{"id":2515,"date":"2025-08-26T07:14:00","date_gmt":"2025-08-25T23:14:00","guid":{"rendered":"https:\/\/blog.laoyulaoyu.top\/?p=2515"},"modified":"2025-08-23T00:16:13","modified_gmt":"2025-08-22T16:16:13","slug":"%e8%9d%b4%e8%9d%b6%e6%95%88%e5%ba%94%e6%93%8d%e7%9b%98%e6%b3%95%ef%bc%9a3%e6%ad%a5%e7%94%a8python%e6%8a%93%e4%bd%8f%e5%b8%82%e5%9c%ba%e5%8f%98%e8%84%b8%e6%97%b6%e5%88%bb%ef%bc%88%e9%99%84%e5%ae%8c","status":"publish","type":"post","link":"https:\/\/laoyulaoyu.com\/index.php\/2025\/08\/26\/%e8%9d%b4%e8%9d%b6%e6%95%88%e5%ba%94%e6%93%8d%e7%9b%98%e6%b3%95%ef%bc%9a3%e6%ad%a5%e7%94%a8python%e6%8a%93%e4%bd%8f%e5%b8%82%e5%9c%ba%e5%8f%98%e8%84%b8%e6%97%b6%e5%88%bb%ef%bc%88%e9%99%84%e5%ae%8c\/","title":{"rendered":"\u8774\u8776\u6548\u5e94\u64cd\u76d8\u6cd5\uff1a3\u6b65\u7528Python\u6293\u4f4f\u5e02\u573a”\u53d8\u8138\u65f6\u523b”\uff08\u9644\u5b8c\u6574\u6e90\u4ee3\u7801\uff09"},"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>\u4f5c\u4e3a\u4ea4\u6613\u8005\uff0c\u4f1a\u82e6\u4e8e\u4f20\u7edf\u6307\u6807\u7684\u6ede\u540e\u6027\u4e0e\u5047\u4fe1\u53f7\uff0c\u76f4\u5230\u4eba\u4eec\u5c06\u6df7\u6c8c\u7406\u8bba\u4e2d\u7684\u6d1b\u4f26\u5179\u516c\u5f0f\u5e94\u7528\u4e8e\u4ea4\u6613\u7b56\u7565\u3002\u4ece\u7ed3\u679c\u6765\u770b\uff0c\u6bd4\u5e94\u7528\u4f20\u7edf\u6307\u6807\u7684Sharpe\u6bd4\u7387\u63d0\u534722%\u3002<\/mark>\u6211\u4eca\u5929\u5c31\u7528Python\u4ee3\u7801\u6a21\u62df\u5b83\uff0c\u7ed3\u5408\u771f\u5b9e\u6570\u636e\uff0c\u6559\u5927\u5bb6\u68c0\u6d4b\u5e02\u573a\u8f6c\u6298\u70b9\u3002<\/pre>\n<\/blockquote>\n\n\n\n
\u4e00\u3001\u4f20\u7edf\u6280\u672f\u6307\u6807\u7684\u56f0\u5c40<\/strong><\/h2>\n\n\n\n
\u5982\u679c\u4f60\u7528\u8fc7RSI\u3001MACD\u6216\u5e03\u6797\u5e26\uff0c\u80af\u5b9a\u7ecf\u5386\u8fc7\u8fd9\u79cd\u60c5\u51b5\uff1a\u6307\u6807\u544a\u8bc9\u4f60\u4e70\u5165\u65f6\uff0c\u5e02\u573a\u5df2\u7ecf\u5f00\u59cb\u4e0b\u8dcc\u4e86\uff1b\u6307\u6807\u663e\u793a\u5356\u51fa\u65f6\uff0c\u884c\u60c5\u5374\u4e00\u8def\u66b4\u6da8\u3002<\/p>\n\n\n\n
\u4e3a\u4ec0\u4e48\u8fd9\u4e9b\u6307\u6807\u603b\u6162\u534a\u62cd\uff1f<\/p>\n\n\n\n
\u6839\u672c\u539f\u56e0\u5728\u4e8e\uff1a\u4f20\u7edf\u6307\u6807\u57fa\u4e8e\u5386\u53f2\u6570\u636e\u8ba1\u7b97\uff0c\u6c38\u8fdc\u6ede\u540e\u4e8e\u5e02\u573a<\/strong>\u3002\u5b83\u4eec\u5047\u8bbe\u5e02\u573a\u662f\u7ebf\u6027\u7684\uff0c\u4f46\u73b0\u5b9e\u662f\u2014\u2014\u5e02\u573a\u5145\u6ee1\u975e\u7ebf\u6027\u6df7\u6c8c\u3002<\/p>\n\n\n\n
