\ucd5c\uadfc \uba87 \ub144\uac04 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c \uc778\uacf5\uc9c0\ub2a5(AI) \ubc0f \uba38\uc2e0\ub7ec\ub2dd(ML)\uc758 \ub3c4\uc785\uc774 \uae09\uc99d\ud558\uc600\uc2b5\ub2c8\ub2e4. \ud000\ud2b8 \ub9e4\ub9e4\ub97c \uc704\ud55c \uc54c\uace0\ub9ac\uc998\uc740 \uc774\ub860\uc801\uc73c\ub85c \uace0\uc218\uc775\uc744 \uc62c\ub9b4 \uc218 \uc788\ub294 \uc7a0\uc7ac\ub825\uc744 \uac00\uc9c0\uace0 \uc788\uc9c0\ub9cc, \uc774\ub97c \uc81c\ub300\ub85c \uad6c\ud604\ud558\uae30 \uc704\ud574\uc120 \uccb4\uacc4\uc801\uc778 \uc811\uadfc\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc18\uc758 \ud2b8\ub808\uc774\ub529 \uc54c\uace0\ub9ac\uc998\uc744 \uad6c\ucd95\ud558\ub294 \ubc29\ubc95\uacfc \uadf8 \uc911\uc5d0\uc11c\ub3c4 \uc790\uae30 \ud68c\uadc0 \ubaa8\ub378(AR, Autoregressive Model)\uc758 \uad6c\ucd95 \ubc29\ubc95\uc744 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
\uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \ud2b9\uc815\ud55c \uc870\uac74\uc744 \ub9cc\uc871\ud558\ub294 \uacbd\uc6b0 \uc790\ub3d9\uc73c\ub85c \ub9e4\ub9e4\ub97c \uc2e4\ud589\ud558\ub294 \ud504\ub85c\uadf8\ub7a8\uc744 \ud65c\uc6a9\ud55c \ub9e4\ub9e4 \ubc29\ubc95\uc785\ub2c8\ub2e4. \uc774 \ubc29\ubc95\uc740 \uc778\uac04 \uac70\ub798\uc790\ubcf4\ub2e4 \ube60\ub974\uace0 \uc815\ud655\ud558\uac8c \uc2dc\uc7a5\uc5d0 \ubc18\uc751\ud560 \uc218 \uc788\uc73c\uba70, \uac10\uc815\uc801 \uc694\uc778\uc744 \ubc30\uc81c\ud560 \uc218 \uc788\ub294 \uc774\uc810\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\uba38\uc2e0\ub7ec\ub2dd\uc740 \uc778\uacf5\uc9c0\ub2a5\uc758 \ud55c \ubd84\uc57c\ub85c, \ub370\uc774\ud130\ub85c\ubd80\ud130 \ud328\ud134\uc744 \ud559\uc2b5\ud558\uc5ec \uc608\uce21\uc774\ub098 \ubd84\ub958\ub97c \uc218\ud589\ud569\ub2c8\ub2e4. \ub525\ub7ec\ub2dd\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \uc885\ub958\ub85c, \uc778\uacf5\uc2e0\uacbd\ub9dd\uc744 \ud65c\uc6a9\ud558\uc5ec \ub354 \ubcf5\uc7a1\ud55c \ub370\uc774\ud130 \ud328\ud134\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\uba38\uc2e0\ub7ec\ub2dd\uc758 \ubaa9\ud45c\ub294 \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \uc54c\uace0\ub9ac\uc998\uc774 \uc790\uccb4\uc801\uc73c\ub85c \ud559\uc2b5\ud558\uc5ec \uc774\ud6c4\uc758 \ub370\uc774\ud130\ub97c \uc608\uce21\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc8fc\uc2dd \uac00\uaca9 \ub370\uc774\ud130\ub97c \ud65c\uc6a9\ud558\uc5ec \ubbf8\ub798\uc758 \uc8fc\uac00\ub97c \uc608\uce21\ud560 \uc218 \uc788\ub294 \ubaa8\ub378\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/p>\n
\ub525\ub7ec\ub2dd\uc740 \uc5ec\ub7ec \uce35\uc73c\ub85c \uad6c\uc131\ub41c \uc2e0\uacbd\ub9dd\uc744 \ud1b5\ud574 \ub370\uc774\ud130\uc758 \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \uc778\uc2dd\ud569\ub2c8\ub2e4. \ub525\ub7ec\ub2dd\uc758 \uc8fc\uc694 \uc7a5\uc810\uc740 \uc774\ubbf8\uc9c0 \uc778\uc2dd, \uc790\uc5f0\uc5b4 \ucc98\ub9ac, \uac8c\uc784 AI \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ub192\uc740 \uc131\ub2a5\uc744 \ubc1c\ud718\ud55c\ub2e4\ub294 \uac83\uc785\ub2c8\ub2e4.<\/p>\n
