\ub9e4\ub3c4 \uc2e0\ud638:<\/strong> \ub2e8\uae30 \uc774\ub3d9\ud3c9\uade0\uc120\uc774 \uc7a5\uae30 \uc774\ub3d9\ud3c9\uade0\uc120\uc744 \ud558\ud5a5 \ub3cc\ud30c\ud560 \ub54c<\/li>\n<\/ul>\n3. \ud658\uacbd \uc124\uc815<\/h2>\n
\n Zipline\uc744 \uc124\uce58\ud558\uae30 \uc704\ud574\uc11c\ub294 Anaconda\ub97c \uc0ac\uc6a9\ud558\ub294 \uac83\uc774 \uc88b\uc2b5\ub2c8\ub2e4. \uc544\ub798\uc758 \uba85\ub839\uc5b4\ub97c
\n \uc0ac\uc6a9\ud558\uc5ec Zipline\uacfc \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n \n conda install -c conda-forge zipline\n <\/code>\n <\/pre>\n4. \ub370\uc774\ud130 \ub2e4\uc6b4\ub85c\ub4dc<\/h2>\n
\n \ubc31\ud14c\uc2a4\ud2b8\ub97c \uc704\ud574\uc11c\ub294 \uacfc\uac70 \uac00\uaca9 \ub370\uc774\ud130\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. Zipline\uc740 Yahoo Finance\uc5d0\uc11c \ub370\uc774\ud130\ub97c
\n \uc9c1\uc811 \uac00\uc838\uc624\ub294 \uae30\ub2a5\uc744 \uc81c\uacf5\ud558\uc9c0 \uc54a\uc73c\ubbc0\ub85c, `pandas-datareader` \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ub97c
\n \ub2e4\uc6b4\ub85c\ub4dc\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc544\ub798\uc758 \ucf54\ub4dc\ub97c \ud1b5\ud574 \ub370\uc774\ud130\ub97c \uac00\uc838\uc62c \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n \n import pandas as pd\n from pandas_datareader import data\n import datetime\n\n # \ub370\uc774\ud130 \ub2e4\uc6b4\ub85c\ub4dc \uae30\uac04 \uc124\uc815\n start = datetime.datetime(2015, 1, 1)\n end = datetime.datetime(2021, 1, 1)\n\n # \uc560\ud50c \uc8fc\uc2dd \ub370\uc774\ud130 \ub2e4\uc6b4\ub85c\ub4dc\n stock_data = data.DataReader('AAPL', 'yahoo', start, end)\n stock_data.to_csv('aapl.csv') # \ub370\uc774\ud130 CSV\ub85c \uc800\uc7a5\n <\/code>\n <\/pre>\n5. Zipline \ud658\uacbd \uc124\uc815<\/h2>\n
\n Zipline\uc5d0\uc11c \uc0ac\uc6a9\ud560 \uc54c\uace0\ub9ac\uc998\uc744 \uc815\uc758\ud558\uae30 \uc704\ud574\uc11c\ub294 \uba87 \uac00\uc9c0 \ud544\uc218\uc801\uc778 \uad6c\uc131\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.
\n \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\uc640 \ub370\uc774\ud130\ub97c \uac00\uc838\uc624\ub294 \uacfc\uc815\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n \n from zipline import run_algorithm\n from zipline.api import order, record, symbol\n import pytz\n from datetime import datetime\n\n # Zipline \uc0ac\uc6a9\uc5d0 \ud544\uc694\ud55c \uc124\uc815\n def initialize(context):\n context.asset = symbol('AAPL') # \uc560\ud50c \uc8fc\uc2dd \uac70\ub798\n\n def handle_data(context, data):\n # \uc774\ub3d9\ud3c9\uade0\uc120 \uacc4\uc0b0\n short_mavg = data.history(context.asset, 'price', 20, '1d').mean()\n long_mavg = data.history(context.asset, 'price', 50, '1d').mean()\n\n # \ub9e4\uc218 \ubc0f \ub9e4\ub3c4 \uc2e0\ud638 \uc0dd\uc131\n if short_mavg > long_mavg:\n order(context.asset, 10) # 10\uc8fc \ub9e4\uc218\n elif short_mavg < long_mavg:\n order(context.asset, -10) # 10\uc8fc \ub9e4\ub3c4\n\n # \uc131\uacfc \uae30\ub85d\n record(AAPL=data.current(context.asset, 'price'))\n <\/code>\n <\/pre>\n6. \ubc31\ud14c\uc2a4\ud2b8 \uc2e4\ud589<\/h2>\n