\u5c31\u50cf\u7528\u81ea\u884c\u8f66\u540e\u89c6\u955c\u5f00F1\u8d5b\u8f66\uff0c\u4e0d\u4ec5\u5371\u9669\uff0c\u800c\u4e14\u6ce8\u5b9a\u5931\u8d25\uff01<\/p>\n\n\n\n
\u6563\u6237\u4e09\u5927\u8840\u6cea\u75db\u70b9<\/strong>\uff1a<\/p>\n\n\n\n
\u2705 \u4fe1\u53f7\u6ede\u540e\uff1a\u7b49\u91d1\u53c9\u51fa\u73b0\uff0c\u4ef7\u683c\u65e9\u98de\u4e86\u3002
\u2705 \u5047\u4fe1\u53f7\u591a\uff1a\u9707\u8361\u884c\u60c5\u91cc\u88ab\u53cd\u590d\u6253\u8138\u3002
\u2705 \u53c2\u6570\u8fc7\u62df\u5408\uff1a\u5386\u53f2\u56de\u6d4b\u7f8e\u5982\u753b\uff0c\u5b9e\u76d8\u4e8f\u5230\u54ed\u3002<\/p>\n\n\n\n
\u771f\u76f8<\/strong>\uff1a\u5e02\u573a\u4e0d\u662f\u5300\u901f\u8dd1\u6b65\u673a\uff0c\u800c\u662f\u8fc7\u5c71\u8f66\uff01\u4f20\u7edf\u6307\u6807\u50cf\u8fd1\u89c6\u773c\u955c\uff0c\u770b\u4e0d\u6e05\u5f2f\u9053\u3002<\/p>\n\n\n\n
\u4e8c\u3001\u8774\u8776\u6548\u5e94\u8ba9\u80a1\u5e02\u5730\u9707\uff1f\uff08\u6df7\u6c8c\u4ea4\u6613\u539f\u7406\uff09<\/strong><\/h2>\n\n\n\n
1963\u5e74\uff0c\u6c14\u8c61\u5b66\u5bb6\u6d1b\u4f26\u5179\u53d1\u73b0\uff1a\u5df4\u897f\u8774\u8776\u6247\u7fc5\u8180\uff0c\u53ef\u80fd\u5f15\u53d1\u5fb7\u5dde\u9f99\u5377\u98ce<\/strong>\u3002<\/p>\n\n\n\n
\u4ed6\u641e\u51fa\u7684”\u8774\u8776\u65b9\u7a0b”\uff0c\u8fd9\u7ec4\u516c\u5f0f\u6700\u521d\u7528\u4e8e\u5929\u6c14\u9884\u62a5\uff1a<\/p>\n\n\n\n
dx\/dt = \u03c3 (y\u2212x)\ndy\/dt = x (\u03c1\u2212z) \u2212 y\ndz\/dt = xy \u2212 \u03b2z<\/code><\/pre>\n\n\n\n
“\u8774\u8776\u65b9\u7a0b”\u5173\u952e\u53c2\u6570\u91ca\u4e49<\/strong>\uff1a<\/p>\n\n\n\n
    \n
  • \u03c3\uff08Sigma\uff09<\/strong> \u2192 \u5e02\u573a”\u66b4\u813e\u6c14”\u6307\u6570\uff08\u6570\u503c\u8d8a\u5927\u8d8a\u5bb9\u6613\u66b4\u6da8\u66b4\u8dcc\uff09\u3002<\/li>\n\n\n\n
  • \u03c1\uff08Rho\uff09<\/strong> \u2192 \u591a\u7a7a\u529b\u91cf\u5929\u5e73\uff08>28=\u8d8b\u52bf\u884c\u60c5\uff0c<28=\u9707\u8361\u884c\u60c5\uff09\u3002<\/li>\n\n\n\n
  • \u03b2\uff08Beta\uff09<\/strong> \u2192 \u60c5\u7eea\u51b7\u5374\u901f\u5ea6\uff08\u6570\u503c\u5927=\u53cd\u5f39\u5feb\uff0c\u6570\u503c\u5c0f=\u9634\u8dcc\u4e45\uff09\u3002<\/li>\n<\/ul>\n\n\n\n
    \u4f46\u5929\u624d\u7684\u4ea4\u6613\u8005\u53d1\u73b0\uff0c\u5e02\u573a\u672c\u8d28\u4e0a\u5c31\u662f\u4e00\u4e2a\u6df7\u6c8c\u7cfb\u7edf\uff1a<\/p>\n\n\n\n
      \n
    • \u8d8b\u52bf\u884c\u60c5\uff08\u725b\u5e02\/\u718a\u5e02\uff09<\/li>\n\n\n\n
    • \u9707\u8361\u884c\u60c5\uff08\u6a2a\u76d8\u6574\u7406\uff09<\/li>\n\n\n\n
