{"id":1615,"date":"2024-11-10T07:20:00","date_gmt":"2024-11-09T23:20:00","guid":{"rendered":"https:\/\/blog.laoyulaoyu.top\/?p=1615"},"modified":"2024-10-16T16:20:01","modified_gmt":"2024-10-16T08:20:01","slug":"%e7%b2%be%e5%87%86%e6%b4%9e%e5%af%9f%e8%82%a1%e5%b8%82%e7%9a%84%e5%bf%83%e8%b7%b3%e5%92%8c%e8%a1%80%e5%8e%8b%ef%bc%8c%e5%8a%a9%e6%82%a8%e4%ba%a4%e6%98%93%e5%86%b3","status":"publish","type":"post","link":"https:\/\/laoyulaoyu.com\/index.php\/2024\/11\/10\/%e7%b2%be%e5%87%86%e6%b4%9e%e5%af%9f%e8%82%a1%e5%b8%82%e7%9a%84%e5%bf%83%e8%b7%b3%e5%92%8c%e8%a1%80%e5%8e%8b%ef%bc%8c%e5%8a%a9%e6%82%a8%e4%ba%a4%e6%98%93%e5%86%b3\/","title":{"rendered":"\u7cbe\u51c6\u6d1e\u5bdf\u80a1\u5e02\u7684\u201c\u5fc3\u8df3\u201d\u548c\u201c\u8840\u538b\u201d\uff0c\u52a9\u60a8\u4ea4\u6613\u51b3\u7b56\u65e0\u5f80\u4e0d\u5229"},"content":{"rendered":"\n

\u4f5c\u8005\uff1a\u8001\u4f59\u635e\u9c7c<\/a><\/p>\n\n\n\n

\u539f\u521b\u4e0d\u6613\uff0c\u8f6c\u8f7d\u8bf7\u6807\u660e\u51fa\u5904\u53ca\u539f\u4f5c\u8005\u3002<\/mark><\/strong><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
\n
\u5199\u5728\u524d\u9762\u7684\u8bdd\uff1a<\/strong>\u6211\u4e4b\u524d\u5199\u8fc7\u4e00\u7bc7\u300a\u795e\u5947\u7684 VROC \u529b\u91cf\uff0c\u8ba9\u4f60\u654f\u9510\u611f\u77e5\u80a1\u5e02\u7684\u5fc3\u8df3\u8282\u594f\u300b\uff0c\u628a VROC\uff08\u6210\u4ea4\u91cf\u53d8\u5316\u7387\uff09\u6bd4\u4f5c\u5e02\u573a\u7684\u5fc3\u8df3\u3002\u90a3\u4e48\uff0cRSI\uff08\u76f8\u5bf9\u5f3a\u5f31\u6307\u6570\uff09\u5c31\u53ef\u4ee5\u770b\u4f5c\u662f\u5e02\u573a\u7684\u8840\u538b\u6307\u6570\u3002\u4eca\u5929\u6211\u51c6\u5907\u548c\u5927\u5bb6\u804a\u804a\u5982\u4f55\u53c2\u8003 VROC\uff08\u4ea4\u6613\u91cf\u53d8\u5316\u7387\uff09\u548c RSI\uff08\u76f8\u5bf9\u5f3a\u5f31\u6307\u6570\uff09\u8fd9\u4e24\u4e2a\u6307\u6807\u6765\u8fdb\u884c\u65e5\u5185\u4ea4\u6613<\/mark>\uff0c\u5e76\u4e14\u4f1a\u50cf\u4e4b\u524d\u4e00\u6837\uff0c\u7ed9\u5927\u5bb6\u63d0\u4f9b\u4e00\u4e2a\u4ee3\u7801\u7ea7\u7684\u4ea4\u6613\u4eea\u8868\u677f\uff0c\u7528\u6765\u5b9e\u4f8b\u5206\u6790\u80a1\u5e02\u6307\u6570\u524d 50 \u80a1\u7968\u7684\u4ea4\u6613\u6570\u636e\u3002<\/pre>\n<\/blockquote>\n\n\n\n
<\/p>\n\n\n\n
\u4e00\u3001\u4ec0\u4e48\u662f VROC \u548c RSI\uff1f<\/strong>
<\/h2>\n\n\n\n
1.1 VROC ( \u4ea4\u6613\u91cf\u53d8\u5316\u7387)<\/strong><\/h3>\n\n\n\n
