{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.13"
},
"colab": {
"name": "wrds_crsp1.ipynb",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
""
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "y2C0OgijlDzv",
"outputId": "cc7485eb-9cd6-4ce6-fa7d-f5653cb23e13"
},
"source": [
"!pip install wrds"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Collecting wrds\n",
" Downloading wrds-3.1.1-py3-none-any.whl (12 kB)\n",
"Requirement already satisfied: sqlalchemy in /usr/local/lib/python3.7/dist-packages (from wrds) (1.4.37)\n",
"Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from wrds) (1.21.6)\n",
"Collecting mock\n",
" Downloading mock-4.0.3-py3-none-any.whl (28 kB)\n",
"Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from wrds) (1.3.5)\n",
"Collecting psycopg2-binary\n",
" Downloading psycopg2_binary-2.9.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.0 MB)\n",
"\u001b[K |████████████████████████████████| 3.0 MB 6.6 MB/s \n",
"\u001b[?25hRequirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->wrds) (2.8.2)\n",
"Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->wrds) (2022.1)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->wrds) (1.15.0)\n",
"Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.7/dist-packages (from sqlalchemy->wrds) (1.1.2)\n",
"Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from sqlalchemy->wrds) (4.11.4)\n",
"Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->sqlalchemy->wrds) (4.1.1)\n",
"Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->sqlalchemy->wrds) (3.8.0)\n",
"Installing collected packages: psycopg2-binary, mock, wrds\n",
"Successfully installed mock-4.0.3 psycopg2-binary-2.9.3 wrds-3.1.1\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "TlUrRmTnlFD_"
},
"source": [
"import wrds"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "Kfij7381Oe4W",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "7b3c6de8-2d4e-42de-9bde-d402aa3f6e44"
},
"source": [
"# Now I am connecting to WRDS site - you must ahve a WRDS account user id and password\n",
"conn=wrds.Connection()"
],
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Enter your WRDS username [root]:hy11\n",
"Enter your password:··········\n",
"WRDS recommends setting up a .pgpass file.\n",
"Create .pgpass file now [y/n]?: y\n",
"Created .pgpass file successfully.\n",
"Loading library list...\n",
"Done\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"collapsed": true,
"id": "zgpZF6Vo11y5"
},
"source": [
"import pandas as pd \n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"\n",
"plt.style.use('fivethirtyeight')\n",
"\n",
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'retina'"
],
"execution_count": 6,
"outputs": []
},
{
"cell_type": "code",
"source": [
"help(wrds)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "eneGwr9g3tDo",
"outputId": "b7ad4477-6b23-41e5-d618-d54844157eea"
},
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Help on package wrds:\n",
"\n",
"NAME\n",
" wrds\n",
"\n",
"DESCRIPTION\n",
" WRDS Python Data Access Library\n",
" ==============================\n",
" \n",
