{"id":398,"date":"2026-02-24T10:22:18","date_gmt":"2026-02-24T02:22:18","guid":{"rendered":"http:\/\/xuebuwan.com\/wp\/?p=398"},"modified":"2026-02-25T10:15:01","modified_gmt":"2026-02-25T02:15:01","slug":"%e9%87%8f%e5%8c%96%e4%ba%a4%e6%98%93%e6%95%b0%e5%ad%a6%e5%9f%ba%e7%a1%80%e5%8f%8a%e5%ad%a6%e4%b9%a0%e8%b7%af%e5%be%84","status":"publish","type":"post","link":"http:\/\/xuebuwan.com\/wp\/?p=398","title":{"rendered":"\u91cf\u5316\u4ea4\u6613\u6570\u5b66\u57fa\u7840\u53ca\u5b66\u4e60\u8def\u5f84"},"content":{"rendered":"<h3>\u4e00\u3001\u5f15\u8a00<\/h3>\n<p>\u91cf\u5316\u4ea4\u6613\uff08Quantitative Trading\uff09\u662f\u73b0\u4ee3\u91d1\u878d\u5e02\u573a\u4e2d\u9ad8\u5ea6\u4f9d\u8d56\u6570\u5b66\u3001\u7edf\u8ba1\u5b66\u4e0e\u8ba1\u7b97\u673a\u6280\u672f\u7684\u6295\u8d44\u65b9\u6cd5\u3002<br \/>\n\u5176\u6838\u5fc3\u5728\u4e8e\u901a\u8fc7\u6570\u5b66\u6a21\u578b\u4ece\u5386\u53f2\u6570\u636e\u4e2d\u6316\u6398\u5e02\u573a\u89c4\u5f8b\uff0c\u6784\u5efa\u53ef\u91cd\u590d\u3001\u53ef\u9a8c\u8bc1\u3001\u53ef\u81ea\u52a8\u6267\u884c\u7684\u4ea4\u6613\u7b56\u7565\u3002<br \/>\n\u4e0e\u4f20\u7edf\u4e3b\u89c2\u4ea4\u6613\u4e0d\u540c\uff0c\u91cf\u5316\u4ea4\u6613\u5f3a\u8c03\u5ba2\u89c2\u6027\u3001\u7cfb\u7edf\u6027\u4e0e\u7eaa\u5f8b\u6027\uff0c\u5176\u6210\u8d25\u5728\u5f88\u5927\u7a0b\u5ea6\u4e0a\u53d6\u51b3\u4e8e\u5efa\u6a21\u8005\u7684\u6570\u5b66\u7d20\u517b\u3002<\/p>\n<p>\u672c\u6587\u65e8\u5728\u7cfb\u7edf\u68b3\u7406\u91cf\u5316\u4ea4\u6613\u6240\u9700\u7684\u6570\u5b66\u57fa\u7840\u77e5\u8bc6\uff0c\u660e\u786e\u5404\u6a21\u5757\u7684\u6280\u672f\u7528\u9014\uff0c\u5e76\u63d0\u4f9b\u4e00\u6761\u6e05\u6670\u3001\u53ef\u6267\u884c\u7684\u5b66\u4e60\u8def\u5f84\uff0c\u9002\u7528\u4e8e\u6709\u5fd7\u4e8e\u8fdb\u5165\u91cf\u5316\u9886\u57df\u7684\u521d\u5b66\u8005\u4e0e\u8f6c\u884c\u8005\u3002<\/p>\n<h3>\u4e8c\u3001\u91cf\u5316\u4ea4\u6613\u4e2d\u7684\u6570\u5b66\u77e5\u8bc6\u4f53\u7cfb<\/h3>\n<p>\u91cf\u5316\u4ea4\u6613\u6240\u4f9d\u8d56\u7684\u6570\u5b66\u77e5\u8bc6\u5e76\u975e\u6cdb\u6cdb\u800c\u8c08\u7684\u201c\u9ad8\u7b49\u6570\u5b66\u201d\uff0c\u800c\u662f\u56f4\u7ed5\u5efa\u6a21\u3001\u4f30\u8ba1\u3001\u4f18\u5316\u4e0e\u63a8\u65ad\u56db\u5927\u76ee\u6807\u6784\u5efa\u7684\u4e13\u95e8\u4f53\u7cfb\u3002<br \/>\n\u5176\u6838\u5fc3\u6a21\u5757\u5982\u4e0b\uff1a<\/p>\n<h4>1. \u6982\u7387\u8bba\u4e0e\u7edf\u8ba1\u5b66\uff08Probability &amp; Statistics\uff09<\/h4>\n<p>\u4f5c\u7528\uff1a \u662f\u91cf\u5316\u4ea4\u6613\u7684\u201c\u8bed\u8a00\u57fa\u7840\u201d\uff0c\u7528\u4e8e\u63cf\u8ff0\u5e02\u573a\u4e0d\u786e\u5b9a\u6027\u3001\u4f30\u8ba1\u53c2\u6570\u3001\u68c0\u9a8c\u7b56\u7565\u6709\u6548\u6027\u3002<\/p>\n<p>\u6838\u5fc3\u5185\u5bb9\uff1a<\/p>\n<ul>\n<li>\u00a0\u968f\u673a\u53d8\u91cf\u3001\u6982\u7387\u5206\u5e03\uff08\u6b63\u6001\u3001t\u3001\u6cca\u677e\u3001\u6307\u6570\uff09<\/li>\n<li>\u00a0\u671f\u671b\u3001\u65b9\u5dee\u3001\u534f\u65b9\u5dee\u3001\u76f8\u5173\u7cfb\u6570<\/li>\n<li>\u00a0\u6761\u4ef6\u6982\u7387\u3001\u8d1d\u53f6\u65af\u63a8\u65ad<\/li>\n<li>\u00a0\u5047\u8bbe\u68c0\u9a8c\uff08t\u68c0\u9a8c\u3001F\u68c0\u9a8c\u3001p\u503c\uff09<\/li>\n<li>\u00a0\u7f6e\u4fe1\u533a\u95f4\u3001\u663e\u8457\u6027\u6c34\u5e73<\/li>\n<li>\u00a0\u5927\u6570\u5b9a\u5f8b\u4e0e\u4e2d\u5fc3\u6781\u9650\u5b9a\u7406<\/li>\n<\/ul>\n<p>\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<ul>\n<li>\u7b56\u7565\u6536\u76ca\u5206\u5e03\u5efa\u6a21\uff1b\u98ce\u9669\u4ef7\u503c\uff08VaR\uff09\u8ba1\u7b97<\/li>\n<li>\u591a\u56e0\u5b50\u6a21\u578b\u4e2d\u7684\u663e\u8457\u6027\u68c0\u9a8c<\/li>\n<li>\u56de\u6d4b\u7ed3\u679c\u7684\u7edf\u8ba1\u6709\u6548\u6027\u5224\u65ad <\/li>\n<\/ul>\n<h4>2. \u7ebf\u6027\u4ee3\u6570\uff08Linear Algebra\uff09<\/h4>\n<p>\u4f5c\u7528\uff1a \u652f\u6491\u9ad8\u7ef4\u6570\u636e\u5904\u7406\u3001\u56e0\u5b50\u6a21\u578b\u3001\u6295\u8d44\u7ec4\u5408\u4f18\u5316\u4e0e\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u3002<\/p>\n<p>\u6838\u5fc3\u5185\u5bb9\uff1a<\/p>\n<ul>\n<li>\u00a0\u5411\u91cf\u3001\u77e9\u9635\u3001\u8f6c\u7f6e\u3001\u9006\u77e9\u9635<\/li>\n<li>\u00a0\u77e9\u9635\u4e58\u6cd5\u3001\u7279\u5f81\u503c\u4e0e\u7279\u5f81\u5411\u91cf<\/li>\n<li>\u00a0\u6b63\u5b9a\u77e9\u9635\u3001\u534f\u65b9\u5dee\u77e9\u9635<\/li>\n<li