VROC\uff08Volume Rate of Change\uff09\uff0c\u8be5\u6307\u6807\u8861\u91cf\u7279\u5b9a\u65f6\u671f\u5185\u4ea4\u6613\u91cf\u7684\u767e\u5206\u6bd4\u53d8\u5316\u3002VROC \u4e0a\u5347\u53ef\u80fd\u9884\u793a\u7740\u5bf9\u67d0\u53ea\u80a1\u7968\u7684\u5174\u8da3\u5728\u589e\u52a0\uff0c\u53cd\u6620\u4e86\u5e02\u573a\u6d3b\u8dc3\u5ea6\u7684\u53d8\u5316\uff0c\u6709\u52a9\u4e8e\u4ea4\u6613\u8005\u8bc6\u522b\u6210\u4ea4\u91cf\u7a81\u7136\u589e\u52a0\u6216\u51cf\u5c11\u7684\u60c5\u51b5\uff0c\u8fd9\u4e9b\u53d8\u5316\u5f80\u5f80\u9884\u793a\u7740\u6f5c\u5728\u7684\u4ef7\u683c\u53d8\u52a8\u3002\u5f53\u6210\u4ea4\u91cf\u5feb\u901f\u53d8\u5316\u65f6\uff0c\u5c31\u53ef\u80fd\u6709\u5927\u4e8b\u53d1\u751f\u3002<\/p>\n\n\n\n
\u66f4\u591a\u7684 VROC \u4ecb\u7ecd\u770b\u8fd9\u7bc7\uff1a\u300a\u795e\u5947\u7684 VROC \u529b\u91cf\uff0c\u8ba9\u4f60\u654f\u9510\u611f\u77e5\u80a1\u5e02\u7684\u5fc3\u8df3\u8282\u594f\u300b<\/p>\n\n\n\n
1.2 RSI (\u76f8\u5bf9\u5f3a\u5f31\u6307\u6570)<\/strong><\/h3>\n\n\n\n
RSI\uff08Relative Strength Index\uff09\uff0c\u4e00\u79cd\u6280\u672f\u5206\u6790\u5de5\u5177\uff0c\u4e3b\u8981\u7528\u4e8e\u8bc4\u4f30\u67d0\u4e2a\u7279\u5b9a\u8d44\u4ea7\uff08\u5982\u80a1\u7968\u3001\u671f\u8d27\u3001\u5916\u6c47\u7b49\uff09\u7684\u4ef7\u683c\u6ce2\u52a8\u65b9\u5411\u548c\u5f3a\u5ea6\u3002\u8be5\u6307\u6807\u6700\u65e9\u7531\u91d1\u878d\u5206\u6790\u5e08\u5a01\u5c14\u65af\u00b7\u5a01\u5c14\u5fb7\uff08Welles Wilder\uff09\u57281978\u5e74\u63d0\u51fa\uff0c\u5e76\u5e7f\u6cdb\u5e94\u7528\u4e8e\u5404\u7c7b\u4ea4\u6613\u5e02\u573a\u4e2d\u3002<\/p>\n\n\n\n
\u8fd9\u79cd\u52a8\u91cf\u9707\u8361\u6307\u6807\u8bc4\u4f30\u4ef7\u683c\u53d8\u52a8\u7684\u901f\u5ea6\u548c\u53d8\u5316\uff0c\u6709\u52a9\u4e8e\u8bc6\u522b\u8d85\u4e70\u6216\u8d85\u5356\u60c5\u51b5<\/strong>\u3002RSI \u4f4e\u4e8e 30\uff1f\u8fd9\u53ef\u80fd\u9884\u793a\u7740\u4e00\u4e2a\u6f5c\u5728\u7684\u4e70\u5165\u4fe1\u53f7\uff0c\u800c RSI \u8d85\u8fc7 70 \u5219\u8868\u660e\u662f\u65f6\u5019\u5356\u51fa\u4e86\uff01\u8bfb\u5230\u8fd9\u91cc\uff0c\u6709\u6ca1\u6709\u4e00\u79cd\u770b\u8840\u538b\u8ba1\u7684\u611f\u89c9<\/strong>\uff0c\u9ad8\u538b70\uff0c\u4f4e\u538b30\uff0c\u8d85\u8fc7\u4e86\u5c31\u8981\u9884\u8b66\uff0c\u600e\u4e48\u6837\uff0c\u6211\u7684\u6bd4\u55bb\u8fd8\u7b97\u6070\u5f53\u5427\uff1f<\/p>\n\n\n\n
1.3 RSI \u7684\u8ba1\u7b97\u516c\u5f0f<\/strong><\/h3>\n\n\n\n
RSI = 100 \u00d7 RS \/ (1 + RS)\uff0c\u5176\u4e2dRS = N\u5929\u5185\u6536\u5e02\u4ef7\u4e0a\u6da8\u6570\u4e4b\u548c\u7684\u5e73\u5747\u503c \/ N\u5929\u5185\u6536\u5e02\u4ef7\u4e0b\u8dcc\u6570\u4e4b\u548c\u7684\u5e73\u5747\u503c\u3002\u5177\u4f53\u8ba1\u7b97\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n\n\n\n
