{"id":1043574,"date":"2024-12-31T13:07:17","date_gmt":"2024-12-31T05:07:17","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1043574.html"},"modified":"2024-12-31T13:07:19","modified_gmt":"2024-12-31T05:07:19","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e6%b1%82%e8%82%a1%e7%a5%a8%e6%94%b6%e7%9b%8a%e7%8e%87","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1043574.html","title":{"rendered":"\u5982\u4f55\u7528python\u6c42\u80a1\u7968\u6536\u76ca\u7387"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u6c42\u80a1\u7968\u6536\u76ca\u7387\"<\/p>\n

\u7528Python\u6c42\u80a1\u7968\u6536\u76ca\u7387\u7684\u65b9\u6cd5\u4e3b\u8981\u6709\uff1a\u4e0b\u8f7d\u80a1\u7968\u6570\u636e\u3001\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387\u3001\u8ba1\u7b97\u7d2f\u8ba1\u6536\u76ca\u7387\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u7ed3\u679c<\/strong>\u3002\u5176\u4e2d\uff0c\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387\u662f\u6700\u5173\u952e\u7684\u4e00\u6b65\u3002\u6bcf\u65e5\u6536\u76ca\u7387\u662f\u5f53\u524d\u80a1\u7968\u4ef7\u683c\u4e0e\u524d\u4e00\u5929\u80a1\u7968\u4ef7\u683c\u7684\u6bd4\u503c\u51cf\u53bb1\uff0c\u53ef\u4ee5\u7528\u516c\u5f0f\u8868\u793a\u4e3a\uff1a(P_t - P_(t-1)) \/ P_(t-1)<\/code>\uff0c\u5176\u4e2dP_t<\/code>\u8868\u793a\u7b2ct\u5929\u7684\u80a1\u7968\u4ef7\u683c\uff0cP_(t-1)<\/code>\u8868\u793a\u7b2ct-1\u5929\u7684\u80a1\u7968\u4ef7\u683c\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u8ba1\u7b97\u80a1\u7968\u6536\u76ca\u7387\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4e0b\u8f7d\u80a1\u7968\u6570\u636e<\/h3>\n<\/p>\n

\u8981\u8ba1\u7b97\u80a1\u7968\u6536\u76ca\u7387\uff0c\u9996\u5148\u9700\u8981\u83b7\u53d6\u80a1\u7968\u7684\u5386\u53f2\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Python\u7684yfinance<\/code>\u5e93\u6765\u4e0b\u8f7d\u80a1\u7968\u6570\u636e\u3002yfinance<\/code>\u662f\u4e00\u4e2a\u65b9\u4fbf\u7684\u5e93\uff0c\u53ef\u4ee5\u4eceYahoo Finance\u83b7\u53d6\u80a1\u7968\u6570\u636e\u3002<\/p>\n<\/p>\n

import yfinance as yf<\/p>\n
\u4e0b\u8f7d\u80a1\u7968\u6570\u636e<\/strong><\/h2>\n
ticker = 'AAPL'  # \u66ff\u6362\u4e3a\u4f60\u611f\u5174\u8da3\u7684\u80a1\u7968\u4ee3\u7801<\/p>\n
stock_data = yf.download(ticker, start='2020-01-01', end='2023-01-01')<\/p>\n
print(stock_data.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e0a\u9762\u7684\u4ee3\u7801\u5c06\u4e0b\u8f7d\u82f9\u679c\u516c\u53f8\uff08AAPL\uff09\u7684\u80a1\u7968\u6570\u636e\uff0c\u4ece2020\u5e741\u67081\u65e5\u52302023\u5e741\u67081\u65e5\u3002\u7ed3\u679c\u5c06\u5b58\u50a8\u5728stock_data<\/code>\u4e2d\uff0c\u8fd9\u4e2a\u6570\u636e\u6846\u5305\u542b\u4e86\u65e5\u671f\u3001\u5f00\u76d8\u4ef7\u3001\u6700\u9ad8\u4ef7\u3001\u6700\u4f4e\u4ef7\u3001\u6536\u76d8\u4ef7\u3001\u8c03\u6574\u6536\u76d8\u4ef7\u548c\u6210\u4ea4\u91cf\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387<\/h3>\n<\/p>\n
