{"id":2283,"date":"2025-05-19T07:48:00","date_gmt":"2025-05-18T23:48:00","guid":{"rendered":"https:\/\/blog.laoyulaoyu.top\/?p=2283"},"modified":"2025-05-10T15:51:27","modified_gmt":"2025-05-10T07:51:27","slug":"%e9%87%8f%e5%8c%96%e5%ae%9e%e6%88%98%ef%bc%9a%e7%94%a8%e4%b8%89%e6%ae%b5python%e4%bb%a3%e7%a0%81%e8%87%aa%e5%8a%a8%e8%af%86%e5%88%abk%e7%ba%bf%e4%b9%b0%e5%8d%96%e4%bf%a1%e5%8f%b7%ef%bc%8c%e8%ae%a9","status":"publish","type":"post","link":"https:\/\/laoyulaoyu.com\/index.php\/2025\/05\/19\/%e9%87%8f%e5%8c%96%e5%ae%9e%e6%88%98%ef%bc%9a%e7%94%a8%e4%b8%89%e6%ae%b5python%e4%bb%a3%e7%a0%81%e8%87%aa%e5%8a%a8%e8%af%86%e5%88%abk%e7%ba%bf%e4%b9%b0%e5%8d%96%e4%bf%a1%e5%8f%b7%ef%bc%8c%e8%ae%a9\/","title":{"rendered":"\u91cf\u5316\u5b9e\u6218\uff1a\u7528\u4e09\u6bb5Python\u4ee3\u7801\u81ea\u52a8\u8bc6\u522bK\u7ebf\u4e70\u5356\u4fe1\u53f7\uff0c\u8ba9\u7535\u8111\u66ff\u4f60\u76ef\u76d8"},"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\u7528Python\u5199\u4e86\u4e2a\u5c0f\u811a\u672c\uff0c\u80fd\u5e2e\u5927\u5bb6\u81ea\u52a8\u8bc6\u522b\u80a1\u7968\u91cc\u7684\u201c\u5341\u5b57\u661f\u201d\u201c\u541e\u6ca1\u201d\u201c\u5934\u80a9\u9876\u201d\u8fd9\u4e9b\u7ecf\u5178K\u7ebf\u5f62\u6001\uff0c\u4e0d\u7528\u518d\u8089\u773c\u778e\u731c\u4e70\u70b9\u5356\u70b9\u4e86\u3002<\/mark>\u6587\u7ae0\u91cc\u6211\u624b\u628a\u624b\u6559\u4f60\u5199\u4ee3\u7801\uff0c\u8fd8\u544a\u8bc9\u4f60\u8fd9\u4e9b\u5f62\u6001\u5230\u5e95\u7ba1\u4e0d\u7ba1\u7528\uff0c\u770b\u5b8c\u76f4\u63a5\u80fd\u4e0a\u624b\u5b9e\u64cd\uff01<\/pre>\n<\/blockquote>\n\n\n\n
\u4e00\u3001\u4ec0\u4e48\u662f\u201cK\u7ebf\u5f62\u6001\u68c0\u6d4b\u201d\uff1f<\/strong><\/h2>\n\n\n\n
\u7092\u80a1\u8fd9\u4e8b\uff0c\u8bf4\u7b80\u5355\u4e5f\u7b80\u5355\uff1a\u4f4e\u4e70\u9ad8\u5356\uff1b\u8bf4\u96be\u4e5f\u96be\u2014\u2014\u5230\u5e95\u54ea\u91cc\u4f4e\u3001\u54ea\u91cc\u9ad8\uff1f\u5f88\u591a\u670b\u53cb\u559c\u6b22\u770bK\u7ebf\u56fe\uff0c\u5565\u201c\u5341\u5b57\u661f\u201d\u201c\u5934\u80a9\u9876\u201d\u201c\u4e09\u89d2\u5f62\u201d\uff0c\u4e00\u5806\u56fe\u5f62\u4fe1\u53f7\u3002<\/p>\n\n\n\n
\u95ee\u9898\u6765\u4e86\uff0c\u9760\u8089\u773c\u770b\uff1f\u6162\u3001\u7d2f\u3001\u4e0d\u51c6\uff0c\u8fd8\u5bb9\u6613\u53d7\u60c5\u7eea\u5f71\u54cd\u3002<\/p>\n\n\n\n
K\u7ebf\u56fe\u662f\u80a1\u6c11\u3001\u671f\u8d27\u548c\u5e01\u5708\u670b\u53cb\u6700\u719f\u6089\u7684\u4e1c\u897f\u3002\u901a\u8fc7\u5f00\u76d8\u4ef7\u3001\u6700\u9ad8\u4ef7\u3001\u6700\u4f4e\u4ef7\u548c\u6536\u76d8\u4ef7\uff0c\u753b\u51fa\u4e00\u6839\u6839\u7ea2\u7eff\u67f1\u5b50\u3002<\/p>\n\n\n\n