    \n
  1. \u786e\u5b9a\u65f6\u95f4\u5468\u671fN\uff08\u598214\u5929\uff09\u3002<\/li>\n\n\n\n
  2. \u8ba1\u7b97N\u5929\u5185\u7684\u6bcf\u65e5\u6536\u76d8\u4ef7\u7684\u6da8\u8dcc\u60c5\u51b5\u3002<\/li>\n\n\n\n
  3. \u5206\u522b\u6c42\u51faN\u5929\u5185\u6536\u76d8\u4ef7\u4e0a\u6da8\u6570\u4e4b\u548c\u7684\u5e73\u5747\u503c(A)\u548c\u6536\u76d8\u4ef7\u4e0b\u8dcc\u6570\u4e4b\u548c\u7684\u5e73\u5747\u503c(B)\u3002<\/li>\n\n\n\n
  4. \u4ee3\u5165\u516c\u5f0f\u8ba1\u7b97RSI\u503c\u3002<\/li>\n<\/ol>\n\n\n\n
    1.4 RSI \u5e94\u7528\u4e0e\u89e3\u8bfb<\/strong><\/h3>\n\n\n\n
      \n
    1. \u8d85\u4e70\u4e0e\u8d85\u5356\uff1a<\/strong>\u901a\u5e38\uff0cRSI\u503c\u8d85\u8fc770\u88ab\u8ba4\u4e3a\u5e02\u573a\u5904\u4e8e\u8d85\u4e70\u72b6\u6001\uff0c\u53ef\u80fd\u9762\u4e34\u56de\u8c03\u6216\u4e0b\u8dcc\u538b\u529b\uff1b\u800cRSI\u503c\u4f4e\u4e8e30\u5219\u88ab\u89c6\u4e3a\u8d85\u5356\u72b6\u6001\uff0c\u53ef\u80fd\u5373\u5c06\u51fa\u73b0\u53cd\u5f39\u6216\u4e0a\u6da8\u3002<\/li>\n\n\n\n
    2. \u8d8b\u52bf\u5224\u65ad\uff1a<\/strong>RSI\u503c\u5927\u4e8e50\u901a\u5e38\u8868\u793a\u5e02\u573a\u5904\u4e8e\u591a\u65b9\u5e02\u573a\uff08\u5373\u4e0a\u6da8\u8d8b\u52bf\uff09\uff0c\u800c\u5c0f\u4e8e50\u5219\u8868\u793a\u5e02\u573a\u5904\u4e8e\u7a7a\u65b9\u5e02\u573a\uff08\u5373\u4e0b\u8dcc\u8d8b\u52bf\uff09\u3002<\/li>\n\n\n\n
    3. \u4ea4\u53c9\u4fe1\u53f7\uff1a<\/strong>\u77ed\u671fRSI\uff08\u59826\u65e5RSI\uff09\u4e0e\u957f\u671fRSI\uff08\u598212\u65e5RSI\uff09\u7684\u4ea4\u53c9\u60c5\u51b5\u53ef\u4ee5\u63d0\u4f9b\u4ea4\u6613\u4fe1\u53f7\u3002\u5f53\u77ed\u671fRSI\u4ece\u4e0b\u5411\u4e0a\u7a81\u7834\u957f\u671fRSI\u65f6\uff0c\u89c6\u4e3a\u4e70\u5165\u4fe1\u53f7\uff1b\u53cd\u4e4b\uff0c\u4ece\u4e0a\u5411\u4e0b\u7a81\u7834\u65f6\uff0c\u5219\u4e3a\u5356\u51fa\u4fe1\u53f7\u3002<\/li>\n\n\n\n
    4. \u80cc\u79bb\u73b0\u8c61\uff1a<\/strong>\u5f53\u8d44\u4ea7\u4ef7\u683c\u7ee7\u7eed\u4e0a\u6da8\u800cRSI\u4e0d\u518d\u521b\u65b0\u9ad8\uff0c\u6216\u4ef7\u683c\u7ee7\u7eed\u4e0b\u8dcc\u800cRSI\u4e0d\u518d\u521b\u65b0\u4f4e\u65f6\uff0c\u8fd9\u79cd\u80cc\u79bb\u73b0\u8c61\u53ef\u80fd\u9884\u793a\u7740\u5e02\u573a\u8d8b\u52bf\u7684\u5373\u5c06\u9006\u8f6c\u3002<\/li>\n<\/ol>\n\n\n\n