" WRDS-Py is a library for extracting data from WRDS data sources and getting it into Pandas.\n",
" \n",
" >>> import wrds\n",
" >>> db = wrds.Connection()\n",
" >>> db.list_libraries()\n",
" ['aha', 'aha_sample', 'ahasamp', 'audit', 'audit_audit_comp', ...]\n",
" >>> db.list_tables(library='crsp')\n",
" ['acti', 'asia', 'asib', 'asic', 'asio', 'asix', 'bmdebt', 'bmheader', ...]\n",
" >>> data = db.raw_sql('SELECT * FROM crsp.stocknames', index_col='permno')\n",
" >>> data.head()\n",
" permco namedt nameenddt cusip ncusip ticker permno\n",
" 10000.0 7952.0 1986-01-07 1987-06-11 68391610 68391610 OMFGA\n",
" 10001.0 7953.0 1986-01-09 1993-11-21 36720410 39040610 GFGC\n",
" 10001.0 7953.0 1993-11-22 2008-02-04 36720410 29274A10 EWST\n",
" 10001.0 7953.0 2008-02-05 2009-08-03 36720410 29274A20 EWST\n",
" 10001.0 7953.0 2009-08-04 2009-12-17 36720410 29269V10 EGAS\n",
" ...\n",
"\n",
"PACKAGE CONTENTS\n",
" sql\n",
" test\n",
"\n",
"DATA\n",
" __copyright__ = '2017-2021 Wharton Research Data Services'\n",
" __title__ = 'wrds-py'\n",
"\n",
"VERSION\n",
" 3.1.1\n",
"\n",
"AUTHOR\n",
" Wharton Research Data Services\n",
"\n",
"FILE\n",
" /usr/local/lib/python3.7/dist-packages/wrds/__init__.py\n",
"\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#listing all dtabases or libraries in WRDS\n",
"conn.list_libraries()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "pf-sgx9YwW3W",
"outputId": "d0ce2fef-f93a-4387-8f4e-926cd82689d9"
},
"execution_count": 8,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"['compbd',\n",
" 'compgd',\n",
" 'compnad',\n",
" 'compsegd',\n",
" 'crspa',\n",
" 'evts',\n",
" 'issm',\n",
" 'nastraq',\n",
" 'tass',\n",
" 'wrds_lib_internal',\n",
" 'aha',\n",
" 'estimize',\n",
" 'levin',\n",
" 'ciqsamp_capstrct',\n",
" 'toyo',\n",
" 'ahasamp',\n",
" 'ciqsamp_pplintel',\n",
" 'crspm',\n",
" 'tresgsmp',\n",
" 'trsdcgs',\n",
" 'columnar',\n",
" 'trws',\n",
" 'lspd',\n",
" 'twoiq',\n",
" 'wcai',\n",
" 'tresg',\n",
" 'wind',\n",
" 'wqa',\n",
" 'msrb_all',\n",
" 'custom_jl',\n",
" 'risk',\n",
" 'centris',\n",
" 'wrdsapps_link_supplychain',\n",
" 'block_all',\n",
" 'zacks',\n",
" 'crsp',\n",
" 'contrib',\n",
" 'audit',\n",
" 'boardex_trial',\n",
" 'emdb',\n",
" 'calcbnch',\n",
" 'comp_na_monthly_all',\n",
" 'auditsmp',\n",
" 'boardsmp',\n",
" 'comp_segments_hist',\n",
" 'wrdsrpts_rep_usage',\n",
" 'public_all',\n",
" 'pwt_all',\n",
" 'msfanly',\n",
" 'etfg',\n",
" 'snlsamp_fig',\n",
" 'wrdsapps_backtest_plus',\n",
" 'pacap',\n",
" 'ciqsamp_transcripts',\n",
" 'ciq',\n",
" 'tr_ds',\n",
" 'ppublica',\n",
" 'crsp_a_stock',\n",
" 'preqin',\n",
" 'etfg_samp',\n",
" 'fisdsamp',\n",
" 'windsmp',\n",
" 'rent',\n",
" 'sustainalyticssamp_all',\n",
" 'wrdsapps_evtstudy_int_ginsight',\n",
" 'compmcur',\n",
" 'tr_dealscan',\n",
" 'markit',\n",
" 'secsamp_all',\n",
" 'rpna',\n",
" 'ibes',\n",
" 'rpa',\n",
" 'sdcsamp',\n",
" 'wrdssec_midas',\n",
" 'cisdmsmp',\n",
" 'cboe_all',\n",
" 'snl',\n",
" 'cboe',\n",
" 'sprat',\n",
" 'ciqsamp',\n",
" 'fjc_litigation',\n",
" 'trucost',\n",
" 'sustain',\n",
" 'trdssamp',\n",
" 'risksamp',\n",
" 'midas',\n",