>\u00a0\u7ebf\u6027\u53d8\u6362\u4e0e\u6295\u5f71<\/li>\n<li>\u00a0\u5947\u5f02\u503c\u5206\u89e3\uff08SVD\uff09\u3001\u4e3b\u6210\u5206\u5206\u6790\uff08PCA\uff09<\/li>\n<\/ul>\n<p>\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<ul>\n<li>\u591a\u8d44\u4ea7\u6295\u8d44\u7ec4\u5408\u7684\u98ce\u9669\u534f\u65b9\u5dee\u77e9\u9635\u6784\u5efa<\/li>\n<li>\u56e0\u5b50\u8f7d\u8377\u77e9\u9635\u8fd0\u7b97<\/li>\n<li>PCA\u7528\u4e8e\u964d\u7ef4\u4e0e\u98ce\u9669\u56e0\u5b50\u63d0\u53d6<\/li>\n<li>\u673a\u5668\u5b66\u4e60\u6a21\u578b\u4e2d\u7684\u53c2\u6570\u77e9\u9635\u8fd0\u7b97<\/li>\n<\/ul>\n<h4>3. \u5fae\u79ef\u5206\u4e0e\u968f\u673a\u8fc7\u7a0b\uff08Calculus &amp; Stochastic Processes\uff09<\/h4>\n<p>\u4f5c\u7528\uff1a \u63cf\u8ff0\u53d8\u91cf\u52a8\u6001\u53d8\u5316\uff0c\u662f\u884d\u751f\u54c1\u5b9a\u4ef7\u4e0e\u9ad8\u9891\u4ea4\u6613\u5efa\u6a21\u7684\u7406\u8bba\u57fa\u7840\u3002<\/p>\n<p>\u6838\u5fc3\u5185\u5bb9\uff1a<\/p>\n<ul>\n<li>\u5bfc\u6570\u3001\u504f\u5bfc\u3001\u68af\u5ea6\u3001\u6cf0\u52d2\u5c55\u5f00<\/li>\n<li>\u79ef\u5206\u3001\u5fae\u5206\u65b9\u7a0b\uff08ODE\uff09<\/li>\n<li>\u968f\u673a\u5fae\u5206\u65b9\u7a0b\uff08SDE\uff09<\/li>\n<li>\u5e03\u6717\u8fd0\u52a8\uff08Brownian Motion\uff09\u3001\u51e0\u4f55\u5e03\u6717\u8fd0\u52a8<\/li>\n<li>\u4f0a\u85e4\u5f15\u7406\uff08It\u00f4&#8217;s Lemma\uff09<\/li>\n<li>\u9785\uff08Martingale\uff09\u3001\u505c\u65f6\uff08Stopping Time\uff09<\/li>\n<\/ul>\n<p>\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<ul>\n<li>Black-Scholes \u671f\u6743\u5b9a\u4ef7\u6a21\u578b\u63a8\u5bfc<\/li>\n<li>\u6ce2\u52a8\u7387\u5efa\u6a21\u4e0e\u8def\u5f84\u4f9d\u8d56\u884d\u751f\u54c1\u4f30\u503c<\/li>\n<li>\u9ad8\u9891\u4ea4\u6613\u4e2d\u7684\u8ba2\u5355\u6d41\u52a8\u6001\u5efa\u6a21<\/li>\n<li>\u7b97\u6cd5\u4ea4\u6613\u4e2d\u7684\u6700\u4f18\u6267\u884c\u8def\u5f84\u8bbe\u8ba1<\/li>\n<\/ul>\n<h4>4.  \u4f18\u5316\u7406\u8bba\uff08Optimization\uff09<\/h4>\n<p>\u4f5c\u7528\uff1a \u5b9e\u73b0\u6295\u8d44\u7ec4\u5408\u6784\u5efa\u3001\u53c2\u6570\u8c03\u4f18\u4e0e\u8d44\u6e90\u5206\u914d\u7684\u6700\u4f18\u5316\u3002<\/p>\n<p>\u6838\u5fc3\u5185\u5bb9\uff1a<\/p>\n<ul>\n<li>\u7ebf\u6027\u89c4\u5212\uff08LP\uff09\u3001\u4e8c\u6b21\u89c4\u5212\uff08QP\uff09<\/li>\n<li>\u51f8\u4f18\u5316\u3001\u62c9\u683c\u6717\u65e5\u4e58\u5b50\u6cd5<\/li>\n<li>\u7ea6\u675f\u4f18\u5316\u4e0eKKT\u6761\u4ef6<\/li>\n<li>\u9ed1\u7bb1\u4f18\u5316\uff1a\u9057\u4f20\u7b97\u6cd5\u3001\u7c92\u5b50\u7fa4\u3001\u8d1d\u53f6\u65af\u4f18\u5316<\/li>\n<li>\u52a8\u6001\u89c4\u5212\uff08DP\uff09<\/li>\n<\/ul>\n<p>\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<ul>\n<li>Markowitz \u5747\u503c-\u65b9\u5dee\u6295\u8d44\u7ec4\u5408\u4f18\u5316<\/li>\n<li>\u591a\u56e0\u5b50\u6a21\u578b\u6743\u91cd\u6c42\u89e3<\/li>\n<li>\u7b56\u7565\u53c2\u6570\u7f51\u683c\u641c\u7d22\u4e0e\u8c03\u4f18<\/li>\n<li>\u98ce\u9669\u9884\u7b97\u5206\u914d\u4e0e\u6760\u6746\u4f18\u5316<\/li>\n<\/ul>\n<h4>5.  \u65f6\u95f4\u5e8f\u5217\u5206\u6790\uff08Time Series Analysis\uff09<\/h4>\n<p>\u4f5c\u7528\uff1a \u5904\u7406\u91d1\u878d\u6570\u636e\u7684\u6838\u5fc3\u5de5\u5177\uff0c\u56e0\u91d1\u878d\u6570\u636e\u672c\u8d28\u4e0a\u662f\u65f6\u95f4\u4f9d\u8d56\u7684\u3002<\/p>\n<p>\u6838\u5fc3\u5185\u5bb9\uff1a<\/p>\n<ul>\n<li>\u5e73\u7a33\u6027\u3001\u81ea\u76f8\u5173\u51fd\u6570\uff08ACF\uff09\u3001\u504f\u81ea\u76f8\u5173\u51fd\u6570\uff08PACF\uff09<\/li>\n<li>AR\u3001MA\u3001ARMA\u3001ARIMA \u6a21\u578b<\/li>\n<li>GARCH\u3001EGARCH\u3001TGARCH \u6ce2\u52a8\u7387\u5efa\u6a21<\/li>\n<li>\u534f\u6574\u5173\u7cfb\u3001\u8bef\u5dee\u4fee\u6b63\u6a21\u578b\uff08ECM\uff09<\/li>\n<li>\u72b6\u6001\u7a7a\u95f4\u6a21\u578b\u4e0e\u5361\u5c14\u66fc\u6ee4\u6ce2<\/li>\n<\/ul>\n<p>\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<ul>\n<li>\u8d8b\u52bf\u8ddf\u8e2a\u7b56\u7565\u5efa\u6a21<\/li>\n<li>\u6ce2\u52a8\u7387\u9884\u6d4b\u4e0e\u98ce\u9669\u63a7\u5236<\/li>\n<li>\u7edf\u8ba1\u5957\u5229\uff08\u5982\u914d\u5bf9\u4ea4\u6613\uff09<\/li>\n<li>\u9ad8\u9891\u8ba2\u5355\u6d41\u5efa\u6a21<\/li>\n<\/ul>\n<h4>6.  \u6570\u503c\u65b9\u6cd5\u4e0e\u8ba1\u7b97\u6570\u5b66\uff08Numerical Methods\uff09<\/h4>\n<p>\u4f5c\u7528\uff1a \u5c06\u7406\u8bba\u6a21\u578b\u8f6c\u5316\u4e3a\u53ef\u8ba1\u7b97\u7684\u7b97\u6cd5\u3002<\/p>\n<p>\u6838\u5fc3\u5185\u5bb9\uff1a<\/p>\n<ul>\n<li>\u6570\u503c\u79ef\u5206\u3001\u8499\u7279\u5361\u6d1b\u6a21\u62df<\/li>\n<li>\u6709\u9650\u5dee\u5206\u6cd5\uff08FDM\uff09\u7528\u4e8ePDE\u6c42\u89e3<\/li>\n<li>\u975e\u7ebf\u6027\u65b9\u7a0b\u6c42\u89e3\uff08\u725b\u987f\u6cd5\uff09<\/li>\n<li>\u77e9\u9635\u5206\u89e3\uff08LU\u3001QR\u3001Cholesky\uff09<\/li>\n<li>\u5e76\u884c\u8ba1\u7b97\u4e0eGPU\u52a0\u901f\u57fa\u7840<\/li>\n<\/ul>\n<p>\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<ul>\n<li>\u671f\u6743\u5b9a\u4ef7\u7684\u8499\u7279\u5361\u6d1b\u6a21\u62df<\/li>\n<li>\u9690\u542b\u6ce2\u52a8\u7387\u6c42\u89e3<\/li>\n<li>\u5927\u89c4\u6a21\u56de\u6d4b\u4e2d\u7684\u77e9\u9635\u8fd0\u7b97\u52a0\u901f<\/li>\n<\/ul>\n<h3>\u4e09\u3001\u91cf\u5316\u4ea4\u6613\u6570\u5b66\u5b66\u4e60\u8def\u5f84\uff08\u5206\u9636\u6bb5\u3001\u53ef\u6267\u884c\uff09<\/h3>\n<p>\u4ee5\u4e0b\u8def\u5f84\u9002\u7528\u4e8e\u975e\u6570\u5b66\u80cc\u666f\u4f46\u6709\u5b66\u4e60\u610f\u613f\u7684\u521d\u5b66\u8005\uff0c\u5efa\u8bae\u5b66\u4e60\u5468\u671f\u4e3a 6\u201312\u4e2a\u6708\uff0c\u6bcf\u65e5\u6295\u51651.5\u20132\u5c0f\u65f6\u3002<\/p>\n<h4>\u7b2c\u4e00\u9636\u6bb5\uff1a\u6253\u7262\u57fa\u7840\uff081\u20133\u4e2a\u6708\uff09<\/h4>\n<p>\u76ee\u6807\uff1a \u638c\u63e1\u91cf\u5316\u6240\u9700\u7684\u6570\u5b66\u8bed\u8a00\uff0c\u6d88\u9664\u77e5\u8bc6\u76f2\u533a\u3002<\/p>\n<table>\n<thead>\n<tr>\n<th>\u5185\u5bb9<\/th>\n<th>\u63a8\u8350\u8d44\u6e90<\/th>\n<th>\u5b66\u4e60\u91cd\u70b9<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u6982\u7387\u4e0e\u7edf\u8ba1<\/td>\n<td>\u300a\u6982\u7387\u8bba\u4e0e\u6570\u7406\u7edf\u8ba1\u300b\uff08\u9648\u5e0c\u5b7a\uff09<\/td>\n<td>\u968f\u673a\u53d8\u91cf\u3001\u5206\u5e03\u3001\u5047\u8bbe\u68c0\u9a8c<\/td>\n<\/tr>\n<tr>\n<td>\u7ebf\u6027\u4ee3\u6570<\/td>\n<td>\u300a\u7ebf\u6027\u4ee3\u6570\u5e94\u8be5\u8fd9\u6837\u5b66\u300b\uff08Sheldon Axler\uff09<\/td>\n<td>\u77e9\u9635\u8fd0\u7b97\u3001\u7279\u5f81\u503c\u3001PCA<\/td>\n<\/tr>\n<tr>\n<td>\u5fae\u79ef\u5206<\/td>\n<td>\u300a\u6258\u9a6c\u65af\u5fae\u79ef\u5206\u300b\u6216 