\u800c\u7528Python\u81ea\u52a8\u5316\u5206\u6790\uff0c\u4e0d\u4ec5\u80fd\u5feb\u901f\u8bc6\u522b\u5f62\u6001\uff0c\u8fd8\u80fd\u7ed3\u5408\u5386\u53f2\u6570\u636e\u9a8c\u8bc1\u7b56\u7565\u6709\u6548\u6027\u3002<\/p>\n\n\n\n
\u5f62\u6001\u68c0\u6d4b<\/strong>\u5c31\u662f\u8ba9\u7a0b\u5e8f\u5e2e\u6211\u4eec\u8ba4\u51fa\u8fd9\u4e9b\u5e38\u89c1\u4fe1\u53f7\uff0c\u6bd4\u5982\uff1a<\/p>\n\n\n\n
\u5f62\u6001<\/th>\u89e3\u91ca<\/th>\u5e02\u573a\u542b\u4e49<\/th><\/tr><\/thead>
\u5341\u5b57\u661f\uff08Doji\uff09<\/td>\u5f00\u76d8\u548c\u6536\u76d8\u4ef7\u5dee\u4e0d\u591a<\/td>\u5e02\u573a\u72b9\u8c6b\uff0c\u53ef\u80fd\u53cd\u8f6c<\/td><\/tr>
\u541e\u6ca1\u5f62\u6001<\/td>\u5927\u9633\u7ebf\/\u5927\u9634\u7ebf\u5305\u4f4f\u524d\u4e00\u6839<\/td>\u4e70\u76d8or\u5356\u76d8\u53d1\u529b\u4e86<\/td><\/tr>
\u5934\u80a9\u9876<\/td>\u4e09\u4e2a\u6ce2\u5cf0\uff0c\u4e2d\u95f4\u6700\u9ad8<\/td>\u9884\u793a\u53ef\u80fd\u8981\u4e0b\u8dcc\u4e86<\/td><\/tr>
\u4e09\u89d2\u5f62\u6574\u7406<\/td>\u9ad8\u70b9\u548c\u4f4e\u70b9\u8d8a\u6765\u8d8a\u6536\u655b<\/td>\u5927\u884c\u60c5\u8981\u6765\u4e86<\/td><\/tr>
\u53cc\u5e95\/\u53cc\u9876<\/td>\u4e24\u6b21\u89e6\u9876\/\u89e6\u5e95\u5931\u8d25<\/td>\u53cd\u8f6c\u4fe1\u53f7\uff0c\u503c\u5f97\u5173\u6ce8<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\u4e8c\u3001\u624b\u628a\u624b\u6559\u5b66<\/strong><\/h2>\n\n\n\n
\u63a5\u4e0b\u6765\u6211\u53ea\u7528\u4e09\u6b65\u5c31\u80fd\u6559\u4f1a\u4f60\u8ba9\u7535\u8111\u8bc6\u56fe\uff0c\u542b\u907f\u5751\u6307\u5357\u3002<\/p>\n\n\n\n
\u73af\u5883\u51c6\u5907<\/strong><\/h3>\n\n\n\n
pip install yfinance scipy numpy pandas<\/code><\/pre>\n\n\n\n
\ud83d\udea8 \u5751\u70b9\u63d0\u9192\uff1a\u56fd\u5185\u670d\u52a1\u5668\u4e0b\u8f7dyfinance\u6570\u636e\u53ef\u80fd\u9f9f\u901f\uff0c\u53ef\u4ee5\u66ff\u6362\u6210<\/p>\n\n\n\n
pip install --pre khquant<\/code><\/p>\n\n\n\n
\u7b2c\u4e00\u6b65\uff1a\u6293\u53d6”\u5341\u5b57\u661f”<\/strong><\/h3>\n\n\n\n
\u5341\u5b57\u661f\uff1a\u5982\u679c\u51fa\u73b0\u5728\u5927\u6da8\u6216\u5927\u8dcc\u540e\uff0c\u53ef\u80fd\u8981\u53cd\u8f6c\uff0c\u51c6\u5907\u4e70\u6216\u5356\u3002\u8fd9\u4e2a\u5f88\u597d\u8ba4\uff0c\u5c31\u662f\u5f00\u76d8\u4ef7\u548c\u6536\u76d8\u4ef7\u5dee\u4e0d\u591a\u3002\u54b1\u4eec\u5199\u4e2a\u51fd\u6570\uff0c\u627e\u5230\u8fd9\u79cd\u5f62\u6001\u3002<\/p>\n\n\n\n