" 'snlsamp',\n",
" 'public',\n",
" 'pwt',\n",
" 'repsamp',\n",
" 'snapsamp',\n",
" 'taqsamp',\n",
" 'totalq',\n",
" 'optionm',\n",
" 'comp_execucomp',\n",
" 'fjc_linking',\n",
" 'compa',\n",
" 'bank',\n",
" 'blab',\n",
" 'compb',\n",
" 'compg',\n",
" 'block',\n",
" 'taqmsec',\n",
" 'trsamp_ds_eq',\n",
" 'contrib_ceo_turnover',\n",
" 'cisdm',\n",
" 'clrvt',\n",
" 'clrvtsmp',\n",
" 'compm',\n",
" 'compseg',\n",
" 'compsamp',\n",
" 'comph',\n",
" 'compsnap',\n",
" 'comscore',\n",
" 'pitchbk',\n",
" 'crspsamp',\n",
" 'dmef',\n",
" 'eursamp',\n",
" 'contrib_kpss',\n",
" 'auditsmp_all',\n",
" 'crspq',\n",
" 'execcomp',\n",
" 'taqmsamp_all',\n",
" 'ff',\n",
" 'ftse',\n",
" 'cusipm',\n",
" 'boardex',\n",
" 'eureka',\n",
" 'eventus',\n",
" 'ftsesamp',\n",
" 'ginsight',\n",
" 'ktsamp',\n",
" 'factset',\n",
" 'ifgrsamp',\n",
" 'imssamp',\n",
" 'gmi',\n",
" 'fssamp',\n",
" 'govpxsmp',\n",
" 'hbsamp',\n",
" 'hbase',\n",
" 'hfr',\n",
" 'ibescorp',\n",
" 'mrktsamp_msf',\n",
" 'iri',\n",
" 'govpx',\n",
" 'kld',\n",
" 'ifgr',\n",
" 'ibeskpi',\n",
" 'fisd',\n",
" 'lspdsamp',\n",
" 'ims',\n",
" 'ktmine',\n",
" 'taq',\n",
" 'aha_sample',\n",
" 'compdcur',\n",
" 'calcbench_trial',\n",
" 'ciqsamp_common',\n",
" 'ppubsamp_d4d',\n",
" 'mrktsamp',\n",
" 'otc',\n",
" 'msrbsamp',\n",
" 'contrib_general',\n",
" 'preqsamp_all',\n",
" 'twoiq_samp',\n",
" 'msrb',\n",
" 'mrktsamp_cdx',\n",
" 'phlx_all',\n",
" 'zacksamp_all',\n",
" 'mfl',\n",
" 'sustsamp',\n",
" 'etfgsamp',\n",
" 'phlx',\n",
" 'ppubsamp',\n",
" 'preqsamp',\n",
" 'ciqsamp_keydev',\n",
" 'tfn',\n",
" 'toyosamp',\n",
" 'wappsamp',\n",
" 'wrdsapps_evtstudy_lr',\n",
" 'crsp_a_ccm',\n",
" 'zacksamp',\n",
" 'revere',\n",
" 'eurekahedge_sample',\n",
" 'comp_na_daily_all',\n",
" 'ims_obp_trial',\n",
" 'wrdsrpts',\n",
" 'compsamp_snapshot',\n",
" 'comp_na_annual_all',\n",
" 'rq_all',\n",
" 'infogroupsamp_business',\n",
" 'infogroupsamp_residential',\n",
" 'ktmine_patents_samp',\n",
" 'djones_all',\n",
" 'doe_all',\n",
" 'factsamp_all',\n",
" 'toyosamp_all',\n",
" 'wrdsapps_eushort',\n",
" 'wrdsapps_subsidiary',\n",
" 'wrdsappssamp_all',\n",
" 'wrdsapps_link_datastream_wscope',\n",
" 'wrdsapps_patents',\n",
" 'dmef_all',\n",
" 'macrofin_comm_trade',\n",
" 'mrktsamp_cds',\n",
" 'pitchsmp',\n",
" 'wrdsapps_link_comp_eushort',\n",
" 'totalq_all',\n",
" 'trsamp_dscom',\n",
" 'trsamp_dsecon',\n",
" 'wrdsapps_finratio',\n",
" 'reprisk',\n",
" 'comp',\n",
" 'trcstsmp',\n",
" 'rpnasamp',\n",
" 'audit_corp_legal',\n",
" 'csmar',\n",
" 'trsamp_dsfut',\n",
" 'wrdsapps_backtest_basic',\n",
" 'wrdsapps_link_crsp_bond',\n",
" 'ff_all',\n",
" 'wrdsapps_link_crsp_taq',\n",
" 'contrib_intangible_value',\n",
" 'wrdssec',\n",
" 'wrdsapps',\n",
" 'audit_common',\n",
" 'contrib_char_returns',\n",
" 'crsp_q_indexhist',\n",
" 'bvd',\n",
" 'secsamp',\n",
" 'factsamp_revere',\n",
" 'frb_all',\n",
" 'hbase_sample',\n",
" 'hfrsamp_hfrdb',\n",
" 'trown',\n",
" 'lvnsamp_all',\n",
" 'risksamp_all',\n",
" 'optionmsamp_europe',\n",
" 'optionmsamp_us',\n",
" 'reprisk_sample',\n",
" 'wrdsapps_finratio_ccm',\n",
" 'trace_standard',\n",
" 'trdstrm',\n",
" 'trace_enhanced',\n",
