From df2117afe822045ae79f3982eb04ef841d97a63f Mon Sep 17 00:00:00 2001
From: "2569718930@qq.com" <2569718930@qq.com>
Date: Fri, 6 Feb 2026 20:11:01 +0800
Subject: [PATCH] feat: Introduce dynamic position sizing based on market
conditions and enhance trading report with grouped positions and ROI.
---
bot_listener.py | 58 ++++++++++++++++++++--------
main.py | 75 ++++++++++++++++++++++++++++++++++++-
src/trading/paper_trader.py | 4 +-
src/utils/notifier.py | 8 +++-
4 files changed, 125 insertions(+), 20 deletions(-)
diff --git a/bot_listener.py b/bot_listener.py
index 35f27530..c649b3db 100644
--- a/bot_listener.py
+++ b/bot_listener.py
@@ -110,20 +110,43 @@ def start_bot():
)
return
- msg_lines = ["📊 模拟交易报告 (北京时间)\n" + "═" * 15]
+ msg_lines = ["📊 模拟交易报告\n" + "═" * 20]
- # 1. 活跃持仓
+ # 1. 活跃持仓 - 按目标日期分组
if positions:
- msg_lines.append("📌 当前持仓:")
- total_pnl = 0
+ # 按目标日期分组
+ positions_by_date = {}
for pid, pos in positions.items():
- pnl_usd = pos.get("pnl_usd", 0)
- total_pnl += pnl_usd
- icon = "🟢" if pnl_usd >= 0 else "🔴"
- msg_lines.append(
- f"{icon} {pos['city']} {pos['option']} ({pos['side']}): {pnl_usd:+.2f}$"
- )
- msg_lines.append(f"持仓小计: {total_pnl:+.2f}$\n")
+ target_date = pos.get("target_date") or "未知日期"
+ if target_date not in positions_by_date:
+ positions_by_date[target_date] = []
+ positions_by_date[target_date].append(pos)
+
+ # 按日期排序显示
+ 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} 【{target_date}】 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💰 持仓总计: {total_pnl:+.2f}$")
# 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_time = t.get("time", "").split(" ")[1] # 仅显示时间
+ t_type = "🛒" if t["type"] == "BUY" else "💰"
+ 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📈 历史战绩:")
- msg_lines.append(f"累计成交: {total_trades} 笔")
- msg_lines.append(f"综合胜率: {win_rate:.1f}%")
+ msg_lines.append(f"累计成交: {total_trades}笔 | 胜率: {win_rate:.1f}%")
+ msg_lines.append(f"已投入: ${total_cost:.2f} | 盈亏: {total_profit:+.2f}$ ({roi:+.1f}%)")
- footer = "\n" + "═" * 15 + "\n" + f"💳 虚拟账户余额: ${balance:.2f}"
+ footer = "\n" + "═" * 20 + "\n" + f"💳 账户余额: ${balance:.2f}"
msg_lines.append(footer)
bot.reply_to(message, "\n".join(msg_lines), parse_mode="HTML")
diff --git a/main.py b/main.py
index f4f297ad..e0197fde 100644
--- a/main.py
+++ b/main.py
@@ -2,6 +2,7 @@ import sys
import time
import os
import json
+import re
from datetime import datetime, timedelta
from loguru import logger
@@ -311,6 +312,67 @@ def main():
else int(buy_no_price * 100)
)
+ # --- 智能动态仓位计算 ---
+ # 1. 获取 Open-Meteo 对目标日期的最高温预测
+ predicted_high = None
+ weather_supports = False
+ daily_data = weather_data.get("open-meteo", {}).get("daily", {})
+ if daily_data and target_date:
+ dates = daily_data.get("time", [])
+ max_temps = daily_data.get("temperature_2m_max", [])
+ for idx, d_str in enumerate(dates):
+ if target_date == d_str and idx < len(max_temps):
+ predicted_high = max_temps[idx]
+ break
+
+ # 2. 判断天气预测是否支持当前方向
+ if predicted_high is not None:
+ # 解析选项的温度范围 (例如 "40-41°F" 或 "32°F or below")
+ temp_match = re.search(r'(\d+)(?:-(\d+))?°[FC]', question)
+ if temp_match:
+ low_bound = int(temp_match.group(1))
+ high_bound = int(temp_match.group(2)) if temp_match.group(2) else low_bound
+
+ # 如果买 NO，天气预测应该在这个区间之外
+ if trigger_side == "Buy No":
+ weather_supports = (predicted_high < low_bound - 2) or (predicted_high > high_bound + 2)
+ else: # 买 YES
+ weather_supports = (low_bound - 2 <= predicted_high <= high_bound + 2)
+
+ # 3. 获取成交量信息
+ market_volume = market.get("volume", 0)
+ if isinstance(market_volume, str):
+ try:
+ market_volume = float(market_volume.replace("$", "").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()
diff --git a/src/trading/paper_trader.py b/src/trading/paper_trader.py
index 53989317..386bf6e4 100644
--- a/src/trading/paper_trader.py
+++ b/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")
}
diff --git a/src/utils/notifier.py b/src/utils/notifier.py
index a855596f..f215090a 100644
--- a/src/utils/notifier.py
+++ b/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} {a['market']}: {a['msg']}{buy_tag}\n"
text = (