{"id":562,"date":"2020-01-29T15:32:47","date_gmt":"2020-01-29T07:32:47","guid":{"rendered":"http:\/\/123.57.142.208\/?p=203"},"modified":"2020-01-29T15:32:47","modified_gmt":"2020-01-29T07:32:47","slug":"matlab%e6%95%b0%e6%a8%a1-03%e5%bc%80%e5%a7%8b%e5%ae%9e%e6%88%98","status":"publish","type":"post","link":"http:\/\/43.142.23.155\/?p=562","title":{"rendered":"Matlab&\u6570\u6a21-03\u5f00\u59cb\u5b9e\u6218"},"content":{"rendered":"

\u9996\u5148\u5462\uff0c\u795d\u5927\u5676\u9f20\u5e74\u5927\u5409\uff01<\/h3>\n

\u7531\u4e8e\u6700\u8fd1sari\u8086\u8650\uff0c\u88ab\u8feb\u5b85\u5728\u5bb6\u91cc\u7ec8\u4e8e\u4e0d\u5f97\u4e0d\u5b66\u4e60\u5b66\u4e60hhh\uff0c\u65e2\u7136\u8bf4\u662f\u5b9e\u6218\uff0c\u6211\u5728\u6211\u7f51\u4e0a\u627e\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u5c0f\u95ee\u9898\uff1a<\/p>\n

\u8bc4\u4f30\u80a1\u7968\u7684\u4ef7\u503c\u548c\u98ce\u9669<\/h1>\n

\u5177\u4f53\u7684\u95ee\u9898\u5185\u5bb9\uff1a\u5df2\u77e5\u80a1\u7968\u7684\u4ea4\u6613\u6570\u636e\uff1a\u65e5\u671f\u3001\u5f00\u76d8\u4ef7\u3001\u6700\u9ad8\u4ef7\u3001\u6700\u4f4e\u4ef7\u3001\u6536\u76d8\u4ef7\u3001\u6210\u4ea4\u91cf\u548c\u6362\u624b\u7387\uff0c\u8bd5\u7528\u67d0\u79cd\u65b9\u6cd5\u6765\u8bc4\u4ef7\u8fd9\u53ea\u80a1\u7968\u7684\u4ef7\u503c\u548c\u98ce\u9669\u3002\u5982\u4f55\u7528MATLAB\u53bb\u6c42\u89e3\u8be5\u95ee\u9898\uff1f<\/h3>\n

\uff08PS\uff1agithub\u5b98\u7f51\u539f\u6765\u7684IP\u597d\u50cf\u53d8\u4e86\uff0c\u5982\u679c\u66fe\u7ecf\u4fee\u6539\u8fc7hosts\u6587\u4ef6\uff0c\u8bb0\u5f97\u628a\u6539\u6210192.30<\/span>.253<\/span>.112<\/span> github<\/span>.com\uff0c\u5bb3\u5f97\u6211\u6587\u4ef6\u627e\u534a\u5929…)<\/span><\/p>\n

\u95ee\u9898\u76f8\u5173\u6587\u4ef6\u7684URL\uff1ahttps:\/\/github.com\/xiexupang\/mathematical-modeling\/tree\/master\/\u80a1\u7968<\/p>\n

