feat: Introduce dynamic position sizing based on market conditions and enhance trading report with grouped positions and ROI.

bot_listener.py

@@ -110,20 +110,43 @@ def start_bot():
                 )
                 return
 
-            msg_lines = ["📊 <b>模拟交易报告 (北京时间)</b>\n" + "═" * 15]
+            msg_lines = ["📊 <b>模拟交易报告</b>\n" + "═" * 20]
 
-            # 1. 活跃持仓
+            # 1. 活跃持仓 - 按目标日期分组
             if positions:
-                msg_lines.append("📌 <b>当前持仓:</b>")
+                # 按目标日期分组
-                total_pnl = 0
+                positions_by_date = {}
                 for pid, pos in positions.items():
-                    pnl_usd = pos.get("pnl_usd", 0)
+                    target_date = pos.get("target_date") or "未知日期"
-                    total_pnl += pnl_usd
+                    if target_date not in positions_by_date:
-                    icon = "🟢" if pnl_usd >= 0 else "🔴"
+                        positions_by_date[target_date] = []
-                    msg_lines.append(
+                    positions_by_date[target_date].append(pos)
-                        f"{icon} {pos['city']} {pos['option']} ({pos['side']}): {pnl_usd:+.2f}$"
+                
-                    )
+                # 按日期排序显示
-                msg_lines.append(f"<b>持仓小计: {total_pnl:+.2f}$</b>\n")
+                for target_date in sorted(positions_by_date.keys()):
+                    date_positions = positions_by_date[target_date]
+                    date_pnl = sum(p.get("pnl_usd", 0) for p in date_positions)
+                    date_icon = "📈" if date_pnl >= 0 else "📉"
+                    
+                    msg_lines.append(f"\n{date_icon} <b>【{target_date}】</b> 小计: {date_pnl:+.2f}$")
+                    msg_lines.append("─" * 18)
+                    
+                    for pos in date_positions:
+                        pnl_usd = pos.get("pnl_usd", 0)
+                        icon = "🟢" if pnl_usd >= 0 else "🔴"
+                        entry_price = pos.get("entry_price", 0)
+                        current_price = pos.get("current_price", entry_price)
+                        predicted_temp = pos.get("predicted_temp")
+                        
+                        # 格式：城市 选项 | 方向 入场→当前 | 预测温度 | 盈亏
+                        pred_text = f"预测:{predicted_temp}" if predicted_temp else ""
+                        msg_lines.append(
+                            f"{icon} {pos['city']} {pos['option']}\n"
+                            f"   {pos['side']} {entry_price}¢→{current_price}¢ {pred_text} | {pnl_usd:+.2f}$"
+                        )
+                
+                total_pnl = sum(p.get("pnl_usd", 0) for p in positions.values())
+                msg_lines.append(f"\n💰 <b>持仓总计: {total_pnl:+.2f}$</b>")
 
             # 2. 最近交易记录 (最新 5 笔)
             trades = data.get("trades", [])
@@ -132,8 +155,8 @@ def start_bot():
                 # 取末尾 5 笔交易并展示
                 recent_trades = trades[-5:]
                 for t in reversed(recent_trades):
-                    t_type = "🛒 买入" if t["type"] == "BUY" else "💰 卖出"
+                    t_type = "🛒" if t["type"] == "BUY" else "💰"
-                    t_time = t.get("time", "").split(" ")[1] # 仅显示时间
+                    t_time = t.get("time", "").split(" ")[1] if " " in t.get("time", "") else t.get("time", "")
                     msg_lines.append(
                         f"• {t_time} {t_type} {t['city']} {t['option']} ({t['price']}¢)"
                     )
@@ -142,12 +165,15 @@ def start_bot():
             if history:
                 total_trades = len(history)
                 wins = sum(1 for p in history if p.get("pnl_usd", 0) > 0)
+                total_cost = sum(p.get("cost_usd", 0) for p in history)
+                total_profit = sum(p.get("pnl_usd", 0) for p in history)
                 win_rate = (wins / total_trades) * 100 if total_trades > 0 else 0
+                roi = (total_profit / total_cost * 100) if total_cost > 0 else 0
                 msg_lines.append("\n📈 <b>历史战绩:</b>")
-                msg_lines.append(f"累计成交: {total_trades} 笔")
+                msg_lines.append(f"累计成交: {total_trades}笔 | 胜率: <b>{win_rate:.1f}%</b>")
-                msg_lines.append(f"综合胜率: <b>{win_rate:.1f}%</b>")
+                msg_lines.append(f"已投入: ${total_cost:.2f} | 盈亏: <b>{total_profit:+.2f}$</b> ({roi:+.1f}%)")
 
-            footer = "\n" + "═" * 15 + "\n" + f"💳 虚拟账户余额: <b>${balance:.2f}</b>"
+            footer = "\n" + "═" * 20 + "\n" + f"💳 账户余额: <b>${balance:.2f}</b>"
             msg_lines.append(footer)
 
             bot.reply_to(message, "\n".join(msg_lines), parse_mode="HTML")

main.py

@@ -2,6 +2,7 @@ import sys
 import time
 import os
 import json
+import re
 from datetime import datetime, timedelta
 from loguru import logger
 
@@ -311,6 +312,67 @@ def main():
                                     else int(buy_no_price * 100)
                                 )
 