" 'fjc',\n",
" 'lvnsamp',\n",
" 'omtrial',\n",
" 'trace',\n",
" 'bvdsamp',\n",
" 'djones',\n",
" 'doe',\n",
" 'frb',\n",
" 'hfrsamp',\n",
" 'macrofin',\n",
" 'comp_bank',\n",
" 'trsamp',\n",
" 'wrdsapps_link_crsp_factset',\n",
" 'twoiqsmp',\n",
" 'comp_bank_daily',\n",
" 'audit_audit_comp',\n",
" 'comp_segments_hist_daily',\n",
" 'otc_endofday',\n",
" 'dealscan',\n",
" 'ravenpack_trial',\n",
" 'msfinst',\n",
" 'crsp_a_indexes',\n",
" 'taqmsamp',\n",
" 'iss',\n",
" 'sdc']"
]
},
"metadata": {},
"execution_count": 8
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "WhENZBZjpNBn",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "f3b40883-e476-4d71-efdb-c004f643be19"
},
"source": [
"#listing CRSP files\n",
"conn.list_tables(library=\"crspa\")"
],
"execution_count": 9,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"['acti',\n",
" 'asia',\n",
" 'asib',\n",
" 'asic',\n",
" 'asio',\n",
" 'asix',\n",
" 'bmdebt',\n",
" 'bmheader',\n",
" 'bmpaymts',\n",
" 'bmquotes',\n",
" 'bmyield',\n",
" 'bndprt06',\n",
" 'bndprt12',\n",
" 'bxcalind',\n",
" 'bxdlyind',\n",
" 'bxmthind',\n",
" 'bxquotes',\n",
" 'bxyield',\n",
" 'ccm_lookup',\n",
" 'ccm_qvards',\n",
" 'ccmxpf_linktable',\n",
" 'ccmxpf_lnkhist',\n",
" 'ccmxpf_lnkrng',\n",
" 'ccmxpf_lnkused',\n",
" 'comphead',\n",
" 'comphist',\n",
" 'compmaster',\n",
" 'crsp_daily_data',\n",
" 'crsp_header',\n",
" 'crsp_monthly_data',\n",
" 'crsp_names',\n",
" 'crsp_ziman_daily_index',\n",
" 'crsp_ziman_monthly_index',\n",
" 'cs20yr',\n",
" 'cs5yr',\n",
" 'cs90d',\n",
" 'cst_hist',\n",
" 'dport1',\n",
" 'dport2',\n",
" 'dport3',\n",
" 'dport4',\n",
" 'dport5',\n",
" 'dport6',\n",
" 'dport7',\n",
" 'dport8',\n",
" 'dport9',\n",
" 'dsbc',\n",
" 'dsbo',\n",
" 'dse',\n",
" 'dse62',\n",
" 'dse62delist',\n",
" 'dse62dist',\n",
" 'dse62exchdates',\n",
" 'dse62names',\n",
" 'dse62nasdin',\n",
" 'dse62shares',\n",
" 'dseall',\n",
" 'dseall62',\n",
" 'dsedelist',\n",
" 'dsedist',\n",
" 'dseexchdates',\n",
" 'dsenames',\n",
" 'dsenasdin',\n",
" 'dseshares',\n",
" 'dsf',\n",
" 'dsf62',\n",
" 'dsfhdr',\n",
" 'dsfhdr62',\n",
" 'dsi',\n",
" 'dsi62',\n",
" 'dsia',\n",
" 'dsib',\n",
" 'dsic',\n",
" 'dsio',\n",
" 'dsir',\n",
" 'dsix',\n",
" 'dsiy',\n",
" 'dsp500',\n",
" 'dsp500list',\n",
" 'dsp500p',\n",
" 'dssc',\n",
" 'dsso',\n",
" 'erdport1',\n",
" 'erdport2',\n",
" 'erdport3',\n",
" 'erdport4',\n",
" 'erdport5',\n",
" 'erdport6',\n",
" 'erdport7',\n",
" 'erdport8',\n",
" 'erdport9',\n",
" 'ermport1',\n",
" 'ermport2',\n",
" 'ermport3',\n",
" 'ermport4',\n",
" 'ermport5',\n",
" 'fbpri',\n",
" 'fbyld',\n",
" 'fwdask06',\n",
" 'fwdask12',\n",
" 'fwdave06',\n",
" 'fwdave12',\n",
" 'fwdbid06',\n",
" 'fwdbid12',\n",
" 'hldask06',\n",
" 'hldask12',\n",
" 'hldave06',\n",
" 'hldave12',\n",
" 'hldbid06',\n",
" 'hldbid12',\n",
" 'index_type_map',\n",
" 'mbi',\n",
" 'mbmdat',\n",
" 'mbmhdr',\n",
" 'mbx',\n",
" 'mbxid',\n",
" 'mcti',\n",
" 'mhista',\n",
" 'mhistn',\n",
" 'mhistq',\n",
" 'mport1',\n",
" 'mport2',\n",
" 'mport3',\n",
" 'mport4',\n",
" 'mport5',\n",
" 'mse',\n",
" 'mse62',\n",
" 'mse62delist',\n",
" 'mse62dist',\n",