\u83b7\u53d6\u5230\u80a1\u7968\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387\u3002\u6bcf\u65e5\u6536\u76ca\u7387\u516c\u5f0f\u4e3a\uff1a(P_t - P_(t-1)) \/ P_(t-1)<\/code>\u3002\u6211\u4eec\u53ef\u4ee5\u7528Pandas\u5e93\u6765\u65b9\u4fbf\u5730\u5b9e\u73b0\u8fd9\u4e00\u8ba1\u7b97\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387<\/strong><\/h2>\n
stock_data['DAI<\/a>ly Return'] = stock_data['Adj Close'].pct_change()<\/p>\n
print(stock_data[['Adj Close', 'Daily Return']].head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u4e86pct_change()<\/code>\u65b9\u6cd5\u6765\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387\uff0c\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u65b0\u5217Daily Return<\/code>\u4e2d\u3002pct_change()<\/code>\u65b9\u6cd5\u5c06\u5f53\u524d\u884c\u7684\u503c\u4e0e\u524d\u4e00\u884c\u7684\u503c\u8fdb\u884c\u6bd4\u8f83\uff0c\u5e76\u8ba1\u7b97\u51fa\u767e\u5206\u6bd4\u53d8\u5316\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u8ba1\u7b97\u7d2f\u8ba1\u6536\u76ca\u7387<\/h3>\n<\/p>\n
\u7d2f\u8ba1\u6536\u76ca\u7387\u8868\u793a\u6295\u8d44\u4ece\u5f00\u59cb\u5230\u7ed3\u675f\u7684\u603b\u6536\u76ca\u7387\uff0c\u53ef\u4ee5\u901a\u8fc7\u5c06\u6bcf\u65e5\u6536\u76ca\u7387\u7d2f\u79ef\u76f8\u4e58\u5f97\u5230\u3002\u7d2f\u8ba1\u6536\u76ca\u7387\u516c\u5f0f\u4e3a\uff1a(1 + r_t) * (1 + r_(t-1)) * ... * (1 + r_1) - 1<\/code>\uff0c\u5176\u4e2dr_t<\/code>\u8868\u793a\u7b2ct\u5929\u7684\u6bcf\u65e5\u6536\u76ca\u7387\u3002<\/p>\n<\/p>\n
# \u8ba1\u7b97\u7d2f\u8ba1\u6536\u76ca\u7387<\/p>\n
stock_data['Cumulative Return'] = (1 + stock_data['Daily Return']).cumprod() - 1<\/p>\n
print(stock_data[['Adj Close', 'Cumulative Return']].head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528cumprod()<\/code>\u65b9\u6cd5\u6765\u8ba1\u7b97\u7d2f\u8ba1\u6536\u76ca\u7387\uff0c\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u65b0\u5217Cumulative Return<\/code>\u4e2d\u3002cumprod()<\/code>\u65b9\u6cd5\u5c06\u5f53\u524d\u884c\u7684\u503c\u4e0e\u524d\u9762\u6240\u6709\u884c\u7684\u503c\u76f8\u4e58\uff0c\u5e76\u8ba1\u7b97\u7d2f\u8ba1\u4e58\u79ef\u3002<\/p>\n<\/p>\n
\u56db\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u7ed3\u679c<\/h3>\n<\/p>\n
\u8ba1\u7b97\u51fa\u6bcf\u65e5\u6536\u76ca\u7387\u548c\u7d2f\u8ba1\u6536\u76ca\u7387\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u7ed3\u679c\u8fdb\u884c\u5206\u6790\u548c\u53ef\u89c6\u5316\u3002\u53ef\u4ee5\u4f7f\u7528Matplotlib\u548cSeaborn\u5e93\u6765\u7ed8\u5236\u56fe\u8868\uff0c\u76f4\u89c2\u5730\u5c55\u793a\u80a1\u7968\u7684\u6536\u76ca\u7387\u53d8\u5316\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import seaborn as sns<\/p>\n
\u8bbe\u7f6e\u56fe\u8868\u98ce\u683c<\/strong><\/h2>\n
sns.set(style='whitegrid')<\/p>\n
\u7ed8\u5236\u6bcf\u65e5\u6536\u76ca\u7387\u56fe\u8868<\/strong><\/h2>\n
plt.figure(figsize=(14, 7))<\/p>\n
plt.plot(stock_data.index, stock_data['Daily Return'], label='Daily Return')<\/p>\n
plt.title('Daily Return of ' + ticker)<\/p>\n