\u4e00\u3001\u5bfc\u5165\u6570\u636e<\/h2>\n

\u6709\u8fd9\u4e48\u4e2a\u56fe\u6807\u2b07<\/p>\n

\"\"<\/p>\n

\u9009\u62e9\u5b8c\u6587\u4ef6\u540e\uff1a\"\"<\/p>\n

\u70b9\u51fb\u5bfc\u5165\uff0c\u6548\u679c\u56fe????<\/p>\n

\"\"<\/p>\n

 <\/p>\n

\u4e8c\u3001\u6570\u636e\u5206\u6790\u4e0e\u5efa\u6a21<\/h2>\n

matlab\u53ea\u662f\u4e00\u4e2a\u5de5\u5177\uff0c\u5c31\u50cf\u4f60\u505a\u795e\u7ecf\u7f51\u7edc\uff0cpy\u4e5f\u53ea\u662f\u5b9e\u73b0\u4f60\u601d\u60f3\u7684\u4e00\u4e2a\u9014\u5f84\uff0c\u5b83\u4e0d\u4f1a\u7ed9\u4f60\u5efa\u6a21\u7684\u5efa\u8bae\uff0c\u5177\u4f53\u9009\u62e9\u4ec0\u4e48\u6837\u7684\u7f51\u7edc\uff0c\u7528\u4ec0\u4e48\u6837\u7684\u51fd\u6570\u672c\u8d28\u8fd8\u662f\u9760\u4f60\u81ea\u5df1\u3002\u6240\u4ee5\u5c31\u50cf\u505a\u795e\u7ecf\u7f51\u7edc\u4e00\u6837\uff0c\u6211\u4eec\u5148\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u6790\uff0c\u89c2\u5bdf\u6570\u636e\u7684\u7279\u5f81\uff0c\u518d\u6839\u636e\u5206\u6790\u7ed3\u679c\u7ed3\u5408\u95ee\u9898\u8fdb\u884c\u5efa\u6a21\u3002<\/p>\n

\u7136\u9e45\u5bf9\u4e8e\u4e00\u4e2a\u5bf9\u6570\u5b57\u6ca1\u90a3\u4e48\u654f\u611f\u7684\u5c0f\u53ef\u601c\u800c\u8a00\uff0c\u5355\u7eaf\u770b\u8868\u683c\u6570\u636e\u662f\u6ca1\u4ec0\u4e48\u7528\u7684\uff0c\u6240\u4ee5\u6211\u4eec\u6700\u597d\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316<\/p>\n

plot\u51fd\u6570\u5373\u53ef\uff0c\u5f53\u7136\u4e5f\u53ef\u4ee5\u7528\u73b0\u6210\u7684\u5de5\u5177\u680f\u4e2d\u7684\u7ed8\u56fe\u3002<\/p>\n

\u5728\u8fd9\u4e4b\u540e\u6211\u4eec\u5c31\u8981\u8003\u8651\u5982\u4f55\u8bc4\u4f30\u80a1\u7968\u7684\u4ef7\u503c\u548c\u98ce\u9669\u5462\uff1f<\/p>\n

\u80a1\u7968\u7684\u589e\u5e45\u8d8a\u5927\u8d8a\u597d\uff0c\u4f53\u73b0\u5728\u6570\u5b66\u4e0a\uff0c\u5c31\u662f\u66f2\u7ebf\u7684\u659c\u7387\u8d8a\u5927\u8d8a\u597d\u3002\u5bf9\u4e8e\u98ce\u9669\uff0c\u5219\u53ef\u7528\u6700\u5927\u64a4\u56de\u7387\u6765\u63cf\u8ff0\u66f4\u5408\u9002\u3002<\/p>\n

\u6700\u5927\u56de\u64a4\u7387\u7684\u516c\u5f0f\u53ef\u4ee5\u8fd9\u6837\u8868\u8fbe:<\/p>\n

\u82e5D\u4e3a\u67d0\u4e00\u5929\u7684\u51c0\u503c\uff0ci\u4e3a\u67d0\u4e00\u5929\uff0cj\u4e3ai\u540e\u7684\u67d0\u4e00\u5929\uff0cDi\u4e3a\u7b2ci\u5929\u7684\u4ea7\u54c1\u51c0\u503c\uff0cDj\u5219\u662fDi\u540e\u9762\u67d0\u4e00\u5929\u7684\u51c0\u503c<\/p>\n

drawdown=max(Di-Dj)\/Di\uff0c<\/h4>\n

drawdown\u5c31\u662f\u6700\u5927\u56de\u64a4\u7387\u3002<\/p>\n

\u5176\u5b9e\u5c31\u662f\u5bf9\u6bcf\u4e00\u4e2a\u51c0\u503c\u8fdb\u884c\u56de\u64a4\u7387\u6c42\u503c\uff0c\u7136\u540e\u627e\u51fa\u6700\u5927\u7684\u3002\u53ef\u4ee5\u4f7f\u7528\u7a0b\u5e8f\u5b9e\u73b0\u3002\u6700\u5927\u56de\u64a4\u7387\u8d8a\u5927\uff0c\u8bf4\u660e\u8be5\u80a1\u7968\u7684\u98ce\u9669\u8d8a\u9ad8\u3002\u6240\u4ee5\u6700\u5927\u56de\u64a4\u7387\u8d8a\u5c0f\uff0c\u80a1\u7968\u8d8a\u597d\u3002<\/p>\n