    • \u7a81\u53d8\u884c\u60c5\uff08\u9ed1\u5929\u9e45\u4e8b\u4ef6\uff09<\/li>\n<\/ul>\n\n\n\n
      \u800c\u6d1b\u4f26\u5179\u516c\u5f0f\u7684\u4f18\u52bf<\/strong>\u5728\u4e8e\uff1a<\/p>\n\n\n\n
      \u4f20\u7edf\u6307\u6807<\/th>\u6df7\u6c8c\u4ea4\u6613\u6cd5<\/th><\/tr><\/thead>
      \u770b\u5386\u53f2\u6570\u636e\uff08\u53cd\u5e94\u6162\uff09<\/td>\u6355\u6349\u5e02\u573a\u60c5\u7eea\uff08\u9884\u5224\u5feb\uff09<\/td><\/tr>
      \u9002\u5408\u5e73\u7a33\u884c\u60c5<\/td>\u4e13\u6cbb\u66b4\u6da8\u66b4\u8dcc<\/td><\/tr>
      \u53c2\u6570\u56fa\u5b9a\u6b7b\u677f<\/td>\u52a8\u6001\u9002\u5e94\u5e02\u573a\u53d8\u5316<\/td><\/tr>
      \u88ab\u4e3b\u529b\u53cd\u590d\u6536\u5272<\/td>\u63d0\u524d\u53d1\u73b0\u4e3b\u529b\u52a8\u5411<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \u4e3e\u4e2a\u6817\u5b50<\/strong>\uff1a<\/p>\n\n\n\n
      \u5f53\u03b2\u7a81\u7136\u53d8\u5c0f\uff0c\u5c31\u50cf\u706b\u9505\u7184\u706b\u2014\u2014\u8868\u9762\u5e73\u9759\uff0c\u5e95\u4e0b\u6697\u6d41\u6d8c\u52a8\uff01\u6b64\u65f6\u8d76\u7d27\u51cf\u4ed3\uff0c\u7b49\u03b2\u56de\u5347\u518d\u6740\u56de\u9a6c\u67aa\uff0c\u8eb2\u8fc790%\u7684\u95ea\u5d29\u3002<\/p>\n\n\n\n
      \u4e09\u3001\u624b\u628a\u624b\u6559\u5b66\uff1a5\u5206\u949f\u642d\u5efa”\u8774\u8776\u9884\u8b66\u7cfb\u7edf”<\/strong><\/h2>\n\n\n\n
      \u63a5\u4e0b\u6765\u662f\u5b9e\u6218\u73af\u8282\uff01\u6211\u4eec\u5c06\u7528Python\u6784\u5efa\u4e00\u4e2a\u5b8c\u6574\u7684\u6d1b\u4f26\u5179\u4ea4\u6613\u5206\u6790\u7cfb\u7edf\u3002<\/p>\n\n\n\n
      \u7b2c\u4e00\u6b65\uff1a\u5b89\u88c5\u5fc5\u5907\u5de5\u5177\uff0830\u79d2\u641e\u5b9a\uff09<\/strong><\/h3>\n\n\n\n
      # \u521d\u6b21\u4f7f\u7528\u5b89\u88c5\npip install numpy scipy matplotlib pandas mplfinance\n\n# \u5bfc\u5165\u6240\u9700\u5e93\nimport numpy as np\nfrom scipy.integrate import odeint\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport mplfinance as mpf<\/code><\/pre>\n\n\n\n
      \u5982\u679c\u62a5\u9519”\u7f51\u7edc\u8d85\u65f6”\uff0c\u52a0\u4e2a\u56fd\u5185\u955c\u50cf\u6e90\uff1a<\/p>\n\n\n\n
      pip install -i https:\/\/pypi.tuna.tsinghua.edu.cn\/simple numpy<\/code><\/p>\n\n\n\n
      \u7b2c\u4e8c\u6b65\uff1a\u5b9a\u4e49\u6d1b\u4f26\u5179\u7cfb\u7edf<\/strong><\/strong><\/h3>\n\n\n\n
      \u8fd0\u884c\u4e0b\u9762\u7684\u4ee3\u7801\u4f60\u5c31\u80fd\u770b\u5230\u4e00\u4e2a\u7f8e\u4e3d\u7684\u8774\u8776\u72b6\u56fe\u5f62\uff0c\u8fd9\u5c31\u662f\u6df7\u6c8c\u7cfb\u7edf\u4e2d\u9690\u85cf\u7684\u79e9\u5e8f\uff01<\/p>\n\n\n\n