MIT OpenCourseWare<\/td>\n<td>\u504f\u5bfc\u3001\u68af\u5ea6\u3001\u79ef\u5206<\/td>\n<\/tr>\n<tr>\n<td>Python \u6570\u5b66\u5b9e\u8df5<\/td>\n<td>\u4f7f\u7528 NumPy\u3001SciPy<\/td>\n<td>\u5b9e\u73b0\u77e9\u9635\u8fd0\u7b97\u3001\u5206\u5e03\u6a21\u62df<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u5b9e\u8df5\u4efb\u52a1\uff1a<\/p>\n<ul>\n<li>\u7528 Python \u6a21\u62df\u6b63\u6001\u5206\u5e03\u3001\u8ba1\u7b97\u534f\u65b9\u5dee\u77e9\u9635<\/li>\n<li>\u5b9e\u73b0\u7b80\u5355\u7684\u7ebf\u6027\u56de\u5f52\u5e76\u53ef\u89c6\u5316<\/li>\n<li>\u7f16\u5199\u4ee3\u7801\u8ba1\u7b97 Sharpe Ratio\u3001VaR<\/li>\n<\/ul>\n<h4>\u7b2c\u4e8c\u9636\u6bb5\uff1a\u8fdb\u9636\u5efa\u6a21\uff084\u20136\u4e2a\u6708\uff09<\/h4>\n<p>\u76ee\u6807\uff1a 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&amp; Kahn\uff09<\/td>\n<td>\u591a\u56e0\u5b50\u6a21\u578b\u3001\u4fe1\u606f\u6bd4\u7387<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u5b9e\u8df5\u4efb\u52a1\uff1a<\/p>\n<ul>\n<li>\u7528 ARIMA \u6a21\u578b\u9884\u6d4b\u80a1\u7968\u6536\u76ca\u7387<\/li>\n<li>\u5b9e\u73b0 GARCH \u6a21\u578b\u4f30\u8ba1\u6ce2\u52a8\u7387<\/li>\n<li>\u4f7f\u7528 cvxpy \u6c42\u89e3\u7b80\u5355\u6295\u8d44\u7ec4\u5408\u4f18\u5316\u95ee\u9898<\/li>\n<\/ul>\n<h4>\u7b2c\u4e09\u9636\u6bb5\uff1a\u5b9e\u6218\u6574\u5408\uff087\u201312\u4e2a\u6708\uff09<\/h4>\n<p>\u76ee\u6807\uff1a \u5c06\u6570\u5b66\u77e5\u8bc6\u5e94\u7528\u4e8e\u771f\u5b9e\u91cf\u5316\u6d41\u7a0b\uff0c\u5b8c\u6210\u7aef\u5230\u7aef\u9879\u76ee\u3002<\/p>\n<p>| \u5185\u5bb9 | \u63a8\u8350\u8d44\u6e90 | \u5b66\u4e60\u91cd\u70b9 |\n| &#8212;- | &#8212;- | &#8212;- |\u56de\u6d4b\u7cfb\u7edf\u642d\u5efa\n| Zipline\u3001Backtrader \u6587\u6863 | \u4fe1\u53f7\u751f\u6210\u3001\u4ed3\u4f4d\u7ba1\u7406 | \u591a\u56e0\u5b50\u6a21\u578b |\n| \u300a\u56e0\u5b50\u6295\u8d44\u300b\uff08Barra \u6587\u6863\uff09 | \u56e0\u5b50\u6784\u5efa\u3001\u6807\u51c6\u5316\u3001\u5408\u6210 |\n|  \u98ce\u9669\u7ba1\u7406 |  \u300a\u91cf\u5316\u98ce\u9669\u7ba1\u7406\u300b\uff08McNeil et al.