\u659c\u7387\u548c\u6700\u5927\u56de\u64a4\u7387\u4e0d\u59a8\u4e00\u4e2a\u4e00\u4e2a\u6765\u89e3\u51b3\u3002\u6211\u4eec\u5148\u6765\u770b\u5982\u4f55\u8ba1\u7b97\u66f2\u7ebf\u7684\u659c\u7387\u3002\u5bf9\u4e8e\u8fd9\u4e2a\u95ee\u9898\uff0c\u6bd4\u8f83\u7b80\u5355\uff0c\u7531\u4e8e\u4ece\u6570\u636e\u7684\u53ef\u89c6\u5316\u7ed3\u679c\u6765\u770b\uff0c\u6570\u636e\u8fd1\u4f3c\u6210\u7ebf\u6027\uff0c\u6240\u4ee5\u4e0d\u59a8\u7528\u591a\u9879\u5f0f\u62df\u5408\u7684\u65b9\u6cd5\u6765\u62df\u5408\u8be5\u6539\u7ec4\u6570\u636e\u7684\u65b9\u7a0b\uff0c\u8fd9\u6837\u6211\u4eec\u5c31\u53ef\u4ee5\u5f97\u5230\u659c\u7387\u3002<\/p>\n

\u8fd9\u91cc\u6211\u5f97\u8bf4\u4e00\u4e0b\uff0c\u6211\u8fd9\u91cc\u5f97\u5230\u7684\u6570\u636e\u6587\u4ef6\u975e\u5e38\u4e0d\u9f50\u5168\uff0c\u4ee5\u81f3\u4e8e\u5b83\u53ea\u662f\u6570\u636e\u4e2d\u7684\u4e00\u5c0f\u90e8\u5206\uff0c\u751a\u81f3\u53ef\u4ee5\u8bf4\u5b83\u53ea\u80fd\u7b97\u662f\u4e00\u4e2a\u5c0f\u5c0f\u7684\u7279\u5f81\u70b9\uff0c\u4e0d\u8fc7\u53cd\u6b63\u6211\u4eec\u4e5f\u4e0d\u662f\u771f\u7684\u60f3\u505a\u4ec0\u4e48\uff0c\u6240\u4ee5\u65e2\u7136\u662f\u4e00\u4e2a\u7ec3\u4e60\u5c31\u7ee7\u7eed\u628a\u64cd\u4f5c\u548c\u8be5\u6709\u7684\u6d41\u7a0b\u8d70\u5b8c\uff0c\u597d\u5427\uff0c\u4e0b\u6b21\u4e00\u5b9a\u662f\u4e00\u4e2a\u50cf\u6837\u7684\u5b9e\u64cd\uff08\u4e0b\u6b21\u4e00\u5b9a\u4e0b\u6b21\u4e00\u5b9a????<\/p>\n

\u901a\u8fc7polyfit()\u591a\u9879\u5f0f\u62df\u5408\u7684\u547d\u4ee4\uff0c\u5e76\u8ba1\u7b97\u80a1\u7968\u7684\u4ef7\u503c\uff0c\u5177\u4f53\u4ee3\u7801\u5927\u6982\u662f\u8fd9\u6837\uff1a<\/p>\n

>> p = polyfit(DateNum,Pclose,1);\u00a0%\u00a0\u591a\u9879\u5f0f\u62df\u5408<\/p>\n