      RSI \u867d\u7136\u662f\u4e00\u79cd\u6709\u6548\u7684\u6280\u672f\u5206\u6790\u5de5\u5177\uff0c\u4f46\u66fe\u88ab\u5e02\u573a\u201c\u6bd2\u6253\u201d\u7684\u6211\u4eec\u90fd\u77e5\u9053\uff0c\u4e0d\u5e94\u8fc7\u5ea6\u4f9d\u8d56\u5355\u4e00\u6307\u6807\uff0c\u800c\u5e94\u7ed3\u5408\u5176\u4ed6\u6280\u672f\u6307\u6807\u548c\u57fa\u672c\u9762\u5206\u6790\u6765\u505a\u51fa\u66f4\u5168\u9762\u7684\u6295\u8d44\u51b3\u7b56\u3002\u4e0b\u9762\u6211\u4eec\u5f00\u59cb\u7ed3\u5408VROC \u548c RSI <\/strong>\u6765\u8fdb\u884c\u4ea4\u6613\u7b56\u7565\u7684\u6784\u5efa\u3002<\/p>\n\n\n\n
      \u4e8c\u3001\u7ed3\u5408 VROC \u548c RSI \u7684\u4ea4\u6613\u7b56\u7565\u8bbe\u8ba1<\/strong><\/h2>\n\n\n\n
      \u5229\u7528 VROC \u548c RSI \u6307\u6807\uff0c\u6211\u4eec\u53ef\u4ee5\u8003\u8651\u4ee5\u4e0b\u4e00\u4e9b\u53ef\u884c\u7684\u4ea4\u6613\u7b56\u7565\uff1a<\/p>\n\n\n\n
      2.1 \u4f7f\u7528 VROC \u8fdb\u884c\u52a8\u91cf\u4ea4\u6613<\/strong><\/h3>\n\n\n\n
        \n
      • \u7b56\u7565\uff1a<\/strong>\u5bfb\u627e VROC \u4e0a\u5347\u7684\u80a1\u7968\uff0c\u8fd9\u8868\u660e\u5e02\u573a\u5173\u6ce8\u5ea6\u548c\u6210\u4ea4\u91cf\u90fd\u5728\u589e\u52a0\u3002\u8fd9\u53ef\u80fd\u9884\u793a\u7740\u5f3a\u52b2\u7684\u4e0a\u5347\u52bf\u5934\u3002<\/li>\n\n\n\n
      • \u5f53 VROC \u8de8\u8fc7\u9884\u5b9a\u7684\u4e70\u5165\u9608\u503c\u65f6\uff0c\u8003\u8651\u8fdb\u5165\u591a\u5934\u4ed3\u4f4d\u3002<\/li>\n\n\n\n
      • \u53ea\u8981 VROC \u4fdd\u6301\u5728\u8fd9\u4e00\u4e34\u754c\u503c\u4ee5\u4e0a\uff0c\u5c31\u4fdd\u6301\u4ed3\u4f4d\u3002<\/li>\n\n\n\n
      • \u5f53 VROC \u5f00\u59cb\u4e0b\u964d\u6216\u4f4e\u4e8e\u4e34\u754c\u503c\u65f6\u9000\u51fa\u3002<\/li>\n<\/ul>\n\n\n\n
        2.2  RSI \u8d85\u4e70\/\u8d85\u5356\u7b56\u7565 <\/strong><\/h3>\n\n\n\n
          \n
        • \u7b56\u7565\uff1a<\/strong>\u4f7f\u7528 RSI \u8bc6\u522b\u80a1\u4ef7\u7684\u6f5c\u5728\u53cd\u8f6c\u70b9\u3002<\/li>\n\n\n\n
        • \u5982\u679c RSI \u8dcc\u7834 30\uff0c\u53ef\u80fd\u8868\u660e\u8be5\u80a1\u5df2\u7ecf\u8d85\u5356\u3002\u8003\u8651\u5efa\u7acb\u591a\u5934\u5934\u5bf8\u3002<\/li>\n\n\n\n
        • \u5982\u679c RSI \u5347\u81f3 70 \u4ee5\u4e0a\uff0c\u53ef\u80fd\u8868\u660e\u80a1\u4ef7\u8d85\u4e70\u3002\u8003\u8651\u5efa\u7acb\u7a7a\u5934\u5934\u5bf8\u6216\u9000\u51fa\u591a\u5934\u5934\u5bf8\u3002<\/li>\n\n\n\n
        • \u5728\u91c7\u53d6\u884c\u52a8\u4e4b\u524d\uff0c\u4e00\u5b9a\u8981\u76d1\u6d4b\u5176\u4ed6\u6307\u6807\uff0c\u4ee5\u786e\u8ba4\u4fe1\u53f7\u3002<\/li>\n<\/ul>\n\n\n\n
          2.3 \u7ed3\u5408 VROC \u548c RSI \u7684\u4fe1\u53f7 <\/strong><\/h3>\n\n\n\n
            \n
          • \u7b56\u7565\uff1a<\/strong>\u7ed3\u5408 VROC \u548c RSI \u6d1e\u5bdf\u529b\uff0c\u589e\u5f3a\u4ea4\u6613\u4fe1\u53f7\u3002<\/li>\n\n\n\n
