\ucd5c\uadfc \uba87 \ub144\uac04 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc758 \ubc1c\uc804\uc740 \uae08\uc735 \ubd84\uc57c\uc5d0\uc11c\ub3c4 \uc0c8\ub85c\uc6b4 \ud328\ub7ec\ub2e4\uc784\uc744 \uac00\uc838\uc654\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \ubd84\uc57c\uc5d0\uc11c \uc774\ub7ec\ud55c \uae30\uc220\ub4e4\uc740 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \ud328\ud134 \uc778\uc2dd\uc744 \ud1b5\ud574 \ud22c\uc790 \uacb0\uc815\uc744 \ubcf4\ub2e4 \uc815\uad50\ud558\uac8c \ub9cc\ub4e4\uc5b4\uc8fc\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uae30\ubcf8 \uac1c\ub150, \ubc29\ubc95\ub860, \uadf8\ub9ac\uace0 \uc2dc\ubbac\ub808\uc774\uc158 \uc808\ucc28\ub97c \uc790\uc138\ud788 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
\uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc774\ub780 \ucef4\ud4e8\ud130 \ud504\ub85c\uadf8\ub7a8\uc744 \uc774\uc6a9\ud558\uc5ec \uc2dc\uc7a5\uc5d0\uc11c\uc758 \uac70\ub798\ub97c \uc218\ud589\ud558\ub294 \uac83\uc73c\ub85c, \uc2dc\uc7a5\uc758 \ub370\uc774\ud130, \uac70\ub798 \uc804\ub7b5 \ubc0f \uc8fc\ubb38 \uc2e4\ud589\uc744 \uc790\ub3d9\ud654\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubc29\ubc95\uc740 \ud22c\uc790\uc790\uc758 \uac10\uc815\uc5d0 \uc601\ud5a5\uc744 \ubc1b\uc9c0 \uc54a\uc73c\uba70, \uace0\uc18d\uc73c\ub85c \ub300\ub7c9\uc758 \uac70\ub798\ub97c \uc218\ud589\ud560 \uc218 \uc788\ub294 \uc7a5\uc810\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\uba38\uc2e0\ub7ec\ub2dd\uc740 \ub370\uc774\ud130\ub85c\ubd80\ud130 \ud328\ud134\uc744 \ud559\uc2b5\ud558\uc5ec \uc608\uce21 \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \uae30\uc220\uc785\ub2c8\ub2e4. \ub525\ub7ec\ub2dd\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud558\uc704 \ubd84\uc57c\ub85c, \uc778\uacf5\uc2e0\uacbd\ub9dd\uc744 \ud1b5\ud574 \ubcf5\uc7a1\ud55c \ub370\uc774\ud130 \uad6c\uc870\ub97c \ud559\uc2b5\ud569\ub2c8\ub2e4.<\/p>\n
\ub525\ub7ec\ub2dd \ubaa8\ub378\uc740 \ud55c \uac1c \uc774\uc0c1\uc758 \uc740\ub2c9\uce35\uc744 \uac00\uc9c4 \uc2e0\uacbd\ub9dd\uc73c\ub85c, \uc77c\ubc18\uc801\uc73c\ub85c \uc785\ub825\uce35, \uc5ec\ub7ec \uac1c\uc758 \uc740\ub2c9\uce35, \uadf8\ub9ac\uace0 \ucd9c\ub825\uce35\uc73c\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4. \uac01 \ub178\ub4dc\ub294 \ud65c\uc131\ud654 \ud568\uc218\ub97c \ud1b5\ud574 \ucd9c\ub825\uac12\uc744 \uacc4\uc0b0\ud569\ub2c8\ub2e4.<\/p>\n
\uc804\ub7b5 \uac1c\ubc1c \uacfc\uc815\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e8\uacc4\ub85c \uc9c4\ud589\ub429\ub2c8\ub2e4.<\/p>\n
\ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc740 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130\uc5d0 \uae30\ubc18\ud574\uc57c \ud569\ub2c8\ub2e4. \uac00\uaca9 \ub370\uc774\ud130, \uac70\ub798\ub7c9, \uae08\uc735 \uc9c0\ud45c \ub4f1 \ub2e4\uc591\ud55c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n
import pandas as pd\n\n# Yahoo Finance\uc5d0\uc11c \ub370\uc774\ud130 \uc218\uc9d1\ndata = pd.read_csv('path_to_your_data.csv')\n<\/code><\/pre>\n3.2 \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h3>\n
\ub370\uc774\ud130\ub294 \ubd84\uc11d\uc5d0 \uc801\ud569\ud55c \ud615\ud0dc\ub85c \uac00\uacf5\ub418\uc5b4\uc57c \ud569\ub2c8\ub2e4. \uacb0\uce21\uce58\ub97c \ucc98\ub9ac\ud558\uace0, \uac12\uc744 \uc815\uaddc\ud654\ud558\ub294 \ub4f1\uc758 \uc791\uc5c5\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n
data.fillna(method='ffill', inplace=True)\ndata['normalized'] = (data['close'] - data['close'].mean()) \/ data['close'].std()\n<\/code><\/pre>\n3.3 \ud53c\ucc98 \uc0dd\uc131<\/h3>\n