>> value = p(1)\u00a0%\u00a0\u5c06\u659c\u7387\u8d4b\u503c\u7ed9value\uff0c\u4f5c\u4e3a\u80a1\u7968\u7684\u4ef7\u503c<\/p>\n

value =<\/p>\n

0.1212<\/p>\n

\u90a3\u4e48\u7b2c\u4e09\u4e2a\u5192\u51fa\u6765\u7684\u53c2\u65701\u662f\u4ec0\u4e48\u610f\u601d\u5462\uff1f<\/p>\n

\u5b83\u8868\u793a\u591a\u9879\u5f0f\u7684\u9636\u6570\uff0c\u4e5f\u5c31\u662f\u6700\u9ad8\u6b21\u6570<\/p>\n

\u6bd4\u5982\uff1a\u5728\u672c\u4f8b\u4e2d\uff0c\u7b2c\u4e09\u4e2a\u53c2\u6570\u4e3a1\uff0c\u8bf4\u660e\u5176\u4e3a\u4e00\u6b21\u9879\uff0c\u5373\u4e00\u6b21\u51fd\u6570\u3002\u7b2c\u4e09\u4e2a\u53c2\u6570\u4e3a\u4f60\u8981\u62df\u5408\u7684\u9636\u6570\uff0c\u4e00\u9636\u76f4\u7ebf\u62df\u5408\uff0c\u4e8c\u9636\u629b\u7269\u7ebf\u62df\u5408\uff0c\u5e76\u975e\u9636\u6b21\u8d8a\u9ad8\u8d8a\u597d\uff0c\u770b\u62df\u5408\u60c5\u51b5\u800c\u5b9a\u3002<\/p>\n

polyfit()\u8fd4\u56de\u9636\u6570\u4e3a n \u7684\u591a\u9879\u5f0f p(x) \u7684\u7cfb\u6570\uff0cp \u4e2d\u7684\u7cfb\u6570\u6309\u964d\u5e42\u6392\u5217\u3002\u5728\u672c\u4f8b\u4e2d\u7684P(1)\u6307\u7684\u662f\u6700\u9ad8\u9879\u7684\u7cfb\u6570\uff0c\u5373\u659c\u7387\u3002<\/p>\n

\u8ba1\u7b97\u6700\u5927\u56de\u64a4\u7684\u4ee3\u7801\uff1a<\/p>\n

>> MaxDD = maxdrawdown(Pclose); % \u8ba1\u7b97\u6700\u5927\u56de\u64a4<\/p>\n

>> risk = MaxDD % \u5c06\u6700\u5927\u56de\u64a4\u8d4b\u503c\u7ed9risk\uff0c\u4f5c\u4e3a\u80a1\u7968\u7684\u98ce\u9669<\/p>\n

risk =<\/p>\n

0.1155<\/p>\n

\u6211\u53bb\u4e86\u89e3\u4e86\u4e00\u4e0b\uff0c\u53d1\u73b0\u6700\u5927\u56de\u64a4\u7387\u8ba1\u7b97\u7684\u662f\u6bcf\u5929\u6536\u76d8\u65f6\u7684\u80a1\u4ef7\u3002\u6700\u5927\u56de\u64a4\u7387\u8d8a\u5927\uff0c\u8bf4\u660e\u8be5\u80a1\u7968\u7684\u98ce\u9669\u8d8a\u9ad8\u3002\u6240\u4ee5\u6700\u5927\u56de\u64a4\u7387\u8d8a\u5c0f\uff0c\u4ece\u98ce\u9669\u8fd9\u4e2a\u89d2\u5ea6\u6765\u8bf4\u80a1\u7968\u8d8a\u597d\u3002<\/p>\n

\u4e09\u3001\u751f\u6210\u811a\u672c<\/h2>\n

\u6240\u4ee5\u63a5\u4e0b\u6765\u505a\u4ec0\u4e48\uff1f\u6d41\u7a0b\u544a\u8bc9\u6211\u4eec\u8be5\u7528\u811a\u672c…WHY\uff1f<\/p>\n