" 'mse62exchdates',\n",
" 'mse62names',\n",
" 'mse62nasdin',\n",
" 'mse62shares',\n",
" 'mseall',\n",
" 'mseall62',\n",
" 'msedelist',\n",
" 'msedist',\n",
" 'mseexchdates',\n",
" 'msenames',\n",
" 'msenasdin',\n",
" 'mseshares',\n",
" 'msf',\n",
" 'msf62',\n",
" 'msfhdr',\n",
" 'msfhdr62',\n",
" 'msi',\n",
" 'msi62',\n",
" 'msia',\n",
" 'msib',\n",
" 'msic',\n",
" 'msio',\n",
" 'msir',\n",
" 'msix',\n",
" 'msiy',\n",
" 'msp500',\n",
" 'msp500list',\n",
" 'msp500p',\n",
" 'priask06',\n",
" 'priask12',\n",
" 'priave06',\n",
" 'priave12',\n",
" 'pribid06',\n",
" 'pribid12',\n",
" 'price_type',\n",
" 'property_type',\n",
" 'qcti',\n",
" 'qsia',\n",
" 'qsib',\n",
" 'qsic',\n",
" 'qsio',\n",
" 'qsix',\n",
" 'rebala',\n",
" 'rebaln',\n",
" 'rebalq',\n",
" 'reit_type',\n",
" 'riskfree',\n",
" 's6z_del',\n",
" 's6z_dind',\n",
" 's6z_dis',\n",
" 's6z_dp_dly',\n",
" 's6z_ds_dly',\n",
" 's6z_hdr',\n",
" 's6z_indhdr',\n",
" 's6z_mdel',\n",
" 's6z_mind',\n",
" 's6z_mth',\n",
" 's6z_nam',\n",
" 's6z_ndi',\n",
" 's6z_shr',\n",
" 'saz_del',\n",
" 'saz_dind',\n",
" 'saz_dis',\n",
" 'saz_dp_dly',\n",
" 'saz_ds_dly',\n",
" 'saz_hdr',\n",
" 'saz_indhdr',\n",
" 'saz_mdel',\n",
" 'saz_mind',\n",
" 'saz_mth',\n",
" 'saz_nam',\n",
" 'saz_ndi',\n",
" 'saz_shr',\n",
" 'sechead',\n",
" 'sechist',\n",
" 'sfz_dind',\n",
" 'sfz_indhdr',\n",
" 'sfz_mbr',\n",
" 'sfz_mind',\n",
" 'sfz_portd',\n",
" 'sfz_portm',\n",
" 'sfz_rb',\n",
" 'stock_qvards',\n",
" 'stocknames',\n",
" 'stocknames62',\n",
" 'sub_property_type',\n",
" 'tfz_dly',\n",
" 'tfz_dly_cd',\n",
" 'tfz_dly_cpi',\n",
" 'tfz_dly_ft',\n",
" 'tfz_dly_rf2',\n",
" 'tfz_dly_ts2',\n",
" 'tfz_idx',\n",
" 'tfz_iss',\n",
" 'tfz_mast',\n",
" 'tfz_mth',\n",
" 'tfz_mth_bp',\n",
" 'tfz_mth_cd',\n",
" 'tfz_mth_cpi',\n",
" 'tfz_mth_fb',\n",
" 'tfz_mth_ft',\n",
" 'tfz_mth_rf',\n",
" 'tfz_mth_rf2',\n",
" 'tfz_mth_ts',\n",
" 'tfz_mth_ts2',\n",
" 'tfz_pay',\n",
" 'yldask06',\n",
" 'yldask12',\n",
" 'yldave06',\n",
" 'yldave12',\n",
" 'yldbid06',\n",
" 'yldbid12',\n",
" 'ziman_reit_info',\n",
" 'zr_hdrnames']"
]
},
"metadata": {},
"execution_count": 9
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "RWYR4QakOoq4",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 694
},
"outputId": "58b5d6de-d4e1-45d7-bfb1-d5de4357e8d7"
},
"source": [
"#listing CRSP dsf file or table\n",
"conn.describe_table('crsp', 'dsf')"
],
"execution_count": 10,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 101070400 rows in crsp.dsf.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 cusip True VARCHAR(8)\n",
"1 permno True DOUBLE_PRECISION\n",
"2 permco True DOUBLE_PRECISION\n",
"3 issuno True DOUBLE_PRECISION\n",
"4 hexcd True DOUBLE_PRECISION\n",
"5 hsiccd True DOUBLE_PRECISION\n",
"6 date True DATE\n",
"7 bidlo True DOUBLE_PRECISION\n",
"8 askhi True DOUBLE_PRECISION\n",
"9 prc True DOUBLE_PRECISION\n",
"10 vol True DOUBLE_PRECISION\n",
"11 ret True DOUBLE_PRECISION\n",
"12 bid True DOUBLE_PRECISION\n",
"13 ask True DOUBLE_PRECISION\n",
"14 shrout True DOUBLE_PRECISION\n",
"15 cfacpr True DOUBLE_PRECISION\n",
"16 cfacshr True DOUBLE_PRECISION\n",
