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Removed IBKR related code

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jarno
2026-08-11 20:13:41 +03:00
parent 2165c4269d
commit 900b70d6df
6 changed files with 95 additions and 652 deletions
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notebooks/spy_direction_dataset.ipynb
+93 -93
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@@ -87,16 +87,16 @@
"output_type": "stream",
"text": [
"<class 'pandas.DataFrame'>\n",
"DatetimeIndex: 1255 entries, 2021-08-02 to 2026-07-31\n",
"DatetimeIndex: 1258 entries, 2021-08-02 to 2026-08-05\n",
"Data columns (total 4 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 SPY_close 1255 non-null float64\n",
" 1 VIX_close 1255 non-null float64\n",
" 2 TLT_close 1255 non-null float64\n",
" 3 USO_close 1255 non-null float64\n",
" 0 SPY_close 1258 non-null float64\n",
" 1 VIX_close 1258 non-null float64\n",
" 2 TLT_close 1258 non-null float64\n",
" 3 USO_close 1258 non-null float64\n",
"dtypes: float64(4)\n",
"memory usage: 49.0 KB\n"
"memory usage: 49.1 KB\n"
]
},
{
@@ -234,7 +234,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -364,7 +364,7 @@
"2021-10-15 -0.002202 0.030287 -0.003823 1.0 "
]
},
"execution_count": 4,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@@ -418,7 +418,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 4,
"metadata": {},
"outputs": [
{
@@ -458,24 +458,24 @@
" <tbody>\n",
" <tr>\n",
" <th>train</th>\n",
" <td>840</td>\n",
" <td>842</td>\n",
" <td>2021-10-11</td>\n",
" <td>2025-02-13</td>\n",
" <td>0.583333</td>\n",
" <td>2025-02-18</td>\n",
" <td>0.581948</td>\n",
" </tr>\n",
" <tr>\n",
" <th>validation</th>\n",
" <td>180</td>\n",
" <td>2025-02-14</td>\n",
" <td>2025-10-31</td>\n",
" <td>0.633333</td>\n",
" <td>2025-02-19</td>\n",
" <td>2025-11-04</td>\n",
" <td>0.638889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>test</th>\n",
" <td>181</td>\n",
" <td>2025-11-03</td>\n",
" <td>2026-07-24</td>\n",
" <td>0.569061</td>\n",
" <td>182</td>\n",
" <td>2025-11-05</td>\n",
" <td>2026-07-29</td>\n",
" <td>0.576923</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
@@ -484,12 +484,12 @@
"text/plain": [
" rows start_date end_date target_mean\n",
"split \n",
"train 840 2021-10-11 2025-02-13 0.583333\n",
"validation 180 2025-02-14 2025-10-31 0.633333\n",
"test 181 2025-11-03 2026-07-24 0.569061"
"train 842 2021-10-11 2025-02-18 0.581948\n",
"validation 180 2025-02-19 2025-11-04 0.638889\n",
"test 182 2025-11-05 2026-07-29 0.576923"
]
},
"execution_count": 5,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@@ -543,17 +543,17 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Rows: 1,201\n",
"Rows: 1,204\n",
"Feature columns: ['SPY_ret_5', 'SPY_ret_20', 'SPY_dist_sma50', 'VIX_change_5', 'VIX_rank_20', 'TLT_ret_10', 'USO_ret_5', 'SPY_TLT_ratio_ret']\n",
"Target column: spy_up_5d\n",
"Training matrix shape: (840, 8)\n"
"Training matrix shape: (842, 8)\n"
]
},
{
@@ -592,16 +592,16 @@
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201.000000</td>\n",
" <td>1201</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204.000000</td>\n",
" <td>1204</td>\n",
" </tr>\n",
" <tr>\n",
" <th>unique</th>\n",
@@ -640,32 +640,32 @@
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>840</td>\n",
" <td>842</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>0.002502</td>\n",
" <td>0.009848</td>\n",
" <td>0.011028</td>\n",
" <td>0.017763</td>\n",
" <td>0.403476</td>\n",
" <td>-0.004099</td>\n",
" <td>0.005024</td>\n",
" <td>0.004880</td>\n",
" <td>0.588676</td>\n",
" <td>0.002464</td>\n",
" <td>0.009816</td>\n",
" <td>0.010973</td>\n",
" <td>0.017820</td>\n",
" <td>0.404506</td>\n",
" <td>-0.004103</td>\n",
" <td>0.004938</td>\n",
" <td>0.004838</td>\n",
" <td>0.589701</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.023057</td>\n",
" <td>0.043558</td>\n",
" <td>0.037315</td>\n",
" <td>0.299417</td>\n",
" <td>0.337501</td>\n",
" <td>0.028502</td>\n",
" <td>0.052628</td>\n",
" <td>0.027606</td>\n",
" <td>0.492279</td>\n",
" <td>0.023044</td>\n",
" <td>0.043515</td>\n",