Matlab\u6700\u7ecf\u5178\u7684\u4e00\u79cd\u529f\u80fd\u5c31\u662f\u5176\u811a\u672c\uff0c\u4e0d\u4ec5\u80fd\u591f\u5b8c\u6574\u5730\u5448\u73b0\u6574\u4e2a\u95ee\u9898\u7684\u89e3\u51b3\u65b9\u6cd5\uff0c\u540c\u65f6\u66f4\u4fbf\u4e8e\u7ef4\u62a4\u3001\u5b8c\u5584\u3001\u6267\u884c\u3002\u6240\u4ee5\u5f53\u6211\u4eec\u7684\u63a2\u7d22\u548c\u5f00\u53d1\u5de5\u4f5c\u6bd4\u8f83\u6210\u719f\u540e\uff0c\u901a\u5e38\u90fd\u4f1a\u5c06\u8fd9\u4e9b\u6709\u7528\u7684\u7a0b\u5e8f\u5f52\u7eb3\u6574\u7406\u8d77\u6765\uff0c\u5f62\u6210\u811a\u672c\u3002<\/p>\n

\u6211\u4eec\u8981\u505a\u7684\u5c31\u662f\uff1a<\/p>\n

\u91cd\u65b0\u9009\u4e2d\u6570\u636e\u6587\u4ef6\uff0c\u53f3\u952e\u5e76\u5355\u51fb\u201c\u5bfc\u5165\u6570\u636e\u201d\u83dc\u5355\uff0c\u5f85\u542f\u52a8\u5bfc\u5165\u6570\u636e\u5f15\u64ce\u540e\uff0c\u9009\u62e9\u201c\u751f\u6210\u811a\u672c\u201d\uff0c\u7136\u540e\u5c31\u4f1a\u5f97\u5230\u5bfc\u5165\u6570\u636e\u7684\u811a\u672c\uff0c\u5e76\u4fdd\u5b58\u8be5\u811a\u672c\u3002<\/p>\n

\u811a\u672c\u6e90\u4ee3\u7801\u4e2d\u6709\u4e9b\u5730\u65b9\u8981\u6ce8\u610f\uff1a<\/p>\n

%%\u5728matlab\u4ee3\u7801\u4e2d\u7684\u4f5c\u7528\u662f\u5c06\u4ee3\u7801\u5206\u5757\uff0c\u4e0a\u4e0b\u4e24\u4e2a%%\u4e4b\u95f4\u7684\u90e8\u5206\u4f5c\u4e3a\u4e00\u5757\uff0c\u5728\u8fd0\u884c\u4ee3\u7801\u7684\u65f6\u5019\u53ef\u4ee5\u5206\u5757\u8fd0\u884c\uff0c\u67e5\u770b\u6bcf\u4e00\u5757\u4ee3\u7801\u7684\u8fd0\u884c\u60c5\u51b5\u3002\u5e38\u7528\u4e8e\u8c03\u8bd5\u7a0b\u5e8f\u3002%%\u76f8\u5f53\u4e8ejupyter notebook\u4e2d\u7684cell\u3002<\/p>\n

%\u540e\u7684\u5185\u5bb9\u662f\u6ce8\u91ca\u3002<\/p>\n

\u6bcf\u53e5\u4ee3\u7801\u540e\u9762\u7684\u5206\u53f7\u4f5c\u7528\u4e3a\u4e0d\u5728\u547d\u4ee4\u7a97\u53e3\u663e\u793a\u6267\u884c\u7ed3\u679c\u3002<\/p>\n

 <\/p>\n

 <\/p>\n

\u4ee5\u4e0b\uff0c\u811a\u672c\u7684\u4e3e\u4f8b\u6e90\u7801\uff1a<\/p>\n

%% \u9884\u6d4b\u80a1\u7968\u7684\u4ef7\u503c\u4e0e\u98ce\u9669<\/p>\n

%% \u5bfc\u5165\u6570\u636e
\nclc, clear, close all
\n% clc\uff1a\u6e05\u9664\u547d\u4ee4\u7a97\u53e3\u7684\u5185\u5bb9\uff0c\u5bf9\u5de5\u4f5c\u73af\u5883\u4e2d\u7684\u5168\u90e8\u53d8\u91cf\u65e0\u4efb\u4f55\u5f71\u54cd
\n% clear\uff1a\u6e05\u9664\u5de5\u4f5c\u7a7a\u95f4\u7684\u6240\u6709\u53d8\u91cf
\n% close all:\u5173\u95ed\u6240\u6709\u7684Figure\u7a97\u53e3<\/p>\n

