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Commit 8c5d6604 authored by Dr.李's avatar Dr.李
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remove unnecessary files

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notebooks/2017-10-18_new_strategy.ipynb deleted 100644 → 0
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notebooks/candidate_prod_model_20171204.ipynb deleted 100644 → 0
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notebooks/data_to_hdf.ipynb deleted 100644 → 0
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import sqlalchemy\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"server = 'rm-bp1psdz5615icqc0yo.mysql.rds.aliyuncs.com'\n",
"user = 'sa'\n",
"pwd = 'We051253524522'\n",
"\n",
"engine = sqlalchemy.create_engine('mysql+pymysql://{0}:{1}@{2}/multifactor?charset=utf8'.format(user, pwd, server))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"index_components = pd.read_sql('select * from index_components', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"index_components.to_hdf('multifactor.hdf', 'index_components')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"index_data = pd.read_sql('select * from index_data', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"index_data.to_hdf('multifactor.hdf', 'index_data')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"prod_500 = pd.read_sql('select * from prod_500', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"prod_500.to_hdf('multifactor.hdf', 'prod_500')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"risk_factor_500 = pd.read_sql('select * from risk_factor_500', engine)\n",
"risk_factor_500['Market'] = 1."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"risk_factor_500.to_hdf('multifactor.hdf', 'risk_factor_500')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"trade_data = pd.read_sql('select * from trade_data', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"trade_data.to_hdf('multifactor.hdf', 'trade_data')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"prod_300 = pd.read_sql('select * from prod_300', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"prod_300.to_hdf('multifactor.hdf', 'prod_300')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"risk_factor_300 = pd.read_sql('select * from risk_factor_300', engine)\n",
"risk_factor_300['Market'] = 1."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"risk_factor_300.to_hdf('multifactor.hdf', 'risk_factor_300')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"factor_data = pd.read_sql('select * from factor_data', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"factor_data.to_hdf('multifactor.hdf', 'factor_data')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"prod_500 = pd.read_hdf('multifactor.hdf', 'prod_500')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"prod_factor_cols = pd.Series(['CFinc1', 'BDTO', 'RVOL', 'CHV', 'VAL'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"prod_factor_cols.to_hdf('multifactor.hdf', 'prod_factor_cols')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"risk_factor_500 = pd.read_hdf('multifactor.hdf', 'risk_factor_500')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"del risk_factor_500['Bank']\n",
"del risk_factor_500['NonBankFinancial']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"risk_factor_cols = pd.Series(risk_factor_500.columns[2:].tolist())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"risk_factor_cols.to_hdf('multifactor.hdf', 'risk_factor_cols')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"factor_data = pd.read_hdf('multifactor.hdf', 'factor_data')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"common_factor_cols = pd.Series(factor_data.columns[5:].tolist())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"common_factor_cols.to_hdf('multifactor.hdf', 'common_factor_cols')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"risk_factor_500.columns"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"return_data_300 = pd.read_sql('select * from return_data_300', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"return_data_300.to_hdf('multifactor.hdf', 'return_data_300')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"return_data_500 = pd.read_sql('select * from return_data_500', engine)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"return_data_500.to_hdf('multifactor.hdf', 'return_data_500')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [default]",
"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": "3.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
notebooks/executor_example.ipynb deleted 100644 → 0
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notebooks/factor analysis.ipynb deleted 100644 → 0
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notebooks/full factor strategy.ipynb deleted 100644 → 0
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notebooks/model_comparing.ipynb deleted 100644 → 0
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notebooks/new_portfolio.ipynb deleted 100644 → 0
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notebooks/prod_model_20171117.ipynb deleted 100644 → 0
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notebooks/production_factor_analysis.ipynb deleted 100644 → 0
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notebooks/strategy with classifier models.ipynb deleted 100644 → 0
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notebooks/target_vol_executor.ipynb deleted 100644 → 0
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notebooks/zz500_factor_analysis.ipynb deleted 100644 → 0
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