\n \ub2e4\uc74c \ub2e8\uacc4\ub294 \uc54c\uace0\ub9ac\uc998\uc744 \ubc31\ud14c\uc2a4\ud2b8\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. Zipline\uc758 `run_algorithm` \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec
\n \ubc31\ud14c\uc2a4\ud2b8\ub97c \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798 \ucf54\ub4dc\ub294 2015\ub144 1\uc6d4 1\uc77c\ubd80\ud130 2021\ub144 1\uc6d4 1\uc77c\uae4c\uc9c0
\n \uc2e4\ud589\ub418\ub294 \ubc31\ud14c\uc2a4\ud2b8\ub97c \uc124\uc815\ud55c \uac83\uc785\ub2c8\ub2e4.\n <\/p>\n
\n \n if __name__ == '__main__':\n start_date = datetime(2015, 1, 1, tzinfo=pytz.UTC)\n end_date = datetime(2021, 1, 1, tzinfo=pytz.UTC)\n\n run_algorithm(start=start_date,\n end=end_date,\n initialize=initialize,\n capital_base=10000,\n handle_data=handle_data,\n data_frequency='daily')\n <\/code>\n <\/pre>\n7. \uacb0\uacfc \ubd84\uc11d<\/h2>\n
\n \ubc31\ud14c\uc2a4\ud2b8\uac00 \uc644\ub8cc\ub418\uba74 Zipline\uc740 \ub9e4\ub9e4 \ub0b4\uc5ed\uacfc \uc131\uacfc \ub370\uc774\ud130\ub97c \uae30\ub85d\ud569\ub2c8\ub2e4. \uacb0\uacfc\ub294 \uadf8\ub798\ud53d\uc73c\ub85c
\n \uc2dc\uac01\ud654\ud558\uac70\ub098, \uc131\uacfc \uc9c0\ud45c(ex. \uc0e4\ud504 \ube44\uc728, \ucd5c\ub300 \uc190\uc2e4 \ub4f1)\ub97c \uacc4\uc0b0\ud558\uc5ec \ud3c9\uac00\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n \ub2e4\uc74c\uc740 \uae30\ubcf8\uc801\uc778 \uacb0\uacfc \ubd84\uc11d \ubc29\ubc95\uc785\ub2c8\ub2e4.\n <\/p>\n
\n \n import matplotlib.pyplot as plt\n from zipline import run_algorithm\n\n # \uacb0\uacfc \uc2dc\uac01\ud654\n result = run_algorithm(start=start_date,\n end=end_date,\n initialize=initialize,\n capital_base=10000,\n handle_data=handle_data,\n data_frequency='daily')\n\n plt.figure(figsize=(12, 6))\n plt.plot(result.index, result['AAPL'], label='AAPL Price')\n plt.title('AAPL Holding Performance')\n plt.xlabel('Date')\n plt.ylabel('Price')\n plt.legend()\n plt.show()\n <\/code>\n <\/pre>\n8. \uacb0\ub860<\/h2>\n
\n \ubcf8 \uae00\uc5d0\uc11c\ub294 Zipline\uc744 \ud65c\uc6a9\ud55c \uc774\ub3d9\ud3c9\uade0\uc120 \uc804\ub7b5\uc758 \ubc31\ud14c\uc2a4\ud2b8 \ubc29\ubc95\uc744 \uc124\uba85\ud558\uc600\uc2b5\ub2c8\ub2e4.
\n \uc774\ub3d9\ud3c9\uade0\uc120 \uc804\ub7b5\uc740 \uac04\ub2e8\ud558\uba74\uc11c\ub3c4 \ud30c\uc545\ud558\uae30 \uc26c\uc6b4 \uc804\ub7b5\uc73c\ub85c, \ub9ce\uc740 \ud2b8\ub808\uc774\ub354\ub4e4\uc774 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.