\uff09 | VaR\u3001ES\u3001\u538b\u529b\u6d4b\u8bd5 |\n|  \u673a\u5668\u5b66\u4e60\u4e0e\u91cf\u5316 | \u300aAdvances in Financial Machine Learning\u300b\uff08Lopez de Prado\uff09| \u7279\u5f81\u5de5\u7a0b\u3001\u8fc7\u62df\u5408\u9632\u8303<\/p>\n<p>\u5b9e\u8df5\u9879\u76ee\uff1a\n1.\u00a0\u6784\u5efa\u4e00\u4e2a\u57fa\u4e8e\u52a8\u91cf\u4e0e\u6ce2\u52a8\u7387\u56e0\u5b50\u7684\u591a\u56e0\u5b50\u9009\u80a1\u6a21\u578b\n2.\u00a0\u4f7f\u7528 GARCH \u9884\u6d4b\u6ce2\u52a8\u7387\u5e76\u52a8\u6001\u8c03\u6574\u4ed3\u4f4d\n3.\u00a0\u5b9e\u73b0\u4e00\u4e2a\u7b80\u5355\u7684\u7edf\u8ba1\u5957\u5229\u7b56\u7565\uff08\u5982\u914d\u5bf9\u4ea4\u6613\uff09\n4.\u00a0\u5b8c\u6574\u56de\u6d4b + 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Pandas\u3001NumPy\u3001Statsmodels\u3001Scikit-learn\u3002<\/li>\n<li>\u907f\u514d\u201c\u7eb8\u4e0a\u8c08\u5175\u201d\uff1a\u6bcf\u5b66\u4e00\u4e2a\u6a21\u578b\uff0c\u5fc5\u987b\u52a8\u624b\u5b9e\u73b0\uff0c\u7528\u771f\u5b9e\u6216\u6a21\u62df\u6570\u636e\u9a8c\u8bc1\u3002<\/li>\n<li>\u00a0\u91cd\u89c6\u6570\u636e\u8d28\u91cf\uff1a\u5783\u573e\u8fdb\uff0c\u5783\u573e\u51fa\u3002\u5b66\u4e60\u6570\u636e\u6e05\u6d17\u3001\u53bb\u566a\u3001\u6807\u51c6\u5316\u65b9\u6cd5\u3002<\/li>\n<li>\u00a0\u8b66\u60d5\u8fc7\u62df\u5408\uff1a\u56de\u6d4b\u7ed3\u679c\u8981\u8fdb\u884c\u6837\u672c\u5916\u6d4b\u8bd5\u3001\u4ea4\u53c9\u9a8c\u8bc1\u4e0e\u8499\u7279\u5361\u6d1b\u6a21\u62df\u3002<\/li>\n<li>\u6301\u7eed\u8ddf\u8e2a\u76d1\u7ba1\u4e0e\u5e02\u573a\u53d8\u5316\uff1a\u59822025\u5e74A\u80a1\u7a0b\u5e8f\u5316\u4ea4\u6613\u65b0\u89c4\u5b9e\u65bd\u540e\uff0c\u9ad8\u9891\u7b56\u7565\u9700\u8c03\u6574\uff0c\u4e2d\u4f4e\u9891\u7ade\u4e89\u52a0\u5267\u3002<\/li>\n<\/ol>\n<h3>\u4e94\u3001\u7ed3\u8bed<\/h3>\n<p>\u91cf\u5316\u4ea4\u6613\u662f\u4e00\u95e8\u79d1\u5b66\u4e0e\u827a\u672f\u7ed3\u5408\u7684\u5b9e\u8df5\u5b66\u79d1\u3002\u6570\u5b66\u662f\u5176\u79d1\u5b66\u6027\u7684\u57fa\u77f3\uff0c\u51b3\u5b9a\u4e86\u6a21\u578b\u7684\u4e25\u8c28\u6027\u4e0e\u53ef\u89e3\u91ca\u6027\u3002\u6ca1\u6709\u624e\u5b9e\u7684\u6570\u5b66\u57fa\u7840\uff0c\u4efb\u4f55\u201c\u7b56\u7565\u7075\u611f\u201d\u90fd\u53ea\u662f\u7a7a\u4e2d\u697c\u9601\u3002<br \/>\n\u638c\u63e1\u4e0a\u8ff0\u6570\u5b66\u77e5\u8bc6\uff0c\u5e76\u6309\u7167\u7cfb\u7edf\u8def\u5f84\u6301\u7eed\u5b66\u4e60\u4e0e\u5b9e\u8df5\uff0c\u4f60\u5c06\u5177\u5907\u8fdb\u5165\u91cf\u5316\u9886\u57df\u7684\u6838\u5fc3\u7ade\u4e89\u529b\u3002\u65e0\u8bba\u4f60\u662f\u91d1\u878d\u3001\u5de5\u7a0b\u3001\u6570\u5b66\u6216\u8ba1\u7b97\u673a\u80cc\u666f\uff0c\u53ea\u8981\u65b9\u6cd5\u5f97\u5f53\u3001\u575a\u6301\u6267\u884c\uff0c\u7ec8\u5c06\u5728\u8fd9\u6761\u9ad8\u95e8\u69db\u3001\u9ad8\u56de\u62a5\u7684\u9053\u8def\u4e0a\u8d70\u5f97\u66f4\u8fdc\u3002<br \/>\n\u8bb0\u4f4f\uff1a\u91cf\u5316\u4ea4\u6613\u7684\u7ec8\u6781\u76ee\u6807\u4e0d\u662f\u201c\u9884\u6d4b\u5e02\u573a\u201d\uff0c\u800c\u662f\u201c\u5728\u4e0d\u786e\u5b9a\u6027\u4e2d\u5efa\u7acb\u53ef\u6301\u7eed\u7684\u6b63\u671f\u671b\u7cfb\u7edf\u201d\u3002\u800c\u6570\u5b66\uff0c\u6b63\u662f\u4f60\u6784\u5efa\u8fd9\u4e00\u7cfb\u7edf\u7684\u552f\u4e00\u53ef\u9760\u5de5\u5177\u3002<\/p>\n<h3>\u53c2\u8003\u6587\u732e\uff1a<\/h3>\n<ul>\n<li>\u00a0Grinold &amp; Kahn, Active Portfolio Management<\/li>\n<li>\u00a0Hull, Options, Futures and Other Derivatives<\/li>\n<li>\u00a0McNeil et al., Quantitative Risk Management<\/li>\n<li>\u00a0Lopez de Prado, Advances in Financial Machine Learning<\/li>\n<li>\u00a0\u56fd\u5185\u91cf\u5316\u76d1\u7ba1\u653f\u7b56\u6587\u4ef6\uff082024\u20132025\uff09 2, 9, 11<\/li>\n<li>\u00a0\u91cf\u5316\u4ea4\u6613\u5e02\u573a\u5360\u6bd4\u6570\u636e\uff082025\u5e74A\u80a130%\uff09 2<\/li>\n<li>\u00a0\u6295\u8d44\u7ec4\u5408\u4f18\u5316\u4e0e\u56e0\u5b50\u6a21\u578b\u7406\u8bba\u57fa\u7840 3\u20134, 7<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>\u4e00\u3001\u5f15\u8a00 \u91cf\u5316\u4ea4\u6613\uff08Quantitative Trading\uff09\u662f\u73b0\u4ee3\u91d1\u878d\u5e02\u573a\u4e2d\u9ad8\u5ea6\u4f9d\u8d56\u6570\u5b66\u3001\u7edf\u8ba1\u5b66\u4e0e\u8ba1\u7b97\u673a\u6280\u672f &#8230; <a title=\"\u91cf\u5316\u4ea4\u6613\u6570\u5b66\u57fa\u7840\u53ca\u5b66\u4e60\u8def\u5f84\" class=\"read-more\" href=\"http:\/\/xuebuwan.com\/wp\/?p=398\" aria-label=\"\u9605\u8bfb 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