\uc790\uae30 \ud68c\uadc0 \ubaa8\ub378(AR)\uc740 \uacfc\uac70\uc758 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ubbf8\ub798 \uac12\uc744 \uc608\uce21\ud558\ub294 \ud1b5\uacc4\uc801 \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc774 \ubaa8\ub378\uc740 \uc8fc\uac00\uc640 \uac19\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\uc5d0 \uc801\ud569\ud569\ub2c8\ub2e4.<\/p>\n
AR \ubaa8\ub378\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \ud615\uc2dd\uc73c\ub85c \ud45c\ud604\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n
\n Y(t) = c + \u03d5\u2081Y(t-1) + \u03d5\u2082Y(t-2) + ... + \u03d5\u2096Y(t-k) + \u03b5(t)\n<\/pre>\n\uc5ec\uae30\uc11c:<\/p>\n
Y(t)<\/code>: \ud604\uc7ac \uc2dc\uac04 t\uc758 \uac12<\/li>\nc<\/code>: \uc0c1\uc218\ud56d<\/li>\n\u03d5<\/code>: \ud68c\uadc0\uacc4\uc218<\/li>\n\u03b5(t)<\/code>: \uc624\ucc28\ud56d<\/li>\n<\/ul>\n3.2 AR \ubaa8\ub378\uc758 \ud2b9\uc9d5<\/h3>\n
AR \ubaa8\ub378\uc740 \ub370\uc774\ud130\uac00 \uc790\uae30 \uc0c1\uad00\uc744 \uac00\uc9c0\ub294 \uacbd\uc6b0\uc5d0 \uc801\ud569\ud558\uba70, \ub370\uc774\ud130\uac00 \uc548\uc815\uc801\uc774\uace0 \ud328\ud134\uc774 \uc77c\uc815\ud560 \ub54c \ub354\uc6b1 \uc720\ud6a8\ud569\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \ub370\uc774\ud130\uac00 \ube44\uc815\uc0c1\uc801\uc774\uac70\ub098 \ubcc0\ub3d9\uc131\uc774 \ud070 \uacbd\uc6b0\uc5d0\ub294 \ud6a8\uacfc\uac00 \ub5a8\uc5b4\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
4. \uc790\uae30 \ud68c\uadc0 \ubaa8\ub378 \uad6c\ucd95 \ub2e8\uacc4<\/h2>\n
\uc790\uae30 \ud68c\uadc0 \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uae30 \uc704\ud574\uc11c\ub294 \ub2e4\uc74c\uc758 \ub2e8\uacc4\ub97c \ub530\ub77c\uc57c \ud569\ub2c8\ub2e4.<\/p>\n
4.1 \ub370\uc774\ud130 \uc218\uc9d1<\/h3>\n
\uba3c\uc800 \ud544\uc694\ud55c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud574\uc57c \ud569\ub2c8\ub2e4. \uc8fc\uc2dd \uac00\uaca9 \ub370\uc774\ud130, \uac70\ub798\ub7c9, \uad11\ubc94\uc704\ud55c \uacbd\uc81c \uc9c0\ud45c \ub4f1\uc774 \ud3ec\ud568\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc591\ud55c \ub370\uc774\ud130 \uc18c\uc2a4\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc73c\uba70, \uae08\uc735 \ub370\uc774\ud130 API\ub97c \ud1b5\ud574 \uc2e4\uc2dc\uac04 \ub370\uc774\ud130\ub97c \uac00\uc838\uc62c \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
4.2 \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h3>\n
\uc218\uc9d1\ud55c \ub370\uc774\ud130\ub294 \ubcf4\ud1b5 \ub178\uc774\uc988\uac00 \ud3ec\ud568\ub418\uc5b4 \uc788\uac70\ub098 \uacb0\uce21\uce58\uac00 \uc874\uc7ac\ud558\ubbc0\ub85c \ub370\uc774\ud130 \uc804\ucc98\ub9ac \uacfc\uc815\uc744 \ud1b5\ud574 \uc774\ub97c \uc815\uc81c\ud574\uc57c \ud569\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc5d0\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e8\uacc4\uac00 \ud3ec\ud568\ub429\ub2c8\ub2e4.<\/p>\n