          • \u5f53 VROC \u4e0a\u5347\uff08\u9ad8\u4e8e\u4e70\u5165\u9608\u503c\uff09\u4e14 RSI \u4f4e\u4e8e 30\uff08\u8d85\u5356\uff09\u65f6\uff0c\u5efa\u7acb\u591a\u5934\u5934\u5bf8\u3002<\/li>\n\n\n\n
          • \u5f53 VROC \u4e0b\u964d\uff08\u4f4e\u4e8e\u5356\u51fa\u9608\u503c\uff09\u4e14 RSI \u8d85\u8fc7 70\uff08\u8d85\u4e70\uff09\u65f6\uff0c\u5efa\u7acb\u7a7a\u5934\u5934\u5bf8\u3002<\/li>\n\n\n\n
          • \u8fd9\u79cd\u7b56\u7565\u8981\u6c42\u4e24\u4e2a\u6761\u4ef6\u4e00\u81f4\uff0c\u6709\u52a9\u4e8e\u786e\u8ba4\u4fe1\u53f7\u7684\u5f3a\u5ea6\u3002<\/li>\n<\/ul>\n\n\n\n
            2.4 \u57fa\u4e8e\u6ce2\u52a8\u6027\u7684\u9608\u503c\u8c03\u6574 <\/strong><\/h3>\n\n\n\n
              \n
            • \u7b56\u7565\uff1a<\/strong>\u6839\u636e\u5e02\u573a\u6ce2\u52a8\u8c03\u6574 VROC \u548c RSI \u4e34\u754c\u503c\u3002<\/li>\n\n\n\n
            • \u5728\u52a8\u8361\u7684\u5e02\u573a\u4e2d\uff0c\u8003\u8651\u6536\u7d27\u9608\u503c\uff08\u5982\uff1a\u5c06 RSI \u9608\u503c\u8bbe\u7f6e\u4e3a 25 \u548c 75\uff09\uff0c\u4ee5\u4fbf\u66f4\u5feb\u6355\u6349\u53cd\u8f6c\u3002<\/li>\n\n\n\n
            • \u5728\u7a33\u5b9a\u7684\u5e02\u573a\u4e2d\uff0c\u66f4\u5bbd\u7684\u9608\u503c\u53ef\u80fd\u6709\u52a9\u4e8e\u6355\u6349\u66f4\u5927\u7684\u6ce2\u52a8\uff08\u4f8b\u5982\uff0cRSI \u9608\u503c\u4e3a 20 \u548c 80\uff09\u3002<\/li>\n\n\n\n
            • \u6839\u636e\u5386\u53f2\u4e1a\u7ee9\u548c\u5e02\u573a\u6761\u4ef6\u4e0d\u65ad\u8fdb\u884c\u8bc4\u4f30\u548c\u8c03\u6574\u3002<\/li>\n<\/ul>\n\n\n\n
              2.5 \u8ffd\u8e2a\u6b62\u635f\u7b56\u7565 <\/strong><\/h3>\n\n\n\n
                \n
              • \u7b56\u7565\uff1a<\/strong>\u5229\u7528\u8ffd\u8e2a\u6b62\u635f\u4fdd\u62a4\u6536\u76ca\uff0c\u540c\u65f6\u5141\u8bb8\u8fdb\u4e00\u6b65\u4e0a\u6da8\u3002<\/li>\n\n\n\n
              • \u4e3a\u591a\u5934\u5934\u5bf8\u8bbe\u7f6e\u4f4e\u4e8e\u5e02\u4ef7\u4e00\u5b9a\u767e\u5206\u6bd4\u7684\u8ffd\u8e2a\u6b62\u635f\u3002<\/li>\n\n\n\n
              • \u5982\u679c RSI \u8dcc\u7834 50\uff0c\u5219\u8003\u8651\u6536\u7d27\u6b62\u635f\u6216\u83b7\u5229\u4e86\u7ed3\u3002<\/li>\n\n\n\n
              • \u8fd9\u79cd\u7b56\u7565\u65e2\u80fd\u9501\u5b9a\u5229\u6da6\uff0c\u53c8\u80fd\u4e3a\u4ea4\u6613\u63d0\u4f9b\u53d1\u5c55\u7a7a\u95f4\u3002<\/li>\n<\/ul>\n\n\n\n
                \u4e09\u3001\u4ee3\u7801\u5b9e\u73b0<\/strong><\/h2>\n\n\n\n