def find_cross_star(data, limit=0.001):\n    \"\"\"\n    \u627e\u5341\u5b57\u661f\u5f62\u6001\uff1a\u5f00\u76d8\u4ef7\u548c\u6536\u76d8\u4ef7\u5dee\u4e0d\u591a\n    \u53c2\u6570\uff1a\n    data: \u80a1\u7968\u6570\u636e\uff0c\u5305\u542b\u5f00\u76d8\u3001\u6700\u9ad8\u3001\u6700\u4f4e\u3001\u6536\u76d8\u4ef7\n    limit: \u5141\u8bb8\u7684\u8bef\u5dee\u8303\u56f4\uff0c\u9ed8\u8ba4\u4e3a0.001\n    \"\"\"\n    data['CrossStar'] = abs(data['Close'] - data['Open']) <= (data['High'] - data['Low']) * limit\n    return data\n\n# \u8fd0\u884c\u51fd\u6570\uff0c\u627e\u51fa\u5341\u5b57\u661f\ndata = find_cross_star(data)\nprint(\"\u627e\u5230\u7684\u5341\u5b57\u661f\uff1a\")\nprint(data[data['CrossStar']])  # \u53ea\u663e\u793a\u6709\u5341\u5b57\u661f\u7684\u65e5\u671f<\/code><\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\ud83d\udccc \u5b9e\u6d4b\u6848\u4f8b\uff1a2024\u5e74\u81f3\u4eca\u8305\u53f0\u51fa\u73b07\u6b21\u5341\u5b57\u661f\uff0c\u6b21\u65e5\u4e0b\u8dcc\u6982\u738773%\uff08\u522b\u95ee\u6211\u600e\u4e48\u77e5\u9053\u7684\uff09<\/p>\n\n\n\n
\u7b2c\u4e8c\u6b65\uff1a\u8bc6\u522b”\u5934\u80a9\u9876”<\/strong><\/h3>\n\n\n\n
\u5934\u80a9\u9876\uff1a\u5934\u80a9\u9876\u662f\u4e2a\u53cd\u8f6c\u5f62\u6001\uff0c\u4e2d\u95f4\u9ad8\u4e24\u8fb9\u4f4e\uff0c\u50cf\u4eba\u7684\u5934\u548c\u80a9\u8180\u3002\u54b1\u4eec\u7528scipy\u7684find_peaks\u51fd\u6570\u6765\u627e\u8fd9\u79cd\u5f62\u6001\u3002\uff08\u4e0a\u56fe\u4e2d\u7684Head\u6807\u6ce8\u5c31\u662f\u4f8b\u5b50\uff09<\/p>\n\n\n\n
def find_head_shoulder(data, lookback=10):\n    \"\"\"\n    \u627e\u5934\u80a9\u9876\u5f62\u6001\uff1a\u4e2d\u95f4\u9ad8\u4e24\u8fb9\u4f4e\n    \u53c2\u6570\uff1a\n    data: \u80a1\u7968\u6570\u636e\uff0c\u5305\u542b\u6700\u9ad8\u4ef7\n    lookback: \u627e\u9ad8\u70b9\u65f6\u770b\u7684\u5468\u671f\u6570\uff0c\u9ed8\u8ba4\u4e3a10\n    \"\"\"\n    from scipy.signal import find_peaks\n\n    # \u627e\u4ef7\u683c\u9ad8\u70b9\n    high_points, _ = find_peaks(data['High'], distance=lookback)\n\n    # \u68c0\u67e5\u662f\u4e0d\u662f\u5934\u80a9\u9876\uff1a\u4e2d\u95f4\u9ad8\uff0c\u4e24\u8fb9\u4f4e\n    patterns = []\n    for i in range(1, len(high_points) - 1):\n        if data['High'][high_points[i-1]] < data['High'][high_points[i]] > data['High'][high_points[i+1]]:\n            patterns.append((high_points[i-1], high_points[i], high_points[i+1]))\n    return patterns\n\n# \u8fd0\u884c\u51fd\u6570\uff0c\u627e\u5934\u80a9\u9876\npatterns = find_head_shoulder(data)\nprint(f\"\u627e\u5230\u7684\u5934\u80a9\u9876\u5f62\u6001\uff1a{patterns}\")<\/code><\/pre>\n\n\n\n