plt.xlabel('Date')<\/p>\n
plt.ylabel('Daily Return')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
\u7ed8\u5236\u7d2f\u8ba1\u6536\u76ca\u7387\u56fe\u8868<\/strong><\/h2>\n
plt.figure(figsize=(14, 7))<\/p>\n
plt.plot(stock_data.index, stock_data['Cumulative Return'], label='Cumulative Return', color='green')<\/p>\n
plt.title('Cumulative Return of ' + ticker)<\/p>\n
plt.xlabel('Date')<\/p>\n
plt.ylabel('Cumulative Return')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e0a\u9762\u7684\u4ee3\u7801\u5c06\u7ed8\u5236\u6bcf\u65e5\u6536\u76ca\u7387\u548c\u7d2f\u8ba1\u6536\u76ca\u7387\u7684\u56fe\u8868\uff0c\u5e2e\u52a9\u6211\u4eec\u66f4\u76f4\u89c2\u5730\u4e86\u89e3\u80a1\u7968\u7684\u6536\u76ca\u60c5\u51b5\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u5b9e\u6218\u6848\u4f8b<\/h3>\n<\/p>\n
\u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u7528Python\u6c42\u80a1\u7968\u6536\u76ca\u7387\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4e00\u4e2a\u5b9e\u6218\u6848\u4f8b\u6765\u8bf4\u660e\u3002\u5047\u8bbe\u6211\u4eec\u60f3\u8981\u5206\u6790\u7279\u65af\u62c9\uff08TSLA\uff09\u7684\u80a1\u7968\u6536\u76ca\u7387\uff0c\u5e76\u6bd4\u8f83\u5176\u4e0e\u7eb3\u65af\u8fbe\u514b\u7efc\u5408\u6307\u6570\uff08IXIC\uff09\u7684\u8868\u73b0\u3002<\/p>\n<\/p>\n
# \u4e0b\u8f7d\u7279\u65af\u62c9\u548c\u7eb3\u65af\u8fbe\u514b\u7efc\u5408\u6307\u6570\u6570\u636e<\/p>\n
tesla_data = yf.download('TSLA', start='2020-01-01', end='2023-01-01')<\/p>\n
nasdaq_data = yf.download('^IXIC', start='2020-01-01', end='2023-01-01')<\/p>\n
\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387<\/strong><\/h2>\n
tesla_data['Daily Return'] = tesla_data['Adj Close'].pct_change()<\/p>\n
nasdaq_data['Daily Return'] = nasdaq_data['Adj Close'].pct_change()<\/p>\n
\u8ba1\u7b97\u7d2f\u8ba1\u6536\u76ca\u7387<\/strong><\/h2>\n
tesla_data['Cumulative Return'] = (1 + tesla_data['Daily Return']).cumprod() - 1<\/p>\n
nasdaq_data['Cumulative Return'] = (1 + nasdaq_data['Daily Return']).cumprod() - 1<\/p>\n
\u7ed8\u5236\u6bcf\u65e5\u6536\u76ca\u7387\u56fe\u8868<\/strong><\/h2>\n
plt.figure(figsize=(14, 7))<\/p>\n
plt.plot(tesla_data.index, tesla_data['Daily Return'], label='TSLA Daily Return')<\/p>\n
plt.plot(nasdaq_data.index, nasdaq_data['Daily Return'], label='NASDAQ Daily Return', color='orange')<\/p>\n
plt.title('Daily Return of TSLA and NASDAQ')<\/p>\n
plt.xlabel('Date')<\/p>\n
plt.ylabel('Daily Return')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
\u7ed8\u5236\u7d2f\u8ba1\u6536\u76ca\u7387\u56fe\u8868<\/strong><\/h2>\n
plt.figure(figsize=(14, 7))<\/p>\n
plt.plot(tesla_data.index, tesla_data['Cumulative Return'], label='TSLA Cumulative Return')<\/p>\n
plt.plot(nasdaq_data.index, nasdaq_data['Cumulative Return'], label='NASDAQ Cumulative Return', color='orange')<\/p>\n
plt.title('Cumulative Return of TSLA and NASDAQ')<\/p>\n
plt.xlabel('Date')<\/p>\n