"17 openprc True DOUBLE_PRECISION\n",
"18 numtrd True DOUBLE_PRECISION\n",
"19 retx True DOUBLE_PRECISION"
],
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" \n",
" 6 | \n",
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" DATE | \n",
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" 7 | \n",
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" 8 | \n",
" askhi | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
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" 9 | \n",
" prc | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 10 | \n",
" vol | \n",
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" 14 | \n",
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" True | \n",
" DOUBLE_PRECISION | \n",
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" 16 | \n",
" cfacshr | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 17 | \n",
" openprc | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
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" \n",
" 18 | \n",
" numtrd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
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" \n",
" 19 | \n",
" retx | \n",
" True | \n",
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},
{
"cell_type": "code",
"metadata": {
"id": "vmsorRJ65eBH",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "660dc3b6-43ed-4e7d-e302-dd013cc5b71f"
},
"source": [
"#listing CRSP dsf file or table\n",
"conn.describe_table('crspm', 'dsfhdr')"
],
"execution_count": 11,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 36564 rows in crspm.dsfhdr.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 permno True DOUBLE_PRECISION\n",
"1 permco True DOUBLE_PRECISION\n",
"2 hshrcd True DOUBLE_PRECISION\n",
"3 dlstcd True DOUBLE_PRECISION\n",
"4 hcusip True VARCHAR(8)\n",
"5 htick True VARCHAR(8)\n",
"6 hcomnam True VARCHAR(35)\n",
"7 htsymbol True VARCHAR(10)\n",
"8 hnaics True VARCHAR(7)\n",
"9 hprimexc True VARCHAR(1)\n",
"10 htrdstat True VARCHAR(1)\n",
"11 hsecstat True VARCHAR(1)\n",
"12 cusip True VARCHAR(8)\n",
"13 compno True DOUBLE_PRECISION\n",
"14 issuno True DOUBLE_PRECISION\n",
"15 hexcd True DOUBLE_PRECISION\n",
"16 hsiccd True DOUBLE_PRECISION\n",
"17 numnam True DOUBLE_PRECISION\n",
"18 numdis True DOUBLE_PRECISION\n",
"19 numshr True DOUBLE_PRECISION\n",
"20 numdel True DOUBLE_PRECISION\n",
"21 numndi True DOUBLE_PRECISION\n",
"22 begdat True DATE\n",
"23 enddat True DATE\n",
"24 begprc True DATE\n",
"25 endprc True DATE\n",
"26 begret True DATE\n",
"27 endret True DATE\n",
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"29 endrtx True DATE\n",
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"31 endbidlo True DATE\n",
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"33 endaskhi True DATE\n",
"34 begvol True DATE\n",
"35 endvol True DATE\n",
"36 begbid True DATE\n",
"37 endbid True DATE\n",
"38 begask True DATE\n",
"39 endask True DATE\n",
"40 begopr True DATE\n",
"41 endopr True DATE\n",
"42 hsicmg True DOUBLE_PRECISION\n",
"43 hsicig True DOUBLE_PRECISION"
],
"text/html": [
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" 4 | \n",
