Update automonitor and add qbot_main.py

.github/scripts/run_all.sh

@@ -1,5 +1,20 @@
 #!/bin/bash
 
+###
+# @Author: Charmve [email protected]
+# @Date: 2023-01-20 23:48:48
+# @LastEditors: Charmve [email protected]
+# @LastEditTime: 2023-03-12 18:23:29
+# @FilePath: /Qbot/.github/scripts/run_all.sh
+# @Version: 1.0.1
+# @Blogs: charmve.blog.csdn.net
+# @GitHub: https://github.com/Charmve
+# @Description:
+#
+# Copyright (c) 2023 by Charmve, All Rights Reserved.
+# Licensed under the MIT License.
+###
+
 set -euo pipefail
 
 TOP_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/../../" && pwd -P)"
@@ -22,8 +37,8 @@ function parse_cmdline_args() {
       -u | --update) ;;
 
       -t | --test)
-        python "${TOP_DIR}"/qbot/bt_boll.py
-        python "${TOP_DIR}"/qbot/bt_bigger_than_EMA.py
+        python "${TOP_DIR}"/qbot/strategies/bigger_than_ema_bt.py
+        python "${TOP_DIR}"/qbot/strategies/boll_strategy_bt.py
         ;;
       -h | --help)
         usage

auto_monitor.py

@@ -62,6 +62,7 @@ def show_notification_2(title, text):
 stocks_pool = [
     {"code": "sz000063", "name": "中兴通讯", "min_threshold": "26", "max_threshold": "38"},
     {"code": "sh000016", "name": "上证50"},
+    {"coce": "601318", "name": "中国平安"},
 ]
 
 
@@ -148,5 +149,5 @@ def check(code, low, high):
         # if MacOs
         os.system(f"afplay {sounds_file}")
 
-        exit()
-    time.sleep(1)
+        #  exit()
+    time.sleep(2)

qbot/qbot.py

@@ -0,0 +1,82 @@
+'''
+Author: Charmve [email protected]
+Date: 2023-03-23 15:07:38
+LastEditors: Charmve [email protected]
+LastEditTime: 2023-03-24 02:42:20
+FilePath: /Qbot/qbot/qbot.py
+Version: 1.0.1
+Blogs: charmve.blog.csdn.net
+GitHub: https://github.com/Charmve
+Description: 
+
+Copyright (c) 2023 by Charmve, All Rights Reserved. 
+Licensed under the MIT License.
+'''
+
+import tushare as ts
+import talib
+import pandas as pd
+import numpy as np
+import time
+
+# 设置股票代码和起止日期
+# code = '600000.SH'
+code = '601318'
+start_date = '20230320'
+end_date = time.strftime('%Y%m%d',time.localtime(time.time()))
+
+def get_data(code, start="2023-02-01", end="2023-03-21"):
+    df = ts.get_k_data(code, autype="qfq", start=start, end=end)
+    df.index = pd.to_datetime(df.date)
+    df["openinterest"] = 0
+    df = df[["open", "high", "low", "close", "volume", "openinterest"]]
+    return df
+
+# 从tushare获取股票数据
+# data = ts.get_k_data(code, start=start_date, end=end_date)
+# print(data)
+
+data = get_data("600018")
+
+# 计算均线、BIAS和BOLL指标
+data['ma5'] = talib.MA(data['close'], timeperiod=5)
+data['ma10'] = talib.MA(data['close'], timeperiod=10)
+data['ma20'] = talib.MA(data['close'], timeperiod=20)
+data['bias1'] = (data['close'] - data['ma5']) / data['ma5'] * 100
+data['bias2'] = (data['close'] - data['ma10']) / data['ma10'] * 100
+data['bias3'] = (data['close'] - data['ma20']) / data['ma20'] * 100
+data['upper'], data['middle'], data['lower'] = talib.BBANDS(data['close'], timeperiod=20, nbdevup=2, nbdevdn=2, matype=0)
+data['k'], data['d'] = talib.STOCH(data['high'], data['low'], data['close'], fastk_period=9, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)
+data['rsi'] = talib.RSI(data['close'], timeperiod=14)
+
+# 初始化买卖信号
+signals = np.zeros(len(data))
+
+# 第一个策略：均线和BIAS指标信号
+condition1 = (data['ma5'] > data['ma10']) & (data['ma5'] > data['ma20']) & (data['bias1'] > data['bias2']) & (data['bias1'] > data['bias3'])
+signals += 0.2 * condition1.astype(int)
+
+# 第二个策略：股价低于BOLL线底
+condition2 = (data['close'] < data['lower'])
+signals += 0.3 * condition2.astype(int)
+
+# 第三个策略：K线上穿D线
+condition3 = (data['k'] > data['d']) & (data['k'].shift() < data['d'].shift())
+signals += 0.2 * condition3.astype(int)
+
+# 第四个策略：RSI指标信号
+condition4 = (data['rsi'] > 80) | (data['rsi'] < 20)
+signals += 0.3 * condition4.astype(int)
+
+# print("signals: ", signals)
+
+# 根据信号生成交易指令，并计算收益率
+orders = np.zeros_like(signals)
+orders[signals > 0] = 1   # 买入信号
+orders[signals < 0] = -1  # 卖出信号
+returns = np.diff(data['close']) * orders[:-1]
+
+# 输出结果
+print('Total returns:', returns.sum())
+print('Positive trades:', len(returns[returns > 0]))
+print('Negative trades:', len(returns[returns < 0]))