\n Zipline\uc744 \ud1b5\ud574 \uc774 \uc804\ub7b5\uc744 \uad6c\ud604\ud558\uace0 \ubc31\ud14c\uc2a4\ud2b8\ub97c \uc9c4\ud589\ud568\uc73c\ub85c\uc368, \uc2e4\uc81c \ud22c\uc790\uc758 \uacb0\uc815\uc5d0 \ub3c4\uc6c0\uc744 \uc8fc\ub294
\n \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n \ub2e4\uc74c \ub2e8\uacc4\ub85c\ub294 \ub354 \ubc1c\uc804\ub41c \uc804\ub7b5\uc744 \uc5f0\uad6c\ud558\uace0, \ub2e4\uc591\ud55c \uc9c0\ud45c\ub4e4\uc744 \uacb0\ud569\ud558\uc5ec \ub354\uc6b1 \uc815\uad50\ud55c
\n \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uad6c\ucd95\ud574\ubcf4\ub294 \uac83\uc744 \uad8c\uc7a5\ud569\ub2c8\ub2e4. Zipline\uc758 \uae4a\uc774 \uc788\ub294 \uae30\ub2a5\uc744 \ud65c\uc6a9\ud558\uace0
\n \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uc138\uacc4\ub85c \ub4e4\uc5b4\uac00\uc2e4 \uc218 \uc788\uae30\ub97c \ubc14\ub78d\ub2c8\ub2e4.\n <\/p>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \ud504\ub85c\uadf8\ub798\ubc0d\ud558\uc5ec \ucef4\ud4e8\ud130\uac00 \uc2e0\ud638\ub97c \uae30\ubc18\uc73c\ub85c \uc8fc\uc2dd\uc744 \uc0ac\uace0 \ud30c\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc2dc\uc2a4\ud15c\uc740 \ud22c\uc790\uc790\uc758 \uc695\uad6c\uc5d0 \ub9de\ucd98 \ub9de\ucda4\ud615 \uc804\ub7b5\uc744 \uc81c\uacf5\ud558\uba70, \uac10\uc815\uc801\uc778 \uc694\uc18c\ub97c \ubc30\uc81c\ud558\uc5ec \uc77c\uad00\ub41c \uac70\ub798\ub97c \uac00\ub2a5\ud558\uac8c \ud569\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ud30c\uc774\uc36c\uc758 Zipline \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774\ub3d9\ud3c9\uade0\uc120 \uc804\ub7b5\uc744 \ubc31\ud14c\uc2a4\ud2b8\ud558\ub294 \ubc29\ubc95\uc744 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. Zipline \uc18c\uac1c Zipline\uc740 Python\uc73c\ub85c \uc791\uc131\ub41c \uc624\ud508 \uc18c\uc2a4 \ubc31\ud14c\uc2a4\ud305 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, Quantopian\uc5d0\uc11c \uac1c\ubc1c\ud55c \uae08\uc735 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \uc5ed\uc0ac\uc801 … \ub354 \ubcf4\uae30 “\ud30c\uc774\uc36c \uc790\ub3d9\ub9e4\ub9e4 \uac1c\ubc1c, Zipline\uc744 \uc774\uc6a9\ud55c \uc774\ub3d9\ud3c9\uade0\uc120 \uc804\ub7b5 \ubc31\ud14c\uc2a4\ud2b8”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[37],"tags":[],"class_list":["post-30883","post","type-post","status-publish","format-standard","hentry","category-37"],"yoast_head":"\n\ud30c\uc774\uc36c \uc790\ub3d9\ub9e4\ub9e4 \uac1c\ubc1c, Zipline\uc744 \uc774\uc6a9\ud55c \uc774\ub3d9\ud3c9\uade0\uc120 \uc804\ub7b5 \ubc31\ud14c\uc2a4\ud2b8 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/30883\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ud30c\uc774\uc36c \uc790\ub3d9\ub9e4\ub9e4 \uac1c\ubc1c, Zipline\uc744 \uc774\uc6a9\ud55c \uc774\ub3d9\ud3c9\uade0\uc120 \uc804\ub7b5 \ubc31\ud14c\uc2a4\ud2b8 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \ud504\ub85c\uadf8\ub798\ubc0d\ud558\uc5ec \ucef4\ud4e8\ud130\uac00 \uc2e0\ud638\ub97c \uae30\ubc18\uc73c\ub85c \uc8fc\uc2dd\uc744 \uc0ac\uace0 \ud30c\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc2dc\uc2a4\ud15c\uc740 \ud22c\uc790\uc790\uc758 \uc695\uad6c\uc5d0 \ub9de\ucd98 \ub9de\ucda4\ud615 \uc804\ub7b5\uc744 \uc81c\uacf5\ud558\uba70, \uac10\uc815\uc801\uc778 \uc694\uc18c\ub97c \ubc30\uc81c\ud558\uc5ec \uc77c\uad00\ub41c \uac70\ub798\ub97c \uac00\ub2a5\ud558\uac8c \ud569\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ud30c\uc774\uc36c\uc758 Zipline \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774\ub3d9\ud3c9\uade0\uc120 \uc804\ub7b5\uc744 \ubc31\ud14c\uc2a4\ud2b8\ud558\ub294 \ubc29\ubc95\uc744 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. 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