      \"\"<\/figure>\n\n\n\n
      \u5b8c\u6574\u6e90\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n
      \n# \u5b9a\u4e49\u6d1b\u4f26\u5179\u65b9\u7a0b\ndef lorenz_system(state, t, sigma=10, rho=28, beta=2.667):\n\n    \"\"\"\n    \u8ba1\u7b97\u6d1b\u4f26\u5179\u7cfb\u7edf\u7684\u5fae\u5206\u65b9\u7a0b\n    \u53c2\u6570:\n    state: \u5f53\u524d\u72b6\u6001 [x, y, z]\n    t: \u65f6\u95f4\uff08\u672a\u4f7f\u7528\uff0c\u4f46odeint\u9700\u8981\uff09\n    sigma: \u6ce2\u52a8\u7387\u56e0\u5b50\n    rho: \u884c\u60c5\u9a71\u52a8\u56e0\u5b50\n    beta: \u8870\u51cf\u7387\n    \"\"\"\n    x, y, z = state\n    \n    dx_dt = sigma * (y - x)\n    dy_dt = x * (rho - z) - y\n    dz_dt = x * y - beta * z\n    \n    return [dx_dt, dy_dt, dz_dt]\n\n# \u8bbe\u7f6e\u521d\u59cb\u72b6\u6001\u548c\u65f6\u95f4\u70b9\ninitial_state = [1.0, 1.0, 1.0]\nt = np.arange(0, 50, 0.01)\n\n# \u6c42\u89e3\u5fae\u5206\u65b9\u7a0b\nstates = odeint(lorenz_system, initial_state, t)\n\n# \u7ed8\u5236\u8457\u540d\u7684\u6d1b\u4f26\u5179\u5438\u5f15\u5b50\u56fe\nplt.figure(figsize=(10, 6))\nplt.plot(states[:, 0], states[:, 2], lw=0.5, color='blue')\nplt.title('Lorenz Attractor - Beauty of Chaos')\nplt.xlabel('X Axis - Price Trend')\nplt.ylabel('Z Axis - Volatility Accumulation')\nplt.grid(True)\nplt.show()<\/code><\/pre>\n\n\n\n
      \u7b2c\u4e09\u6b65\uff1a\u5c06\u4ef7\u683c\u6570\u636e\u6620\u5c04\u5230\u6d1b\u4f26\u5179\u7cfb\u7edf<\/strong><\/h3>\n\n\n\n
      \u8fd9\u5f20\u56fe\u662f\u539f\u59cb\u4ef7\u683c\u5e8f\u5217\u548c\u6d1b\u4f26\u5179\u7cfb\u7edf\u72b6\u6001\u7684\u5173\u7cfb\u6620\u5c04\u56fe\u3002<\/p>\n\n\n\n
      \"\"<\/figure>\n\n\n\n
      \u5b8c\u6574\u6e90\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n
      # \u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u80a1\u7968\u6216\u52a0\u5bc6\u8d27\u5e01\u7684\u4ef7\u683c\u6570\u636e\n# \u8fd9\u91cc\u6211\u4eec\u751f\u6210\u6a21\u62df\u4ef7\u683c\u6570\u636e\u4f5c\u4e3a\u793a\u4f8b\nnp.random.seed(42)\nn_points = 1000\nprice_data = np.cumsum(np.random.randn(n_points)) + 100\n\n# \u6807\u51c6\u5316\u4ef7\u683c\u6570\u636e\ndef normalize_data(data):\n    \"\"\"\u5c06\u6570\u636e\u6807\u51c6\u5316\u5230-1\u52301\u8303\u56f4\"\"\"\n    return 2 * (data - np.min(data)) \/ (np.max(data) - np.min(data)) - 1\n\nnormalized_prices = normalize_data(price_data)\n\n# \u5c06\u6807\u51c6\u5316\u540e\u7684\u4ef7\u683c\u6620\u5c04\u5230\u6d1b\u4f26\u5179\u7cfb\u7edf\u53c2\u6570\n# \u8fd9\u91cc\u662f\u4e00\u79cd\u7b80\u5316\u65b9\u6cd5\uff0c\u5b9e\u9645\u5e94\u7528\u53ef\u80fd\u9700\u8981\u66f4\u590d\u6742\u7684\u6620\u5c04\ndef map_to_lorenz(prices, sigma=10, rho=28, beta=2.667):\n    \"\"\"\n    \u5c06\u4ef7\u683c\u5e8f\u5217\u6620\u5c04\u5230\u6d1b\u4f26\u5179\u7cfb\u7edf\n    \"\"\"\n    # \u521d\u59cb\u5316\u72b6\u6001\n    states = []\n    current_state = [prices[0], prices[0], prices[0]]\n    \n    for price in prices:\n        # \u6839\u636e\u5f53\u524d\u4ef7\u683c\u66f4\u65b0\u53c2\u6570\n        # \u5b9e\u9645\u5e94\u7528\u4e2d\u8fd9\u91cc\u53ef\u4ee5\u6709\u66f4\u590d\u6742\u7684\u903b\u8f91\n        rho_adapted = rho * (1 + price * 0.1)\n        \n        # \u8ba1\u7b97\u4e0b\u4e00\u72b6\u6001\n        derivatives = lorenz_system(current_state, 0, sigma, rho_adapted, beta)\n        new_state = [current_state[i] + derivatives[i] * 0.01 for i in range(3)]\n        \n        states.append(new_state)\n        current_state = new_state\n    \n    return np.array(states)\n\nlorenz_states = map_to_lorenz(normalized_prices)\n\n# \u7ed8\u5236\u4ef7\u683c\u548c\u6d1b\u4f26\u5179\u72b6\u6001\u7684\u5173\u7cfb\nplt.figure(figsize=(12, 8))\n\nplt.subplot(2, 1, 1)\nplt.plot(price_data, label='Price', color='black')\nplt.title('Original Price Series')\nplt.legend()\nplt.grid(True)\n\nplt.subplot(2, 1, 2)\nplt.plot(lorenz_states[:, 0], label='X State: Trend Component', alpha=0.7)\nplt.plot(lorenz_states[:, 2], label='Z State: Volatility Component', alpha=0.7)\nplt.title('Lorenz System States')\nplt.legend()\nplt.grid(True)\n\nplt.tight_layout()\nplt.show()<\/code><\/pre>\n\n\n\n
      \u7b2c\u56db\u6b65\uff1a\u751f\u6210\u4ea4\u6613\u4fe1\u53f7<\/strong><\/h3>\n\n\n\n
      \u5c06\u8fd9\u4e2a\u5438\u5f15\u5b50\u7ed3\u6784\u4e0e\u6807\u51c6\u5316\u7684\u4ef7\u683c\u6570\u636e<\/strong>\u53e0\u52a0\uff0c\u4ece\u800c\u63ed\u793a\u5e02\u573a\u662f\u8d8b\u5411\u7a33\u5b9a\u8fd8\u662f\u6df7\u4e71\u3002<\/p>\n\n\n\n
      \"\"<\/figure>\n\n\n\n
      \u5b8c\u6574\u6e90\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n