" <td>0.037287</td>\n",
" <td>0.299050</td>\n",
" <td>0.337773</td>\n",
" <td>0.028469</td>\n",
" <td>0.052606</td>\n",
" <td>0.027586</td>\n",
" <td>0.492092</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
@@ -683,40 +683,40 @@
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>-0.009601</td>\n",
" <td>-0.016509</td>\n",
" <td>-0.008656</td>\n",
" <td>-0.056615</td>\n",
" <td>-0.009749</td>\n",
" <td>-0.016557</td>\n",
" <td>-0.008704</td>\n",
" <td>-0.056606</td>\n",
" <td>0.100000</td>\n",
" <td>-0.023304</td>\n",
" <td>-0.025866</td>\n",
" <td>-0.010013</td>\n",
" <td>-0.023139</td>\n",
" <td>-0.025950</td>\n",
" <td>-0.010029</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>0.003798</td>\n",
" <td>0.015725</td>\n",
" <td>0.017802</td>\n",
" <td>-0.018570</td>\n",
" <td>0.003749</td>\n",
" <td>0.015639</td>\n",
" <td>0.017755</td>\n",
" <td>-0.018430</td>\n",
" <td>0.300000</td>\n",
" <td>-0.004435</td>\n",
" <td>0.004950</td>\n",
" <td>0.005537</td>\n",
" <td>-0.004429</td>\n",
" <td>0.004869</td>\n",
" <td>0.005508</td>\n",
" <td>1.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>0.015955</td>\n",
" <td>0.038179</td>\n",
" <td>0.038282</td>\n",
" <td>0.030814</td>\n",
" <td>0.015950</td>\n",
" <td>0.038167</td>\n",
" <td>0.038124</td>\n",
" <td>0.030815</td>\n",
" <td>0.750000</td>\n",
" <td>0.014227</td>\n",
" <td>0.032486</td>\n",
" <td>0.021390</td>\n",
" <td>0.014188</td>\n",
" <td>0.032295</td>\n",
" <td>0.021358</td>\n",
" <td>1.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
@@ -739,33 +739,33 @@
],
"text/plain": [
" SPY_ret_5 SPY_ret_20 SPY_dist_sma50 VIX_change_5 VIX_rank_20 \\\n",
"count 1201.000000 1201.000000 1201.000000 1201.000000 1201.000000 \n",
"count 1204.000000 1204.000000 1204.000000 1204.000000 1204.000000 \n",
"unique NaN NaN NaN NaN NaN \n",
"top NaN NaN NaN NaN NaN \n",
"freq NaN NaN NaN NaN NaN \n",
"mean 0.002502 0.009848 0.011028 0.017763 0.403476 \n",
"std 0.023057 0.043558 0.037315 0.299417 0.337501 \n",
"mean 0.002464 0.009816 0.010973 0.017820 0.404506 \n",
"std 0.023044 0.043515 0.037287 0.299050 0.337773 \n",
"min -0.114962 -0.123975 -0.141995 -0.387709 0.050000 \n",
"25% -0.009601 -0.016509 -0.008656 -0.056615 0.100000 \n",
"50% 0.003798 0.015725 0.017802 -0.018570 0.300000 \n",
"75% 0.015955 0.038179 0.038282 0.030814 0.750000 \n",
"25% -0.009749 -0.016557 -0.008704 -0.056606 0.100000 \n",
"50% 0.003749 0.015639 0.017755 -0.018430 0.300000 \n",
"75% 0.015950 0.038167 0.038124 0.030815 0.750000 \n",
"max 0.082843 0.157566 0.088105 3.846154 1.000000 \n",
"\n",
" TLT_ret_10 USO_ret_5 SPY_TLT_ratio_ret spy_up_5d split \n",
"count 1201.000000 1201.000000 1201.000000 1201.000000 1201 \n",
"count 1204.000000 1204.000000 1204.000000 1204.000000 1204 \n",
"unique NaN NaN NaN NaN 3 \n",
"top NaN NaN NaN NaN train \n",
"freq NaN NaN NaN NaN 840 \n",
"mean -0.004099 0.005024 0.004880 0.588676 NaN \n",
"std 0.028502 0.052628 0.027606 0.492279 NaN \n",
"freq NaN NaN NaN NaN 842 \n",
"mean -0.004103 0.004938 0.004838 0.589701 NaN \n",
"std 0.028469 0.052606 0.027586 0.492092 NaN \n",
"min -0.092880 -0.196652 -0.117208 0.000000 NaN \n",
"25% -0.023304 -0.025866 -0.010013 0.000000 NaN \n",
"50% -0.004435 0.004950 0.005537 1.000000 NaN \n",
"75% 0.014227 0.032486 0.021390 1.000000 NaN \n",
"25% -0.023139 -0.025950 -0.010029 0.000000 NaN \n",
"50% -0.004429 0.004869 0.005508 1.000000 NaN \n",
"75% 0.014188 0.032295 0.021358 1.000000 NaN \n",
"max 0.091322 0.327273 0.129204 1.000000 NaN "
]
},
"execution_count": 6,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@@ -787,14 +787,14 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(PosixPath('/home/jarno/repos/trading-bot/data/training/spy_direction_5d.parquet'),\n",
" (1201, 11),\n",
" (1204, 11),\n",
" date SPY_ret_5 SPY_ret_20 SPY_dist_sma50 VIX_change_5 \\\n",
" 0 2021-10-11 0.014114 -0.026625 -0.018145 -0.090869 \n",
" 1 2021-10-12 0.001201 -0.023752 -0.020386 -0.074091 \n",
@@ -810,7 +810,7 @@
" 4 0.05 -0.002202 0.030287 -0.003823 1.0 train )"
]
},
"execution_count": 7,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}