\ud2b9\uc9d5(feature)\uc740 \ubaa8\ub378\uc758 \uc785\ub825\uc73c\ub85c \uc0ac\uc6a9\ub420 \ubcc0\uc218\ub4e4\uc785\ub2c8\ub2e4. \uae30\uc220\uc801 \uc9c0\ud45c, \uc774\ub3d9 \ud3c9\uade0, \uc218\uc775\ub960 \ub4f1\uc758 \ud53c\ucc98\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/p>\n
3.4 \ubaa8\ub378 \uc120\ud0dd \ubc0f \ud559\uc2b5<\/h3>\n
\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \ubaa8\ub378 \uc120\ud0dd\uc740 \uc804\ub7b5\uc5d0 \ub530\ub77c \ub2ec\ub77c\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c Random Forest, SVM, LSTM \ub4f1\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
from sklearn.ensemble import RandomForestClassifier\n\nmodel = RandomForestClassifier()\nmodel.fit(X_train, y_train)\n<\/code><\/pre>\n3.5 \ud3c9\uac00 \ubc0f \ud29c\ub2dd<\/h3>\n
\ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud574 \uad50\ucc28 \uac80\uc99d, \uc815\ud655\ub3c4 \ubc0f F1-score \ub4f1\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \ucd5c\uc801\uc758 \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\ub97c \uc124\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
4. \uc2dc\ubbac\ub808\uc774\uc158 \ubc0f \ubc31\ud14c\uc2a4\ud305<\/h2>\n
\uc804\ub7b5\uc758 \uc720\ud6a8\uc131\uc744 \uac80\uc99d\ud558\uae30 \uc704\ud574 \uacfc\uac70 \ub370\uc774\ud130\ub97c \ubc14\ud0d5\uc73c\ub85c \uc2dc\ubbac\ub808\uc774\uc158\uc744 \uc218\ud589\ud574\uc57c \ud569\ub2c8\ub2e4. \uc774\ub294 \ubc31\ud14c\uc2a4\ud305\uc774\ub77c\uace0\ub3c4 \ud558\uba70, \uc2e4\uc81c \uac70\ub798\uc5d0\uc11c\uc758 \uc131\uacfc\ub97c \uc608\uce21\ud558\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc90d\ub2c8\ub2e4.<\/p>\n
4.1 \ubc31\ud14c\uc2a4\ud305 \ud658\uacbd \uad6c\ucd95<\/h3>\n
\ubc31\ud14c\uc2a4\ud305\uc744 \uc704\ud55c \ud658\uacbd\uc744 \uad6c\ucd95\ud574\uc57c \ud569\ub2c8\ub2e4. \uc774 \ud658\uacbd\uc740 \ub370\uc774\ud130 \ud53c\ub4dc\ub97c \uc81c\uacf5\ud558\uace0, \uac70\ub798 \ubc0f \uc8fc\ubb38 \uc2e4\ud589 \ucc98\ub9ac, \uc2dc\ubbac\ub808\uc774\uc158 \uc2e4\ud589 \ub4f1\uc744 \ud3ec\ud568\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n
4.2 \uc131\uacfc \uc9c0\ud45c<\/h3>\n
\uc131\uacfc\ub97c \uce21\uc815\ud558\uae30 \uc704\ud55c \ub2e4\uc591\ud55c \uc9c0\ud45c\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc0e4\ud504 \uc9c0\uc218, \ucd5c\ub300 drawdown, \uc218\uc775\ub960 \ub4f1\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
def calculate_sharpe_ratio(returns):\n return returns.mean() \/ returns.std()\n<\/code><\/pre>\n4.3 \uacb0\uacfc \ud574\uc11d<\/h3>\n
\ubc31\ud14c\uc2a4\ud305 \uacb0\uacfc\ub294 \uac70\ub798 \uc804\ub7b5\uc758 \uc131\uacfc\ub97c \uc9c1\uad00\uc801\uc73c\ub85c \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \ub370\uc774\ud130 \uc624\ubc84\ud53c\ud305\uc744 \ud53c\ud558\uace0, \uc2e4\uc81c \ud658\uacbd\uc5d0\uc11c\uc758 \ubcc0\uc218\ub4e4\uc744 \uace0\ub824\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n
5. \uacb0\ub860<\/h2>\n
\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\ubc18\uc758 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc740 \ub370\uc774\ud130\uc5d0 \uc758\uc874\ud558\uba70, \uc815\ud655\ud55c \ubaa8\ub378\ub9c1\uacfc \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130\uac00 \uc911\uc694\ud569\ub2c8\ub2e4. \uc62c\ubc14\ub978 \uc2dc\ubbac\ub808\uc774\uc158 \uacfc\uc815\uc744 \ud1b5\ud574 \uc804\ub7b5\uc758 \uc720\ud6a8\uc131\uc744 \uac80\uc99d\ud558\uace0 \ub9ac\uc2a4\ud06c\ub97c \ucd5c\uc18c\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
6. \ucc38\uace0 \ubb38\ud5cc<\/h2>\n