% \u5bfc\u5165\u6570\u636e
\n[~, ~, raw] = xlsread(‘sz000004.xlsx’, ‘Sheet1’, ‘A2:H7’);
\n% [num,txt,raw],~\u8868\u793a\u7701\u7565\u8be5\u90e8\u5206\u7684\u8fd4\u56de\u503c
\n% xlsread(‘filename’\uff0c’sheet’\uff0c ‘range’)\uff0c\u7b2c\u4e8c\u4e2a\u53c2\u6570\u6307\u6570\u636e\u5728sheet1\u8fd8\u662f\u5176\u4ed6sheet\u90e8\u5206\uff0crange\u8868\u793a\u5355\u5143\u683c\u8303\u56f4<\/p>\n

% \u521b\u5efa\u8f93\u51fa\u53d8\u91cf
\ndata = reshape([raw{:}],size(raw));
\n% [raw{:}]\u6307raw\u91cc\u7684\u6240\u6709\u6570\u636e\uff0csize(raw)\uff1a6 x 8 \uff0c\u8be5\u8bed\u53e5\u628a6×8\u7684cell\u7c7b\u578b\u6570\u636e\u8f6c\u6362\u4e3a6×8 double\u7c7b\u578b\u6570\u636e<\/p>\n

% \u5c06\u5bfc\u5165\u7684\u6570\u7ec4\u5206\u914d\u5217\u53d8\u91cf\u540d\u79f0
\nDate = data(:, 1); % \u7b2c\u4e00\u4e2a\u53c2\u6570\u8868\u793a\u4ece\u7b2c\u4e00\u884c\u5230\u6700\u540e\u4e00\u884c\uff0c\u7b2c\u4e8c\u4e2a\u53c2\u6570\u8868\u793a\u7b2c\u4e00\u5217
\nDateNum = data(:, 2);
\nPopen = data(:, 3);
\nPhigh = data(:, 4);
\nPlow = data(:, 5);
\nPclose = data(:, 6);
\nVolum = data(:, 7); % Volume \u8868\u793a\u80a1\u7968\u6210\u4ea4\u91cf\u7684\u610f\u601d\uff0c\u6210\u4ea4\u91cf=\u6210\u4ea4\u80a1\u6570*\u6210\u4ea4\u4ef7\u683c \u518d\u52a0\u6743\u6c42\u548c
\nTurn = data(:, 8); % turn\u8868\u793a\u80a1\u7968\u5468\u8f6c\u7387\uff0c\u80a1\u7968\u5468\u8f6c\u7387\u8d8a\u9ad8\uff0c\u610f\u5473\u7740\u8be5\u80a1\u80a1\u6027\u8d8a\u6d3b\u6cfc\uff0c\u4e5f\u5c31\u662f\u6295\u8d44\u4eba\u6240\u8c13\u7684\u70ed\u95e8\u80a1<\/p>\n

% \u6e05\u9664\u4e34\u65f6\u53d8\u91cfdata\u548craw
\nclearvars data raw;<\/p>\n

%% \u6570\u636e\u63a2\u7d22<\/p>\n

figure % \u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u56fe\u50cf\u7a97\u53e3
\nplot(DateNum, Pclose, ‘k’); % ‘k’,\u66f2\u7ebf\u662f\u9ed1\u8272\u7684\uff0c\u6253\u5370\u540e\u4e0d\u5931\u771f
\ndatetick(‘x’,’mm-dd’); % \u66f4\u6539\u65e5\u671f\u663e\u793a\u7c7b\u578b\u3002\u53c2\u6570x\u8868\u793ax\u8f74\uff0cmm-dd\u8868\u793a\u6708\u4efd\u548c\u65e5\u3002yyyy-mm-dd,\u59822018-10-27
\nxlabel(‘\u65e5\u671f’) % x\u8f74
\nylabel(‘\u6536\u76d8\u4ef7’) % y\u8f74
\nfigure
\nbar(Pclose) % \u4f5c\u4e3a\u5bf9\u7167\u56fe\u5f62<\/p>\n

