mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-27 18:57:55 +00:00
217 lines
66 KiB
Plaintext
217 lines
66 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"\u001b[2m\u001b[36m(__load_df pid=33339)\u001b[0m /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33339)\u001b[0m result = getattr(ufunc, method)(*inputs, **kwargs)\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33345)\u001b[0m /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33345)\u001b[0m result = getattr(ufunc, method)(*inputs, **kwargs)\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33342)\u001b[0m /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33342)\u001b[0m result = getattr(ufunc, method)(*inputs, **kwargs)\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33344)\u001b[0m /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33344)\u001b[0m result = getattr(ufunc, method)(*inputs, **kwargs)\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33349)\u001b[0m /usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33349)\u001b[0m result = getattr(ufunc, method)(*inputs, **kwargs)\n",
|
|
"\u001b[2m\u001b[36m(__load_df pid=33341)\u001b[0m \n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"import pandas_ta as ta\n",
|
|
"from config.config import get_default_level_2_daily_config\n",
|
|
"from config.preprocess import preprocess_config\n",
|
|
"from data_loader.load_data import load_data\n",
|
|
"import seaborn as sns\n",
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"model_config, training_config, data_config = get_default_level_2_daily_config()\n",
|
|
"model_config, training_config, data_config = preprocess_config(model_config, training_config, data_config)\n",
|
|
"\n",
|
|
"data_config['target_asset'] = data_config['assets'][0]\n",
|
|
"X, y, target_returns = load_data(**data_config)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<AxesSubplot:>"
|
|
]
|
|
},
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"X['sth_nupl_fracdiff_30'].plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/usr/local/anaconda3/envs/quant/lib/python3.9/site-packages/pandas/core/arraylike.py:364: RuntimeWarning: invalid value encountered in log\n",
|
|
" result = getattr(ufunc, method)(*inputs, **kwargs)\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<AxesSubplot:>"
|
|
]
|
|
},
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"np.log(X['sth_nupl_fracdiff_30']).plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<AxesSubplot:>"
|
|
]
|
|
},
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"X['BTC_USD_returns'].plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# pd.plotting.scatter_matrix(X, figsize=(12, 12));"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Index(['ADA_USD_returns', 'ADA_USD_mom_10', 'ADA_USD_mom_20', 'ADA_USD_mom_30',\n",
|
|
" 'ADA_USD_mom_60', 'ADA_USD_mom_90', 'ADA_USD_vol_10', 'ADA_USD_vol_20',\n",
|
|
" 'ADA_USD_vol_30', 'ADA_USD_vol_60',\n",
|
|
" ...\n",
|
|
" 'sth_nupl_fracdiff_30', 'lth_nupl_returns', 'lth_nupl_fracdiff_10',\n",
|
|
" 'lth_nupl_fracdiff_30', 'ssr_returns', 'ssr_fracdiff_10',\n",
|
|
" 'ssr_fracdiff_30', 'bvin_returns', 'bvin_fracdiff_10',\n",
|
|
" 'bvin_fracdiff_30'],\n",
|
|
" dtype='object', length=588)"
|
|
]
|
|
},
|
|
"execution_count": 8,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"X.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"interpreter": {
|
|
"hash": "51432b8e5767c06330d9b51dfad63f9db0ea39868e37d921b9c2e277373f8d11"
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3.9.2 64-bit ('deeplearning': conda)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.9.7"
|
|
},
|
|
"orig_nbformat": 4
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|