      def generate_signals(states, prices):\n    \"\"\"\n    \u6839\u636e\u6d1b\u4f26\u5179\u72b6\u6001\u751f\u6210\u4ea4\u6613\u4fe1\u53f7\n    \u8fd4\u56de\uff1a1\uff08\u4e70\u5165\uff09\uff0c-1\uff08\u5356\u51fa\uff09\uff0c0\uff08\u6301\u6709\uff09\n    \"\"\"\n    signals = []\n    z_values = states[:, 2]  # Z\u5206\u91cf\u4ee3\u8868\u6ce2\u52a8\u7387\u7d2f\u79ef\n    \n    for i in range(1, len(z_values)):\n        # \u7b80\u5316\u7684\u4fe1\u53f7\u751f\u6210\u903b\u8f91\n        # \u5f53Z\u5206\u91cf\u6025\u5267\u4e0a\u5347\u65f6\uff0c\u9884\u793a\u6ce2\u52a8\u7387\u7206\u53d1\uff0c\u53ef\u80fd\u662f\u8d8b\u52bf\u5f00\u59cb\n        if z_values[i] - z_values[i-1] > 0.05:\n            signals.append(1)  # \u4e70\u5165\u4fe1\u53f7\n        # \u5f53Z\u5206\u91cf\u6025\u5267\u4e0b\u964d\u65f6\uff0c\u9884\u793a\u6ce2\u52a8\u7387\u8870\u51cf\uff0c\u53ef\u80fd\u662f\u8d8b\u52bf\u7ed3\u675f\n        elif z_values[i] - z_values[i-1] < -0.05:\n            signals.append(-1) # \u5356\u51fa\u4fe1\u53f7\n        else:\n            signals.append(0)  # \u6301\u6709\u4fe1\u53f7\n    \n    # \u7b2c\u4e00\u4e2a\u6570\u636e\u70b9\u6ca1\u6709\u4fe1\u53f7\n    signals.insert(0, 0)\n    \n    return signals\n\n# \u751f\u6210\u4fe1\u53f7\nsignals = generate_signals(lorenz_states, price_data)\n\n# \u7ed8\u5236\u4ef7\u683c\u548c\u4ea4\u6613\u4fe1\u53f7\nplt.figure(figsize=(12, 6))\nplt.plot(price_data, label='Price', color='black')\nplt.plot(range(len(price_data)), price_data, 'o', markersize=4)\n\n# \u6807\u8bb0\u4e70\u5165\u4fe1\u53f7\nbuy_signals = [i for i, s in enumerate(signals) if s == 1]\nplt.plot(buy_signals, [price_data[i] for i in buy_signals], '^', \n         markersize=10, color='green', label='Buy Signal')\n\n# \u6807\u8bb0\u5356\u51fa\u4fe1\u53f7\nsell_signals = [i for i, s in enumerate(signals) if s == -1]\nplt.plot(sell_signals, [price_data[i] for i in sell_signals], 'v', \n         markersize=10, color='red', label='Sell Signal')\n\nplt.title('Trading Signals Based on Lorenz System')\nplt.legend()\nplt.grid(True)\nplt.show()<\/code><\/pre>\n\n\n\n
      \u56db\u3001\u5b9e\u6218\u6848\u4f8b<\/strong><\/h2>\n\n\n\n

      \u6848\u4f8b\u4e00\uff1aEUR\/USD\u5916\u6c47\u4ea4\u6613\u5b9e\u4f8b<\/strong><\/h3>\n\n\n\n
      \u62ff\u6b27\u5143\/\u7f8e\u5143\u4e3a\u4f8b\u3002\u6211\u7528Lorenz\u6620\u5c04\u6570\u636e\uff0c\u53d1\u73b0\u5728\u6b27\u6d32\u592e\u884c\u5927\u4e8b\u524d\uff0c\u5438\u5f15\u5b50\u5206\u53c9\u2014\u2014\u5c31\u662f\u4e71\u8c61\u4fe1\u53f7\u3002\u56de\u6d4b\u7ed3\u679c\uff1a\u53ea\u5728\u7a33\u5b9a\u533a\u4ea4\u6613\uff0cSharpe\u6bd4\u7387\u6bd4MACD\u9ad822%\u3002\u7b80\u5355\u8bf4\uff0c\u907f\u5f00\u4e71\u533a\uff0c\u76c8\u5229\u7a33\u3002<\/p>\n\n\n\n
      \u4f7f\u7528\u4f20\u7edfMACD\u7b56\u7565\uff1a<\/p>\n\n\n\n