%% \u80a1\u7968\u4ef7\u503c\u7684\u8bc4\u4f30<\/p>\n

p = polyfit(DateNum, Pclose, 1); % \u591a\u9879\u5f0f\u62df\u5408
\n% polyfit()\u8fd4\u56de\u9636\u6570\u4e3a n \u7684\u591a\u9879\u5f0f p(x) \u7684\u7cfb\u6570\uff0cp \u4e2d\u7684\u7cfb\u6570\u6309\u964d\u5e42\u6392\u5217
\nP1 = polyval(p,DateNum); % \u5f97\u5230\u591a\u9879\u5f0f\u6a21\u578b\u7684\u7ed3\u679c
\nfigure
\nplot(DateNum,P1,DateNum,Pclose,’*g’); % \u6a21\u578b\u4e0e\u539f\u59cb\u6570\u636e\u7684\u5bf9\u7167, ‘*g’\u8868\u793a\u7eff\u8272\u7684*
\nvalue = p(1) % \u5c06\u659c\u7387\u8d4b\u503c\u7ed9value\uff0c\u4f5c\u4e3a\u80a1\u7968\u7684\u4ef7\u503c\u3002p(1)\u6700\u9ad8\u9879\u7684\u6b21\u6570<\/p>\n

%% \u80a1\u7968\u98ce\u9669\u7684\u8bc4\u4f30
\nMaxDD = maxdrawdown(Pclose); % \u8ba1\u7b97\u6700\u5927\u56de\u64a4
\nrisk = MaxDD % \u5c06\u6700\u5927\u56de\u64a4\u8d4b\u503c\u7ed9risk\uff0c\u4f5c\u4e3a\u80a1\u7968\u7684\u98ce\u9669<\/p>\n","protected":false},"excerpt":{"rendered":"

\u9996\u5148\u5462\uff0c\u795d\u5927\u5676\u9f20\u5e74\u5927\u5409\uff01 \u7531\u4e8e\u6700\u8fd1sari\u8086\u8650\uff0c\u88ab\u8feb\u5b85\u5728\u5bb6\u91cc\u7ec8\u4e8e\u4e0d\u5f97\u4e0d\u5b66\u4e60\u5b66\u4e60hhh\uff0c\u65e2\u7136\u8bf4\u662f\u5b9e\u6218\uff0c\u6211\u5728\u6211\u7f51\u4e0a\u627e\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u5c0f\u95ee\u9898\uff1a \u8bc4\u4f30\u80a1\u7968\u7684\u4ef7\u503c\u548c\u98ce\u9669 \u5177\u4f53\u7684\u95ee\u9898\u5185\u5bb9\uff1a\u5df2\u77e5\u80a1\u7968\u7684\u4ea4\u6613\u6570\u636e\uff1a\u65e5\u671f\u3001\u5f00...<\/p>\n","protected":false},"author":1,"featured_media":198,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[],"class_list":["post-562","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-8"],"_links":{"self":[{"href":"http:\/\/43.142.23.155\/index.php?rest_route=\/wp\/v2\/posts\/562","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/43.142.23.155\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/43.142.23.155\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/43.142.23.155\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/43.142.23.155\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=562"}],"version-history":[{"count":0,"href":"http:\/\/43.142.23.155\/index.php?rest_route=\/wp\/v2\/posts\/562\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/43.142.23.155\/index.php?rest_route=\/wp\/v2\/media\/198"}],"wp:attachment":[{"href":"http:\/\/43.142.23.155\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=562"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/43.142.23.155\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=562"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/43.142.23.155\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=562"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}