plt.ylabel('Cumulative Return')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u4ee3\u7801\uff0c\u6211\u4eec\u53ef\u4ee5\u4e0b\u8f7d\u7279\u65af\u62c9\u548c\u7eb3\u65af\u8fbe\u514b\u7efc\u5408\u6307\u6570\u7684\u80a1\u7968\u6570\u636e\uff0c\u8ba1\u7b97\u5176\u6bcf\u65e5\u6536\u76ca\u7387\u548c\u7d2f\u8ba1\u6536\u76ca\u7387\uff0c\u5e76\u7ed8\u5236\u5bf9\u6bd4\u56fe\u8868\u3002\u8fd9\u6837\u53ef\u4ee5\u76f4\u89c2\u5730\u5c55\u793a\u7279\u65af\u62c9\u80a1\u7968\u4e0e\u7eb3\u65af\u8fbe\u514b\u7efc\u5408\u6307\u6570\u7684\u8868\u73b0\u5dee\u5f02\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u7528Python\u6c42\u80a1\u7968\u6536\u76ca\u7387\u7684\u65b9\u6cd5\u4e3b\u8981\u5305\u62ec\uff1a\u4e0b\u8f7d\u80a1\u7968\u6570\u636e\u3001\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387\u3001\u8ba1\u7b97\u7d2f\u8ba1\u6536\u76ca\u7387\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u7ed3\u679c\u3002\u901a\u8fc7\u5b9e\u6218\u6848\u4f8b\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u597d\u5730\u7406\u89e3\u548c\u5e94\u7528\u8fd9\u4e9b\u65b9\u6cd5\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u8fdb\u884c\u8c03\u6574\u548c\u6269\u5c55\uff0c\u4f8b\u5982\u52a0\u5165\u66f4\u591a\u7684\u80a1\u7968\u8fdb\u884c\u5bf9\u6bd4\u5206\u6790\u3001\u4f7f\u7528\u4e0d\u540c\u7684\u65f6\u95f4\u6bb5\u8fdb\u884c\u56de\u6d4b\u7b49\u3002<\/p>\n<\/p>\n
\u603b\u4e4b\uff0cPython\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5de5\u5177\u548c\u5e93\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u65b9\u4fbf\u5730\u8fdb\u884c\u80a1\u7968\u6536\u76ca\u7387\u7684\u8ba1\u7b97\u548c\u5206\u6790\u3002\u8fd9\u5bf9\u4e8e\u6295\u8d44\u8005\u548c\u7814\u7a76\u4eba\u5458\u6765\u8bf4\uff0c\u662f\u4e00\u4e2a\u975e\u5e38\u6709\u7528\u7684\u6280\u80fd\u3002\u5e0c\u671b\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u80fd\u591f\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u638c\u63e1\u7528Python\u6c42\u80a1\u7968\u6536\u76ca\u7387\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u8ba1\u7b97\u80a1\u7968\u7684\u6536\u76ca\u7387\uff1f<\/strong>
\u8981\u8ba1\u7b97\u80a1\u7968\u7684\u6536\u76ca\u7387\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u4e2d\u7684Pandas\u5e93\u6765\u5904\u7406\u6570\u636e\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u83b7\u53d6\u80a1\u7968\u7684\u5386\u53f2\u4ef7\u683c\u6570\u636e\uff0c\u901a\u5e38\u53ef\u4ee5\u901a\u8fc7Yahoo Finance\u7b49API\u83b7\u53d6\u3002\u63a5\u4e0b\u6765\uff0c\u4f7f\u7528Pandas\u8bfb\u53d6\u6570\u636e\uff0c\u8ba1\u7b97\u6536\u76ca\u7387\u53ef\u4ee5\u901a\u8fc7\u4ef7\u683c\u7684\u53d8\u52a8\u767e\u5206\u6bd4\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528\u516c\u5f0f\uff1a(\u5f53\u524d\u4ef7\u683c – \u524d\u4e00\u4e2a\u4ef7\u683c) \/ \u524d\u4e00\u4e2a\u4ef7\u683c \u6765\u8ba1\u7b97\u6bcf\u65e5\u6536\u76ca\u7387\u3002<\/p>\n
\u5728Python\u4e2d\u5982\u4f55\u5904\u7406\u7f3a\u5931\u7684\u80a1\u7968\u6570\u636e\uff1f<\/strong>
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