analysis.ipynb

{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"tags":[]},"outputs":[],"source":["import os\n","\n","import matplotlib.pyplot as plt\n","import numpy as np\n","import pandas as pd\n","import seaborn as sns\n","from mpl_toolkits.mplot3d import Axes3D\n","from sklearn.metrics import silhouette_score\n","from sklearn.preprocessing import StandardScaler\n","\n","from core.generator import weekly\n","from core.model import Hierarchy\n","\n","# %matplotlib qt"]},{"cell_type":"code","execution_count":2,"metadata":{},"outputs":[],"source":["stock    = '0001.HK'\n","data_dir = './data/processed'\n","lexicon  = 'SenticNet5'\n","split    = 0.8\n","\n","YCOL = ['pct_chg']"]},{"cell_type":"code","execution_count":3,"metadata":{},"outputs":[{"output_type":"execute_result","data":{"text/plain":"             close    volume        ma7       ma14       ma21  pct_chg  \\\ndate                                                                     \n2003-04-03   42.80   7906900   44.01429   45.10000   45.12381 -2.05950   \n2003-04-04   44.10   7601200   43.78571   45.12143   44.96190  3.03738   \n2003-04-07   45.10   6543800   43.84286   45.13571   44.88571  2.26757   \n2003-04-08   44.40   7190100   43.80000   44.90714   44.85714 -1.55211   \n2003-04-09   42.60  11624700   43.72857   44.52857   44.78095 -4.05405   \n...            ...       ...        ...        ...        ...      ...   \n2008-03-11  109.80  11700900  110.82857  113.30000  115.02857  3.68272   \n2008-03-12  111.00   9031900  110.32857  113.03571  114.89048  1.09290   \n2008-03-13  106.00   7283700  109.40000  112.60000  114.42857 -4.50450   \n2008-03-14  104.50   6972700  108.08571  112.07143  113.69048 -1.41509   \n2008-03-17   99.05  11528600  106.17857  110.97500  112.62619 -5.21531   \n\n                upper     mid      lower       adx  ...  inhpase  quadrature  \\\ndate                                                ...                        \n2003-04-03   44.84599   43.54   42.23401  19.63993  ... -1.81836    -0.75161   \n2003-04-04   44.32686   43.42   42.51314  19.80534  ... -1.74026    -0.06861   \n2003-04-07   45.35571   43.82   42.28429  19.09246  ... -1.90128    -0.08068   \n2003-04-08   45.54525   44.02   42.49475  18.43050  ... -1.95259     1.29353   \n2003-04-09   45.71416   43.80   41.88584  19.02330  ... -0.93676     1.75621   \n...               ...     ...        ...       ...  ...      ...         ...   \n2008-03-11  115.76080  109.76  103.75920  20.64984  ... -3.81804    -5.80393   \n2008-03-12  114.08358  109.22  104.35642  19.98822  ... -4.31154    -1.47933   \n2008-03-13  112.10000  107.94  103.78000  19.94201  ... -3.77835    -1.06090   \n2008-03-14  112.44656  107.44  102.43344  20.22910  ... -4.93245    -1.04576   \n2008-03-17  114.55377  106.07   97.58623  21.14589  ... -5.51433     2.22804   \n\n               sine  leadsine  trendmode  polarity  pleasantness  attention  \\\ndate                                                                          \n2003-04-03 -0.99992  -0.69787          1   0.26852      -0.06965    0.36093   \n2003-04-04 -0.94176  -0.42813          1   0.26513       0.02843    0.17367   \n2003-04-07 -0.79391  -0.13143          1   0.29441       0.05087    0.33754   \n2003-04-08 -0.39198   0.37335          0   0.24803       0.06883    0.32927   \n2003-04-09 -0.07812   0.64971          1   0.00763      -0.61105    0.33856   \n...             ...       ...        ...       ...           ...        ...   \n2008-03-11 -0.53596   0.21799          1   0.42812       0.28148    0.31179   \n2008-03-12 -0.59801   0.14389          1   0.85050       0.34478    1.75549   \n2008-03-13 -0.41632   0.34854          1   0.01556       0.01233    0.02000   \n2008-03-14 -0.18986   0.56000          1   0.75549       0.44020    0.55626   \n2008-03-17  0.17061   0.81738          1   0.55839       0.19716    0.81959   \n\n            sensitivity  aptitude  \ndate                               \n2003-04-03     -0.04510   0.29688  \n2003-04-04     -0.00665   0.41081  \n2003-04-07      0.01065   0.16199  \n2003-04-08     -0.04072   0.16143  \n2003-04-09     -0.16676   0.43990  \n...                 ...       ...  \n2008-03-11      0.07546   0.54213  \n2008-03-12      0.64964   0.66897  \n2008-03-13      0.00000   0.01422  \n2008-03-14      0.18995   0.56660  \n2008-03-17      0.15334   0.31497  \n\n[1226 rows x 34 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>close</th>\n      <th>volume</th>\n      <th>ma7</th>\n      <th>ma14</th>\n      <th>ma21</th>\n      <th>pct_chg</th>\n      <th>upper</th>\n      <th>mid</th>\n      <th>lower</th>\n      <th>adx</th>\n      <th>...</th>\n      <th>inhpase</th>\n      <th>quadrature</th>\n      <th>sine</th>\n      <th>leadsine</th>\n      <th>trendmode</th>\n      <th>polarity</th>\n      <th>pleasantness</th>\n      <th>attention</th>\n      <th>sensitivity</th>\n      <th>aptitude</th>\n    </tr>\n    <tr>\n      <th>date</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2003-04-03</th>\n      <td>42.80</td>\n      <td>7906900</td>\n      <td>44.01429</td>\n      <td>45.10000</td>\n      <td>45.12381</td>\n      <td>-2.05950</td>\n      <td>44.84599</td>\n      <td>43.54</td>\n      <td>42.23401</td>\n      <td>19.63993</td>\n      <td>...</td>\n      <td>-1.81836</td>\n      <td>-0.75161</td>\n      <td>-0.99992</td>\n      <td>-0.69787</td>\n      <td>1</td>\n      <td>0.26852</td>\n      <td>-0.06965</td>\n      <td>0.36093</td>\n      <td>-0.04510</td>\n      <td>0.29688</td>\n    </tr>\n    <tr>\n      <th>2003-04-04</th>\n      <td>44.10</td>\n      <td>7601200</td>\n      <td>43.78571</td>\n      <td>45.12143</td>\n      <td>44.96190</td>\n      <td>3.03738</td>\n      <td>44.32686</td>\n      <td>43.42</td>\n      <td>42.51314</td>\n      <td>19.80534</td>\n      <td>...</td>\n      <td>-1.74026</td>\n      <td>-0.06861</td>\n      <td>-0.94176</td>\n      <td>-0.42813</td>\n      <td>1</td>\n      <td>0.26513</td>\n      <td>0.02843</td>\n      <td>0.17367</td>\n      <td>-0.00665</td>\n      <td>0.41081</td>\n    </tr>\n    <tr>\n      <th>2003-04-07</th>\n      <td>45.10</td>\n      <td>6543800</td>\n      <td>43.84286</td>\n      <td>45.13571</td>\n      <td>44.88571</td>\n      <td>2.26757</td>\n      <td>45.35571</td>\n      <td>43.82</td>\n      <td>42.28429</td>\n      <td>19.09246</td>\n      <td>...</td>\n      <td>-1.90128</td>\n      <td>-0.08068</td>\n      <td>-0.79391</td>\n      <td>-0.13143</td>\n      <td>1</td>\n      <td>0.29441</td>\n      <td>0.05087</td>\n      <td>0.33754</td>\n      <td>0.01065</td>\n      <td>0.16199</td>\n    </tr>\n    <tr>\n      <th>2003-04-08</th>\n      <td>44.40</td>\n      <td>7190100</td>\n      <td>43.80000</td>\n      <td>44.90714</td>\n      <td>44.85714</td>\n      <td>-1.55211</td>\n      <td>45.54525</td>\n      <td>44.02</td>\n      <td>42.49475</td>\n      <td>18.43050</td>\n      <td>...</td>\n      <td>-1.95259</td>\n      <td>1.29353</td>\n      <td>-0.39198</td>\n      <td>0.37335</td>\n      <td>0</td>\n      <td>0.24803</td>\n      <td>0.06883</td>\n      <td>0.32927</td>\n      <td>-0.04072</td>\n      <td>0.16143</td>\n    </tr>\n    <tr>\n      <th>2003-04-09</th>\n      <td>42.60</td>\n      <td>11624700</td>\n      <td>43.72857</td>\n      <td>44.52857</td>\n      <td>44.78095</td>\n      <td>-4.05405</td>\n      <td>45.71416</td>\n      <td>43.80</td>\n      <td>41.88584</td>\n      <td>19.02330</td>\n      <td>...</td>\n      <td>-0.93676</td>\n      <td>1.75621</td>\n      <td>-0.07812</td>\n      <td>0.64971</td>\n      <td>1</td>\n      <td>0.00763</td>\n      <td>-0.61105</td>\n      <td>0.33856</td>\n      <td>-0.16676</td>\n      <td>0.43990</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>2008-03-11</th>\n      <td>109.80</td>\n      <td>11700900</td>\n      <td>110.82857</td>\n      <td>113.30000</td>\n      <td>115.02857</td>\n      <td>3.68272</td>\n      <td>115.76080</td>\n      <td>109.76</td>\n      <td>103.75920</td>\n      <td>20.64984</td>\n      <td>...