diff --git a/backtest.ipynb b/backtest.ipynb index 9907a0c..f8fea5e 100644 --- a/backtest.ipynb +++ b/backtest.ipynb @@ -3,8 +3,8 @@ { "metadata": { "ExecuteTime": { - "end_time": "2026-01-19T09:22:09.640369Z", - "start_time": "2026-01-19T09:22:07.517191Z" + "end_time": "2026-01-19T10:00:35.820002Z", + "start_time": "2026-01-19T10:00:34.354216Z" } }, "cell_type": "code", @@ -19,7 +19,7 @@ ], "id": "d815a3591c4f9463", "outputs": [], - "execution_count": 7 + "execution_count": 2 }, { "cell_type": "code", @@ -27,8 +27,8 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2026-01-19T09:42:25.068816Z", - "start_time": "2026-01-19T09:42:18.026869Z" + "end_time": "2026-01-19T10:00:42.739695Z", + "start_time": "2026-01-19T10:00:35.820726Z" } }, "source": [ @@ -49,9 +49,9 @@ " )\n", " rows = cursor.fetchall()\n", "\n", - " df = pd.DataFrame.from_records(rows, columns=['trade_date', 'open', 'close', 'high', 'low', 'factor'])\n", + " dailies_df = pd.DataFrame.from_records(rows, columns=['trade_date', 'open', 'close', 'high', 'low', 'factor'])\n", "\n", - "df" + "dailies_df" ], "outputs": [ { @@ -205,12 +205,201 @@ "" ] }, - "execution_count": 17, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 17 + "execution_count": 3 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-01-19T10:01:46.133661Z", + "start_time": "2026-01-19T10:01:46.044719Z" + } + }, + "cell_type": "code", + "source": [ + "dailies_df['factor'] = dailies_df['factor'].fillna(1.0)\n", + "dailies_df['open'] = dailies_df['open'] * dailies_df['factor']\n", + "dailies_df['close'] = dailies_df['close'] * dailies_df['factor']\n", + "dailies_df['high'] = dailies_df['high'] * dailies_df['factor']\n", + "dailies_df['low'] = dailies_df['low'] * dailies_df['factor']\n", + "dailies_df" + ], + "id": "29226cf1c6fe9f94", + "outputs": [ + { + "data": { + "text/plain": [ + " trade_date open close high low \\\n", + "0 2025-01-02 191536.544976 186637.912112 192189.696025 185984.761064 \n", + "1 2025-01-03 186801.199875 185821.473302 188434.077496 185494.897778 \n", + "2 2025-01-06 185821.473302 186801.199875 187454.350923 183208.869108 \n", + "3 2025-01-07 186474.624350 187944.214209 188270.789734 185658.185540 \n", + "4 2025-01-08 187780.926447 187780.926447 189903.667355 186148.048826 \n", + ".. ... ... ... ... ... \n", + "183 2025-10-09 196779.714513 197995.476209 198169.156451 195737.633059 \n", + "184 2025-10-10 197474.435482 198516.516936 199558.598389 197300.755240 \n", + "185 2025-10-13 196606.034270 197995.476209 199037.557663 195911.313301 \n", + "186 2025-10-14 197821.795966 200948.040328 201469.081055 197300.755240 \n", + "187 2025-10-15 205385.713015 206472.409910 206834.642208 203936.783823 \n", + "\n", + " factor \n", + "0 127.7841 \n", + "1 127.7841 \n", + "2 127.7841 \n", + "3 127.7841 \n", + "4 127.7841 \n", + ".. ... \n", + "183 131.7878 \n", + "184 131.7878 \n", + "185 131.7878 \n", + "186 131.7878 \n", + "187 134.5794 \n", + "\n", + "[188 rows x 6 columns]" + ], + "text/html": [ + "
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