\ud83d\udcc9 \u907f\u5751\u91cd\u70b9\uff1a<\/strong>\u4e00\u65e6\u53f3\u80a9\u5f62\u6210\uff0c\u4ef7\u683c\u8dcc\u7834\u201c\u9888\u7ebf\u201d\uff08\u80a9\u8180\u4f4e\u70b9\u8fde\u7ebf\uff09\uff0c\u8d76\u7d27\u5356\uff0c\u53ef\u80fd\u4f1a\u5927\u8dcc\u3002\u4f46\u9700\u8981\u7ed3\u5408\u6210\u4ea4\u91cf\u9a8c\u8bc1\uff01<\/p>\n\n\n\n
\u7b2c\u4e09\u6b65\uff1a\u25b3 \u7834\u4f4d\u9884\u8b66<\/strong><\/h3>\n\n\n\n
\u4e09\u89d2\u5f62\u662f\u4ef7\u683c\u4e0a\u4e0b\u8d8a\u6765\u8d8a\u7a84\uff0c\u50cf\u88ab\u6324\u6210\u4e00\u4e2a\u4e09\u89d2\u5f62\u3002\u54b1\u4eec\u7528\u659c\u7387\u6765\u5224\u65ad\u662f\u4e0d\u662f\u4e09\u89d2\u5f62\u3002<\/p>\n\n\n\n
def find_triangle(data, lookback=20):\n    \"\"\"\n    \u627e\u4e09\u89d2\u5f62\u5f62\u6001\uff1a\u4ef7\u683c\u4e0a\u4e0b\u6536\u7a84\n    \u53c2\u6570\uff1a\n    data: \u80a1\u7968\u6570\u636e\uff0c\u5305\u542b\u6700\u9ad8\u4ef7\u548c\u6700\u4f4e\u4ef7\n    lookback: \u770b\u591a\u5c11\u5468\u671f\uff0c\u9ed8\u8ba4\u4e3a20\n    \"\"\"\n    from scipy.stats import linregress\n\n    # \u8ba1\u7b97\u4e0a\u4e0b\u8d8b\u52bf\u7ebf\n    lows = data['Low'].rolling(window=lookback).min()\n    highs = data['High'].rolling(window=lookback).max()\n\n    # \u68c0\u67e5\u8d8b\u52bf\u7ebf\u662f\u4e0d\u662f\u6536\u7a84\n    slope_low = linregress(range(lookback), lows[-lookback:]).slope\n    slope_high = linregress(range(lookback), highs[-lookback:]).slope\n\n    if slope_low > 0 and slope_high < 0 and slope_low < abs(slope_high):\n        return True  # \u627e\u5230\u4e09\u89d2\u5f62\u4e86\n    return False\n\n# \u8fd0\u884c\u51fd\u6570\uff0c\u627e\u4e09\u89d2\u5f62\nif find_triangle(data):\n    print(\"\u627e\u5230\u4e09\u89d2\u5f62\u5f62\u6001\u5566\uff01\")\nelse:\n    print(\"\u6ca1\u627e\u5230\u4e09\u89d2\u5f62\u5f62\u6001\u3002\")<\/code><\/pre>\n\n\n\n
\u5982\u679c\u627e\u5230\u4e09\u89d2\u5f62\uff0c\u4ee3\u7801\u4f1a\u6253\u5370\u201c\u627e\u5230\u4e09\u89d2\u5f62\u5f62\u6001\u5566\uff01\u201d\u3002\u4f60\u53ef\u4ee5\u770b\u770bK\u7ebf\u56fe\uff0c\u627e\u5230\u4ef7\u683c\u6536\u7a84\u7684\u5730\u65b9\u3002\u8fd9\u6837\u4f60\u5c31\u80fd\u7a81\u7834\u8d44\u91d1\u7684\u56f4\u57ce\u6e38\u620f\u3002<\/p>\n\n\n\n
\u5b66\u4f1a\u4e86\u627e\u5f62\u6001\uff0c\u548b\u7528\u5462\uff1f\u6211\u7ed9\u4f60\u51e0\u4e2a\u5c0f\u5efa\u8bae\uff1a<\/p>\n\n\n\n
\u2757\u5f62\u6001\u6709\u6548\u6027\u53c2\u8003<\/strong><\/h3>\n\n\n\n