\n- \uacb0\uce21\uce58 \ucc98\ub9ac: \uacb0\uce21\uce58\ub97c \uc81c\uac70\ud558\uac70\ub098 \uc801\uc808\ud55c \uac12\uc73c\ub85c \ub300\uccb4\ud569\ub2c8\ub2e4.<\/li>\n
- \uc815\uaddc\ud654: \ub370\uc774\ud130\uc758 \uc2a4\ucf00\uc77c\uc744 \ud1b5\uc77c\ud558\uc5ec \ubaa8\ub378 \ud559\uc2b5\uc744 \uc6d0\ud65c\ud558\uac8c \ud569\ub2c8\ub2e4.<\/li>\n
- \ud2b9\uc131 \uc0dd\uc131: \ud0c0\uc784\uc2a4\ud0ec\ud504, \uc774\ub3d9 \ud3c9\uade0, \ubcc0\ub3d9\uc131 \ub4f1 \ucd94\uac00\uc801\uc778 \ud2b9\uc131\uc744 \uc0dd\uc131\ud558\uc5ec \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n
4.3 \ubaa8\ub378 \uad6c\ucd95<\/h3>\n
\uc774\uc81c \uba38\uc2e0\ub7ec\ub2dd \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud574 \uc790\uae30 \ud68c\uadc0 \ubaa8\ub378\uc744 \uad6c\ucd95\ud569\ub2c8\ub2e4. Python\uc758 \uacbd\uc6b0 statsmodels<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec AR \ubaa8\ub378\uc744 \uc27d\uac8c \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\nimport pandas as pd\nfrom statsmodels.tsa.ar_model import AutoReg\n\n# \ub370\uc774\ud130 \ub85c\ub4dc\ndata = pd.read_csv('stock_prices.csv')\nprices = data['Close']\n\n# \uc790\uae30 \ud68c\uadc0 \ubaa8\ub378 \uc0dd\uc131\nmodel = AutoReg(prices, lags=5) # lag=5\nmodel_fit = model.fit()\nprint(model_fit.summary())\n<\/pre>\n4.4 \ubaa8\ub378 \ud3c9\uac00<\/h3>\n
\ubaa8\ub378\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud574 RMSE(\ub8e8\ud2b8 \ud3c9\uade0 \uc81c\uacf1 \uc624\ucc28), MAE(\uc808\ub300 \ud3c9\uade0 \uc624\ucc28) \ub4f1\uc758 \uc9c0\ud45c\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \uce21\uc815\ud569\ub2c8\ub2e4. \ud640\ub4dc\uc544\uc6c3 \uac80\uc99d\uc774\ub098 \uad50\ucc28 \uac80\uc99d\uc744 \ud65c\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc77c\ubc18\ud654 \uc131\ub2a5\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\nfrom sklearn.metrics import mean_squared_error\nimport numpy as np\n\n# \uc608\uce21\npredictions = model_fit.predict(start=len(prices), end=len(prices)+5-1) # \uc608\uce21 \uae30\uac04\nerror = np.sqrt(mean_squared_error(prices[-5:], predictions))\nprint(f'RMSE: {error}')\n<\/pre>\n4.5 \ub9e4\ub9e4 \uc804\ub7b5 \uad6c\ud604<\/h3>\n
\ubaa8\ub378\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uac1c\ubc1c\ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc608\uce21\uac12\uc774 \ud604\uc7ac \uac00\uaca9\ubcf4\ub2e4 \ub192\uc73c\uba74 \ub9e4\uc218, \ub0ae\uc73c\uba74 \ub9e4\ub3c4\ud558\ub294 \uac04\ub2e8\ud55c \uc804\ub7b5\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\nif predictions[-1] > prices.iloc[-1]:\n print(\"Buy Signal\")\nelse:\n print(\"Sell Signal\")\n<\/pre>\n5. \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\uae30 \ud68c\uadc0 \ubaa8\ub378<\/h2>\n
\uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ub2e8\uacc4 \ubc1c\uc804\ub41c \ud615\ud0dc\ub85c, \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\uae30 \ud68c\uadc0 \ubaa8\ub378\uc744 \uace0\ub824\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Keras\uc640 \uac19\uc740 \ud504\ub808\uc784\uc6cc\ud06c\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
5.1 LSTM(Long Short-Term Memory) \ubaa8\ub378<\/h3>\n
LSTM\uc740 \uc21c\ud658 \uc2e0\uacbd\ub9dd(RNN)\uc758 \ud55c \ud615\ud0dc\ub85c, \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130 \uc608\uce21\uc5d0 \uac15\ub825\ud55c \uc131\ub2a5\uc744 \ubc1c\ud718\ud569\ub2c8\ub2e4. \uacfc\uac70 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ud558\ub294 \uc2dc\ud000\uc2a4 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\ub294 \ub370 \ud2b9\ud654\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\nfrom keras.models import Sequential\nfrom keras.layers import LSTM, Dense\n\n# \ub370\uc774\ud130 \uc804\ucc98\ub9ac\n# ...\n\n# LSTM \ubaa8\ub378 \uad6c\ucd95\nmodel = Sequential()\nmodel.add(LSTM(50, activation='relu', input_shape=(n_timesteps, n_features)))\nmodel.add(Dense(1))\nmodel.compile(optimizer='adam', loss='mse')\n\n# \ubaa8\ub378 \ud559\uc2b5\nmodel.fit(X_train, y_train, epochs=200, verbose=0)\n<\/pre>\n5.2 \uc131\ub2a5 \ud3c9\uac00 \ubc0f \uc804\ub7b5<\/h3>\n
DNN \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud55c \ud6c4, \uc2e4\uc81c \ud504\ub85c\ub355\uc158 \ud658\uacbd\uc5d0\uc11c \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uad6c\ud604\ud569\ub2c8\ub2e4. \uc2e0\uc911\ud55c \ubc31\ud14c\uc2a4\ud305\uacfc \uc2e4\uac70\ub798 \uac80\uc99d\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n
6. \uacb0\ub860<\/h2>\n
\uc624\ub298 \uac15\uc88c\ub97c \ud1b5\ud574 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc18\uc758 \uc790\uae30 \ud68c\uadc0 \ubaa8\ub378 \uad6c\ucd95 \ubc0f \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uae30\ubcf8 \uac1c\ub150\uc744 \uc775\ud614\uc2b5\ub2c8\ub2e4. \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c\uc758 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \ub370\uc774\ud130 \uae30\ubc18\uc758 \uc608\uce21\uc744 \ud1b5\ud574 \uc218\uc775\uc744 \ucc3d\ucd9c\ud560 \uc218 \uc788\ub294 \uac00\ub2a5\uc131\uc744 \uac00\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ub530\ub77c\uc11c, \ub04a\uc784\uc5c6\ub294 \ud559\uc2b5\uacfc \uc2e4\ud5d8\uc744 \ud1b5\ud574 \uc790\uc2e0\ub9cc\uc758 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \uac1c\ubc1c\ud574 \ub098\uac00\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n
\uc55e\uc73c\ub85c \ub354 \uae4a\uc774 \uc788\ub294 \uc8fc\uc81c\ub85c \ub3cc\uc544\uc62c \uac83\uc744 \uae30\ub300\ud558\uba70, \uc9c8\ubb38\uc774\ub098 \ub17c\uc758\uac00 \ud544\uc694\ud558\uc2dc\uba74 \uc5b8\uc81c\ub4e0\uc9c0 \ub313\uae00\ub85c \ub0a8\uaca8\uc8fc\uc138\uc694. \uac10\uc0ac\ud569\ub2c8\ub2e4!<\/p>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"