+                                # --- 智能动态仓位计算 ---
+                                # 1. 获取 Open-Meteo 对目标日期的最高温预测
+                                predicted_high = None
+                                weather_supports = False
+                                daily_data = weather_data.get("open-meteo", {}).get("daily", {})
+                                if daily_data and target_date:
+                                    dates = daily_data.get("time", [])
+                                    max_temps = daily_data.get("temperature_2m_max", [])
+                                    for idx, d_str in enumerate(dates):
+                                        if target_date == d_str and idx < len(max_temps):
+                                            predicted_high = max_temps[idx]
+                                            break
+                                
+                                # 2. 判断天气预测是否支持当前方向
+                                if predicted_high is not None:
+                                    # 解析选项的温度范围 (例如 "40-41°F" 或 "32°F or below")
+                                    temp_match = re.search(r'(\d+)(?:-(\d+))?°[FC]', question)
+                                    if temp_match:
+                                        low_bound = int(temp_match.group(1))
+                                        high_bound = int(temp_match.group(2)) if temp_match.group(2) else low_bound
+                                        
+                                        # 如果买 NO，天气预测应该在这个区间之外
+                                        if trigger_side == "Buy No":
+                                            weather_supports = (predicted_high < low_bound - 2) or (predicted_high > high_bound + 2)
+                                        else:  # 买 YES
+                                            weather_supports = (low_bound - 2 <= predicted_high <= high_bound + 2)
+                                
+                                # 3. 获取成交量信息
+                                market_volume = market.get("volume", 0)
+                                if isinstance(market_volume, str):
+                                    try:
+                                        market_volume = float(market_volume.replace("$", "").replace(",", ""))
+                                    except:
+                                        market_volume = 0
+                                high_volume = market_volume >= 5000  # $5000+ 算高成交量
+                                
+                                # 4. 动态仓位决策
+                                # 条件: 价格锁定程度 + 天气支持 + 成交量
+                                if trigger_price >= 90 and weather_supports and high_volume:
+                                    # 三重确认：重注
+                                    amount_usd = 10.0
+                                    confidence_tag = "🔥高置信"
+                                elif trigger_price >= 90 and weather_supports:
+                                    # 双重确认：中等仓位
+                                    amount_usd = 7.0
+                                    confidence_tag = "⭐中置信"
+                                elif trigger_price >= 92:
+                                    # 价格接近锁定，即使其他条件不满足也小额参与
+                                    amount_usd = 5.0
+                                    confidence_tag = "📌价格锁定"
+                                else:
+                                    # 普通信号：最小仓位
+                                    amount_usd = 3.0
+                                    confidence_tag = "💡试探"
+                                
+                                logger.info(
+                                    f"【仓位决策】{city} {question} | "
+                                    f"价格:{trigger_price}¢ | 预测:{predicted_high} | 天气支持:{weather_supports} | "
+                                    f"高量:{high_volume} | 仓位:${amount_usd} ({confidence_tag})"
+                                )
+
                                 # --- 模拟交易触发逻辑 ---
                                 side = "YES" if trigger_side == "Buy Yes" else "NO"
                                 success = paper_trader.open_position(
@@ -319,15 +381,24 @@ def main():
                                     option=question,
                                     price=trigger_price,
                                     side=side,
-                                    amount_usd=5.0,
+                                    amount_usd=amount_usd,
+                                    target_date=target_date,
+                                    predicted_temp=predicted_high,
                                 )
 
+                                # 构建预测温度显示文本
+                                temp_unit = weather_data.get("open-meteo", {}).get("unit", "celsius")
+                                temp_symbol = "°F" if temp_unit == "fahrenheit" else "°C"
+                                forecast_text = f"预测:{predicted_high}{temp_symbol}" if predicted_high else "预测:N/A"
+
                                 city_alerts.append(
                                     {
                                         "type": "price",
                                         "market": f"{question} ({target_date or '今日'})",
-                                        "msg": f"{trigger_side}进入锁定区间 {trigger_price}¢",
+                                        "msg": f"{trigger_side} {trigger_price}¢ | {forecast_text}",
                                         "bought": success,
+                                        "amount": amount_usd,
+                                        "confidence": confidence_tag,
                                     }
                                 )
                                 pushed_signals[alert_key] = time.time()

src/trading/paper_trader.py

@@ -43,7 +43,7 @@ class PaperTrader:
                 indent=2,
             )
 
-    def open_position(self, market_id: str, city: str, option: str, price: int, side: str, amount_usd: float = 5.0):
+    def open_position(self, market_id: str, city: str, option: str, price: int, side: str, amount_usd: float = 5.0, target_date: str = None, predicted_temp: float = None):
         """
         开仓进入模拟仓位
         """
@@ -76,6 +76,8 @@ class PaperTrader:
             "pnl_usd": 0.0,
             "pnl_pct": 0.0,
             "status": "OPEN",
+            "target_date": target_date,
+            "predicted_temp": predicted_temp,
             "opened_at": (datetime.utcnow() + timedelta(hours=8)).strftime("%Y-%m-%d %H:%M:%S")
         }
         

src/utils/notifier.py

@@ -132,7 +132,13 @@ class TelegramNotifier:
         items_text = ""
         for a in alerts:
             type_icon = "⚡" if a["type"] == "price" else "🐋"
-            buy_tag = " [🛒 模拟仓已买入]" if a.get("bought") else ""
+            # 买入标签：显示金额
+            if a.get("bought"):
+                amount = a.get("amount", 5.0)
+                confidence = a.get("confidence", "")
+                buy_tag = f" [🛒 ${amount} {confidence}]"
+            else:
+                buy_tag = ""
             items_text += f"{type_icon} <b>{a['market']}</b>: {a['msg']}{buy_tag}\n"
 
         text = (