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" True | \n",
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" \n",
" 5 | \n",
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" True | \n",
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" 6 | \n",
" hcomnam | \n",
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" VARCHAR(35) | \n",
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" 7 | \n",
" htsymbol | \n",
" True | \n",
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" 8 | \n",
" hnaics | \n",
" True | \n",
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" 9 | \n",
" hprimexc | \n",
" True | \n",
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" 10 | \n",
" htrdstat | \n",
" True | \n",
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" 11 | \n",
" hsecstat | \n",
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" \n",
" 21 | \n",
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" 27 | \n",
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" True | \n",
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" 29 | \n",
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" True | \n",
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" 30 | \n",
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" DATE | \n",
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" 31 | \n",
" endbidlo | \n",
" True | \n",
" DATE | \n",
"
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" 32 | \n",
" begaskhi | \n",
" True | \n",
" DATE | \n",
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" 33 | \n",
" endaskhi | \n",
" True | \n",
" DATE | \n",
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" 34 | \n",
" begvol | \n",
" True | \n",
" DATE | \n",
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" 35 | \n",
" endvol | \n",
" True | \n",
" DATE | \n",
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" 36 | \n",
" begbid | \n",
" True | \n",
" DATE | \n",
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" 37 | \n",
" endbid | \n",
" True | \n",
" DATE | \n",
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" True | \n",
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" True | \n",
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" True | \n",
" DATE | \n",
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" 41 | \n",
" endopr | \n",
" True | \n",
" DATE | \n",
"
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" \n",
" 42 | \n",
" hsicmg | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
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" \n",
" 43 | \n",
" hsicig | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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},
"metadata": {},
"execution_count": 11
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "VyJJa5UM5Xat",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "497b9138-8c23-4959-d313-e39f2fb16301"
},
"source": [
"#listing CRSP dsf file or table\n",
"conn.describe_table('crsp', 'dsfhdr')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 36437 rows in crsp.dsfhdr.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 permno True DOUBLE_PRECISION\n",