                \u63a5\u4e0b\u6765\u8ba9\u6211\u4eec\u4e00\u8d77\u6765\u6253\u9020 VROC \u548c RSI \u4ea4\u6613\u4eea\u8868\u76d8\uff01\u8fd9\u4e2a\u57fa\u7840\u7684\u4ea4\u4e92\u5f0f\u4eea\u8868\u76d8\u4e13\u4e3a\u597d\u5947\u7684\u65b0\u624b\u8bbe\u8ba1\uff0c\u6211\u4e3e\u7684\u4f8b\u5b50\u662f\u5bf9\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u524d 50 \u53ea\u80a1\u7968\u7684\u5206\u6790\uff0c\u5305\u62ec\u82f9\u679c (AAPL)\u3001\u8c37\u6b4c (GOOGL) \u548c\u7279\u65af\u62c9 (TSLA) \u7b49\u5de8\u5934\u3002\u8ba9\u6211\u4eec\u6765\u770b\u770b\u5982\u4f55\u5229\u7528\u8fd9\u4e00\u5de5\u5177\u4e3a\u60a8\u505a\u51fa\u66f4\u660e\u667a\u7684\u4ea4\u6613\u51b3\u7b56\uff01\u4e0b\u9762\u662f\u4e3b\u8981\u7ec4\u4ef6\u7684\u5206\u89e3\u4ee3\u7801\uff1a<\/p>\n\n\n\n
                3.1 \u5efa\u5e93<\/strong><\/h3>\n\n\n\n
                import streamlit as st\nimport yfinance as yf\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom datetime import datetime, timedelta<\/code><\/code><\/pre>\n\n\n\n
                \u6211\u4eec\u5bfc\u5165\u4e86\u4e00\u4e9b\u91cd\u8981\u7684\u5e93\uff0c\u5982\u7528\u4e8e\u7f51\u7edc\u5e94\u7528\u529f\u80fd\u7684 Streamlit \u5e93\u3001\u7528\u4e8e\u83b7\u53d6\u80a1\u7968\u6570\u636e\u7684 yfinance \u5e93\u548c\u7528\u4e8e\u7ed8\u5236\u56fe\u8868\u7684 matplotlib \u5e93\u3002<\/p>\n\n\n\n
                3.2 \u9009\u62e9\u80a1\u7968<\/strong><\/h3>\n\n\n\n
                top_50_stocks = [\n    'AAPL', 'MSFT', 'AMZN', 'GOOGL', 'TSLA',\n    ...\n]<\/code><\/code><\/pre>\n\n\n\n
                \u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4efd\u6807\u51c6\u666e\u5c14 500 \u6307\u6570\u524d 50 \u540d\u80a1\u7968\u7684\u5217\u8868\uff0c\u4ee5\u586b\u5145\u9009\u62e9\u4e0b\u62c9\u83dc\u5355\u3002<\/p>\n\n\n\n
                3.3 \u8ba1\u7b97 VROC<\/strong><\/h3>\n\n\n\n
                def calculate_vroc(data, period=5):\n    data['VROC'] = data['Volume'].pct_change(periods=period) * 100\n    return data<\/code><\/code><\/pre>\n\n\n\n
                \u8be5\u51fd\u6570\u8ba1\u7b97\u6210\u4ea4\u91cf\u53d8\u5316\u7387 (VROC)\u3002\u5b83\u8ba1\u7b97\u6307\u5b9a\u65f6\u95f4\u6bb5\u5185\u6210\u4ea4\u91cf\u7684\u767e\u5206\u6bd4\u53d8\u5316\uff0c\u5e2e\u52a9\u6211\u4eec\u8bc4\u4f30\u4ea4\u6613\u6d3b\u52a8\u3002<\/p>\n\n\n\n
                3.4 \u8ba1\u7b97 RSI<\/strong><\/h3>\n\n\n\n
                def calculate_rsi(data, period=14):\n    delta = data['Close'].diff()\n    gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()\n    loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()\n    rs = gain \/ loss\n    data['RSI'] = 100 - (100 \/ (1 + rs))\n    return data<\/code><\/code><\/pre>\n\n\n\n
