades)>0 else 0):.1f}%</td>
+                <td class="{'positive' if short_trades['盈亏金额'].sum() >= 0 else 'negative'}">{short_trades['盈亏金额'].sum():+,.0f}元</td>
+            </tr>
+        </table>
+        
+        <h2>🚪 退出原因分析</h2>
+        <table>
+            <tr><th>退出原因</th><th>次数</th><th>占比</th></tr>
+    """
+    
+    for reason, count in exit_reasons.items():
+        pct = count / total_trades * 100
+        html += f"<tr><td>{reason}</td><td>{count}</td><td>{pct:.1f}%</td></tr>"
+    
+    html += """
+        </table>
+        
+        <h2>📝 最近10笔交易明细</h2>
+        <table>
+            <tr>
+                <th>方向</th>
+                <th>开仓时间</th>
+                <th>平仓时间</th>
+                <th>开仓价</th>
+                <th>平仓价</th>
+                <th>盈亏金额</th>
+                <th>盈亏%</th>
+                <th>退出原因</th>
+            </tr>
+    """
+    
+    recent_trades = trades_df.tail(10)
+    for _, trade in recent_trades.iterrows():
+        pnl_class = "positive" if trade['盈亏金额'] >= 0 else "negative"
+        html += f"""
+            <tr>
+                <td>{trade['方向']}</td>
+                <td>{trade['开仓时间']}</td>
+                <td>{trade['平仓时间']}</td>
+                <td>{trade['开仓价']:.2f}</td>
+                <td>{trade['平仓价']:.2f}</td>
+                <td class="{pnl_class}">{trade['盈亏金额']:+.0f}</td>
+                <td class="{pnl_class}">{trade['盈亏百分比']:+.2f}%</td>
+                <td>{trade['退出原因']}</td>
+            </tr>
+        """
+    
+    html += """
+        </table>
+        
+        <hr>
+        <p style="color: #666; font-size: 12px;">
+            本报告由 cat-fly 自动交易系统生成 | 策略：30分钟K线多空双向<br>
+            风险提示：历史回测不代表未来表现，投资有风险，入市需谨慎。
+        </p>
+    </body>
+    </html>
+    """
+    
+    # 生成纯文本版本
+    text = f"""
+创业板50指数交易报告
+生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
+数据区间: 近2个月
+
+【总体绩效】
+初始资金: {initial_capital:,.0f}元
+最终资金: {final_capital:,.0f}元
+总收益率: {total_return:+.2f}%
+总交易次数: {total_trades}笔
+胜率: {win_rate:.1f}%
+盈亏比: {profit_factor:.2f}
+平均持仓: {avg_hold_time*0.5:.1f}小时
+
+【盈亏统计】
+总盈利: +{total_profit:,.0f}元
+总亏损: -{total_loss:,.0f}元
+最大单笔盈利: +{max_profit:,.0f}元
+最大单笔亏损: {max_loss:,.0f}元
+
+【多空统计】
+做多: {len(long_trades)}笔, 盈亏{long_trades['盈亏金额'].sum():+,.0f}元
+做空: {len(short_trades)}笔, 盈亏{short_trades['盈亏金额'].sum():+,.0f}元
+
+【退出原因】
+{exit_reasons.to_string()}
+
+【最近5笔交易】
+{trades_df.tail(5)[['方向', '开仓时间', '平仓时间', '盈亏金额', '退出原因']].to_string(index=False)}
+    """
+    
+    return html, text
+
+
+# ==================== 主程序 ====================
+def main():
+    """主程序"""
+    print("="*80)
+    print("🚀 cat-fly 自动交易报告系统")
+    print("="*80)
+    print(f"执行时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
+    
+    # 检查是否在交易时间（可选）
+    now = datetime.now()
+    hour = now.hour
+    minute = now.minute
+    time_str = f"{hour:02d}:{minute:02d}"
+    
+    # A股交易时间检查
+    is_trading_time = False
+    if (9 <= hour <= 11) or (13 <= hour <= 15):
+        if hour == 9 and minute < 30:
+            is_trading_time = False
+        elif hour == 11 and minute > 30:
+            is_trading_time = False
+        elif hour == 15 and minute > 0:
+            is_trading_time = False
+        else:
+            is_trading_time = True
+    
+    print(f"当前时间: {time_str}")
+    print(f"交易时间: {'是' if is_trading_time else '否（非交易时间也会执行）'}")
+    
+    # 1. 获取近2个月数据
+    print("\n📊 步骤1: 获取近2个月数据...")
+    df = DataFetcher.fetch_recent_2months()
+    if df is None:
+        print("❌ 数据获取失败，退出")
+        return
+    
+    # 2. 运行策略
+    print("\n📈 步骤2: 运行策略回测...")
+    strategy = CatFlyStrategy()
+    df, trades_df, final_capital = strategy.backtest(df)
+    
+    print(f"✅ 回测完成: 共{len(trades_df)}笔交易")
+    print(f"   最终资金: {final_capital:,.0f}元")
+    print(f"   收益率: {(final_capital/1000000-1)*100:+.2f}%")
+    
+    # 3. 生成报告
+    print("\n📝 步骤3: 生成报告...")
+    html_report, text_report = generate_report(trades_df, final_capital)
+    
+    # 4. 发送邮件
+    print("\n📧 步骤4: 发送邮件...")
+    subject = f"🚀 创业板50交易报告 {datetime.now().strftime('%m-%d %H:%M')} | 收益{(final_capital/1000000-1)*100:+.2f}%"
+    
+    # 检查邮件配置
+    if EMAIL_CONFIG['sender_email'] == 'your_email@qq.com':
+        print("⚠️ 警告: 请先修改 EMAIL_CONFIG 中的邮箱配置！")
+        print("   配置文件位于脚本开头的 EMAIL_CONFIG 字典")
+        print("\n📋 报告预览（前500字符）:")
+        print(text_report[:500])
+    else:
+        send_email(subject, html_report, text_report)
+    
+    print("\n✅ 全部完成!")
+    print("="*80)
+
+
+if __name__ == "__main__":
+    main()