</td>\n      <td>-3.81804</td>\n      <td>-5.80393</td>\n      <td>-0.53596</td>\n      <td>0.21799</td>\n      <td>1</td>\n      <td>0.42812</td>\n      <td>0.28148</td>\n      <td>0.31179</td>\n      <td>0.07546</td>\n      <td>0.54213</td>\n    </tr>\n    <tr>\n      <th>2008-03-12</th>\n      <td>111.00</td>\n      <td>9031900</td>\n      <td>110.32857</td>\n      <td>113.03571</td>\n      <td>114.89048</td>\n      <td>1.09290</td>\n      <td>114.08358</td>\n      <td>109.22</td>\n      <td>104.35642</td>\n      <td>19.98822</td>\n      <td>...</td>\n      <td>-4.31154</td>\n      <td>-1.47933</td>\n      <td>-0.59801</td>\n      <td>0.14389</td>\n      <td>1</td>\n      <td>0.85050</td>\n      <td>0.34478</td>\n      <td>1.75549</td>\n      <td>0.64964</td>\n      <td>0.66897</td>\n    </tr>\n    <tr>\n      <th>2008-03-13</th>\n      <td>106.00</td>\n      <td>7283700</td>\n      <td>109.40000</td>\n      <td>112.60000</td>\n      <td>114.42857</td>\n      <td>-4.50450</td>\n      <td>112.10000</td>\n      <td>107.94</td>\n      <td>103.78000</td>\n      <td>19.94201</td>\n      <td>...</td>\n      <td>-3.77835</td>\n      <td>-1.06090</td>\n      <td>-0.41632</td>\n      <td>0.34854</td>\n      <td>1</td>\n      <td>0.01556</td>\n      <td>0.01233</td>\n      <td>0.02000</td>\n      <td>0.00000</td>\n      <td>0.01422</td>\n    </tr>\n    <tr>\n      <th>2008-03-14</th>\n      <td>104.50</td>\n      <td>6972700</td>\n      <td>108.08571</td>\n      <td>112.07143</td>\n      <td>113.69048</td>\n      <td>-1.41509</td>\n      <td>112.44656</td>\n      <td>107.44</td>\n      <td>102.43344</td>\n      <td>20.22910</td>\n      <td>...</td>\n      <td>-4.93245</td>\n      <td>-1.04576</td>\n      <td>-0.18986</td>\n      <td>0.56000</td>\n      <td>1</td>\n      <td>0.75549</td>\n      <td>0.44020</td>\n      <td>0.55626</td>\n      <td>0.18995</td>\n      <td>0.56660</td>\n    </tr>\n    <tr>\n      <th>2008-03-17</th>\n      <td>99.05</td>\n      <td>11528600</td>\n      <td>106.17857</td>\n      <td>110.97500</td>\n      <td>112.62619</td>\n      <td>-5.21531</td>\n      <td>114.55377</td>\n      <td>106.07</td>\n      <td>97.58623</td>\n      <td>21.14589</td>\n      <td>...</td>\n      <td>-5.51433</td>\n      <td>2.22804</td>\n      <td>0.17061</td>\n      <td>0.81738</td>\n      <td>1</td>\n      <td>0.55839</td>\n      <td>0.19716</td>\n      <td>0.81959</td>\n      <td>0.15334</td>\n      <td>0.31497</td>\n    </tr>\n  </tbody>\n</table>\n<p>1226 rows × 34 columns</p>\n</div>"},"metadata":{},"execution_count":3}],"source":["indicator = pd.read_csv(os.path.join(data_dir, 'indicators', '%s.csv' % stock), index_col='date', parse_dates=True)\n","sentiment = pd.read_csv(os.path.join(data_dir, 'sentiments', lexicon, '%s.csv' % stock), index_col='date', parse_dates=True)\n","data      = pd.merge(indicator, sentiment, how='left', left_index=True, right_index=True)\n","data      = data.drop(['open', 'high', 'low', 'adj close'], axis=1)\n","data      = data.fillna(0)\n","data"]},{"cell_type":"code","execution_count":4,"metadata":{"tags":[]},"outputs":[{"output_type":"stream","name":"stdout","text":"get best cluster parameters: tau = 4, n = 3, score = 0.214\n"}],"source":["taus = np.arange(1, 8)\n","n_class = np.arange(2, 10)\n","\n","scores = list()\n","for tau in taus:\n","    score = list()\n","    X = np.array([x.mean().values for x in weekly(data, tau)])\n","    X = StandardScaler().fit_transform(X)\n","    for n in n_class:\n","        clster = Hierarchy(n, method='ward', criterion='maxclust').fit(X)\n","        score.append(clster.silhouette_score_)\n","    scores.append(score)\n","scores = np.array(scores).T\n","best_tau = taus[np.argmax(scores) % len(taus)]\n","best_n   = n_class[np.argmax(scores) // len(taus)]\n","print('get best cluster parameters: tau = %d, n = %d, score = %.3f' % (best_tau, best_n, scores.max()))"]},{"cell_type":"code","execution_count":5,"metadata":{"tags":[]},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/svg+xml":"<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (https://matplotlib.org/) -->\n<svg height=\"302.4pt\" version=\"1.1\" viewBox=\"0 0 446.4 302.4\" width=\"446.4pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <defs>\n  <style type=\"text/css\">\n*{stroke-linecap:butt;stroke-linejoin:round;}\n  </style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 302.4 \nL 446.4 302.4 \nL 446.4 0 \nL 0 0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g 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= plt.figure()\n","ax = Axes3D(fig)\n","grid = np.meshgrid(taus, n_class)\n","ax.plot_surface(grid[0], grid[1], scores, cmap='rainbow')\n","ax.view_init(elev=25, azim=50)\n","ax.set_xlabel('Period $\\\\tau$')\n","ax.set_ylabel('Style number $n$')\n","ax.set_zlabel('Silhouette score')\n","plt.show()"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[],"source":["def class_change(X, y, center, radius, rank=1):\n","    change = abs(np.sign(np.append(0, np.diff(y,rank)))) # change[0] === 0\n","    dist = []\n","    for i in range(len(change)):\n","        if change[i] == 0:\n","            dist.append(0)\n","        else:\n","            precenter = center[y[i-rank]]\n","            preradius = radius[y[i-rank]]\n","            dist.append(abs((np.linalg.norm(X[i] - precenter) - preradius) / preradius))\n","    return dist"]},{"cell_type":"code","execution_count":7,"metadata":{"tags":[]},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x216 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= best_tau\n","n_class = np.arange(2,6)\n","\n","X = [x.mean().values for x in weekly(data, tau)]\n","X = StandardScaler().fit_transform(X)\n","fig, ax = plt.subplots(1, 4, figsize=(15, 3), sharey=True)\n","for i, n in enumerate(n_class):\n","    cluster = Hierarchy(n, method='ward', criterion='maxclust').fit(X)\n","    dist = class_change(X, cluster.predict(), cluster.center, cluster.radius)\n","    ax[i].bar(np.arange(len(dist)), dist, color='C3')\n","    ax[i].set_xlabel('Period', fontsize=10)\n","    ax[i].set_ylabel('Distance between styles', fontsize=10)\n","    ax[i].set_title('Style number = %d' % n, fontsize=10)\n","plt.tight_layout()\n","plt.show()"]},{"cell_type":"code","execution_count":8,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x216 with 4 Axes>","image/svg+xml":"<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  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= best_n\n","taus = np.arange(1,5)\n","\n","fig, ax = plt.subplots(1, 4, figsize=(15, 3), sharey=True)\n","for i, tau in enumerate(taus):\n","    X = [x.mean().values for x in weekly(data, tau)]\n","    X = StandardScaler().fit_transform(X)\n","    cluster = Hierarchy(n, method='ward', criterion='maxclust').fit(X)\n","    dist = class_change(X, cluster.predict(), cluster.center, cluster.radius)\n","    ax[i].bar(np.arange(len(dist)), dist, color='C3')\n","    ax[i].set_xlabel('Period', fontsize=10)\n","    ax[i].set_ylabel('Distance between styles', fontsize=10)\n","    ax[i].set_title('window size = %d' % tau, fontsize=10)\n","plt.tight_layout()\n","plt.show()"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x158.4 with 2 Axes>","image/svg+xml":"<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  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\n"},"metadata":{"needs_background":"light"}}],"source":["tau, n = best_tau, best_n\n","\n","X = [x.mean().values for x in weekly(data, tau)]\n","X = StandardScaler().fit_transform(X)\n","\n","cluster = Hierarchy(n, method='ward', criterion='maxclust').fit(X)\n","center = cluster.center\n","fig, ax = plt.subplots(1, 1, figsize=(15, 2.2))\n","ax = sns.heatmap(center,-1, 1, annot=True, square=True, cmap='RdYlGn', fmt='.1f', xticklabels=data.columns, ax=ax)\n","ax.tick_params(labelsize=10)\n","plt.tight_layout()\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":[]}],"nbformat":4,"nbformat_minor":2,"metadata":{"language_info":{"name":"python","codemirror_mode":{"name":"ipython","version":3},"version":"3.7.6-final"},"orig_nbformat":2,"file_extension":".py","mimetype":"text/x-python","name":"python","npconvert_exporter":"python","pygments_lexer":"ipython3","version":3,"kernelspec":{"name":"python_defaultSpec_1598510892613","display_name":"Python 3.7.5 64-bit ('base': conda)"}}}