                \u5728\u6b64\uff0c\u6211\u4eec\u8ba1\u7b97\u76f8\u5bf9\u5f3a\u5f31\u6307\u6570 (RSI)\u3002\u8be5\u51fd\u6570\u8ba1\u7b97\u6307\u5b9a\u65f6\u95f4\u6bb5\u5185\u7684\u5e73\u5747\u6536\u76ca\u548c\u635f\u5931\uff0c\u6709\u52a9\u4e8e\u8bc6\u522b\u6f5c\u5728\u7684\u4e70\u5165\/\u5356\u51fa\u4fe1\u53f7\u3002<\/p>\n\n\n\n
                3.5 \u83b7\u53d6\u6570\u636e<\/strong><\/h3>\n\n\n\n
                def get_yesterday_data(ticker):\n    end_date = datetime.now().date()\n    start_date = end_date - timedelta(days=1)\n    ...\n    return data<\/code><\/code><\/pre>\n\n\n\n
                \u8be5\u51fd\u6570\u83b7\u53d6\u6240\u9009\u80a1\u7968\u524d\u4e00\u5929\u7684\u4ea4\u6613\u6570\u636e\uff0c\u786e\u4fdd\u6211\u4eec\u5728\u7ee7\u7eed\u8ba1\u7b97\u4e4b\u524d\u83b7\u5f97\u6570\u636e\u3002<\/p>\n\n\n\n
                3.6 \u4fe1\u53f7\u751f\u6210<\/strong><\/h3>\n\n\n\n
                signals['Signal'] = 0\nsignals.loc[(signals['VROC'] > vroc_buy_threshold) & (signals['RSI'] < rsi_buy_threshold), 'Signal'] = 1\nsignals.loc[(signals['VROC'] < vroc_sell_threshold) & (signals['RSI'] > rsi_sell_threshold), 'Signal'] = -1<\/code><\/code><\/pre>\n\n\n\n
                \u6839\u636e\u7528\u6237\u5b9a\u4e49\u7684\u9608\u503c\uff0c\u6211\u4eec\u751f\u6210\u4e70\u5165\u548c\u5356\u51fa\u4fe1\u53f7\uff0c\u5e2e\u52a9\u4ea4\u6613\u8005\u786e\u5b9a\u6700\u4f73\u8fdb\u51fa\u573a\u70b9\u3002<\/p>\n\n\n\n
                3.7 \u7ed8\u5236\u56fe\u8868<\/strong><\/h3>\n\n\n\n
                fig = plt.figure(figsize=(14, 7))\nplt.plot(data['Close'], label='Close Price', color='blue')\nplt.plot(data['VROC'], label='VROC', color='orange')\nplt.plot(data['RSI'], label='RSI', color='green')\nplt.title(f'{ticker} Price, VROC, and RSI')\nplt.legend()\nst.pyplot(fig)<\/code><\/code><\/pre>\n\n\n\n
                \u6700\u540e\uff0c\u6211\u4eec\u5c06\u6536\u76d8\u4ef7\u3001VROC \u548c RSI \u7ed8\u5236\u5728\u4e00\u5f20\u56fe\u8868\u4e0a\uff0c\u8ba9\u7528\u6237\u76f4\u89c2\u5730\u4e86\u89e3\u4ea4\u6613\u6307\u6807\u3002<\/p>\n\n\n\n
                3.8  \u5b8c\u6574\u4ee3\u7801\u7247\u6bb5<\/strong><\/h3>\n\n\n\n
                import streamlit as st\nimport yfinance as yf\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom datetime import datetime, timedelta\n\n# Define top 50 stocks list\ntop_50_stocks = [\n    'AAPL', 'MSFT', 'AMZN', 'GOOGL', 'TSLA',\n    # ... add other stocks here\n]\n\n# Function to calculate VROC\ndef calculate_vroc(data, period=5):\n    data['VROC'] = data['Volume'].pct_change(periods=period) * 100\n    return data\n\n# Function to calculate RSI\ndef calculate_rsi(data, period=14):\n    delta = data['Close'].diff()\n    gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()\n    loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()\n    rs = gain \/ loss\n    data['RSI'] = 100 - (100 \/ (1 + rs))\n    return data\n\n# Fetch yesterday's data\ndef get_yesterday_data(ticker):\n    end_date = datetime.now().date()\n    start_date = end_date - timedelta(days=1)\n    data = yf.download(ticker, start=start_date, end=end_date)\n    return data\n\n# Streamlit App\nst.title('VROC and RSI Day Trading Dashboard')\n\nselected_stock = st.selectbox('Select a stock:', top_50_stocks)\n\n# Fetch and process stock data\ndata = get_yesterday_data(selected_stock)\ndata = calculate_vroc(data)\ndata = calculate_rsi(data)\n\n# Set trading thresholds\nvroc_buy_threshold = st.slider('VROC Buy Threshold', -100, 100, 20)\nvroc_sell_threshold = st.slider('VROC Sell Threshold', -100, 100, -20)\nrsi_buy_threshold = st.slider('RSI Buy Threshold', 0, 100, 30)\nrsi_sell_threshold = st.slider('RSI Sell Threshold', 0, 100, 70)\n\n# Signal generation\ndata['Signal'] = 0\ndata.loc[(data['VROC'] > vroc_buy_threshold) & (data['RSI'] < rsi_buy_threshold), 'Signal'] = 1\ndata.loc[(data['VROC'] < vroc_sell_threshold) & (data['RSI'] > rsi_sell_threshold), 'Signal'] = -1\n\n# Plotting\nfig = plt.figure(figsize=(14, 7))\nplt.plot(data['Close'], label='Close Price', color='blue')\nplt.plot(data['VROC'], label='VROC', color='orange')\nplt.plot(data['RSI'], label='RSI', color='green')\nplt.title(f'{selected_stock} Price, VROC, and RSI')\nplt.legend()\nst.pyplot(fig)<\/code><\/code><\/pre>\n\n\n\n
                \u56db\u3001\u6218\u7565\u6709\u6548\u6027\u6d4b\u8bd5<\/strong><\/h2>\n\n\n\n
                \u4e3a\u4e86\u8bf4\u660e VROC \u548c RSI \u4ea4\u6613\u7b56\u7565\u7684\u6709\u6548\u6027\uff0c\u8ba9\u6211\u4eec\u6765\u770b\u4e00\u4e9b\u793a\u4f8b\u56fe\u8868\u8f93\u51fa\u7ed3\u679c\uff1a<\/p>\n\n\n\n
                4.1 \u82f9\u679c\u516c\u53f8\uff08AAPL\uff09\u793a\u4f8b<\/strong><\/h3>\n\n\n\n
                \"\"\/<\/figure>\n\n\n\n
                \u5728\u8fd9\u5f20\u56fe\u8868\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff1a<\/p>\n\n\n\n