"1 permco True DOUBLE_PRECISION\n",
"2 hshrcd True DOUBLE_PRECISION\n",
"3 dlstcd True DOUBLE_PRECISION\n",
"4 hcusip True VARCHAR(8)\n",
"5 htick True VARCHAR(8)\n",
"6 hcomnam True VARCHAR(35)\n",
"7 htsymbol True VARCHAR(10)\n",
"8 hnaics True VARCHAR(7)\n",
"9 hprimexc True VARCHAR(1)\n",
"10 htrdstat True VARCHAR(1)\n",
"11 hsecstat True VARCHAR(1)\n",
"12 cusip True VARCHAR(8)\n",
"13 compno True DOUBLE_PRECISION\n",
"14 issuno True DOUBLE_PRECISION\n",
"15 hexcd True DOUBLE_PRECISION\n",
"16 hsiccd True DOUBLE_PRECISION\n",
"17 numnam True DOUBLE_PRECISION\n",
"18 numdis True DOUBLE_PRECISION\n",
"19 numshr True DOUBLE_PRECISION\n",
"20 numdel True DOUBLE_PRECISION\n",
"21 numndi True DOUBLE_PRECISION\n",
"22 begdat True DATE\n",
"23 enddat True DATE\n",
"24 begprc True DATE\n",
"25 endprc True DATE\n",
"26 begret True DATE\n",
"27 endret True DATE\n",
"28 begrtx True DATE\n",
"29 endrtx True DATE\n",
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"31 endbidlo True DATE\n",
"32 begaskhi True DATE\n",
"33 endaskhi True DATE\n",
"34 begvol True DATE\n",
"35 endvol True DATE\n",
"36 begbid True DATE\n",
"37 endbid True DATE\n",
"38 begask True DATE\n",
"39 endask True DATE\n",
"40 begopr True DATE\n",
"41 endopr True DATE\n",
"42 hsicmg True DOUBLE_PRECISION\n",
"43 hsicig True DOUBLE_PRECISION"
],
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" \n",
" 7 | \n",
" htsymbol | \n",
" True | \n",
" VARCHAR(10) | \n",
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" \n",
" 8 | \n",
" hnaics | \n",
" True | \n",
" VARCHAR(7) | \n",
"
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" \n",
" 9 | \n",
" hprimexc | \n",
" True | \n",
" VARCHAR(1) | \n",
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" True | \n",
" DOUBLE_PRECISION | \n",
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" True | \n",
" DOUBLE_PRECISION | \n",
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" 19 | \n",
" numshr | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
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" 20 | \n",
" numdel | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
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" 21 | \n",
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" True | \n",
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" \n",
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" \n",
" 23 | \n",
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" True | \n",
" DATE | \n",
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" \n",
" 24 | \n",
" begprc | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 25 | \n",
" endprc | \n",
" True | \n",
" DATE | \n",
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\n",
" \n",
" 26 | \n",
" begret | \n",
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" DATE | \n",
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" \n",
" 27 | \n",
" endret | \n",
" True | \n",
" DATE | \n",
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\n",
" \n",
" 28 | \n",
" begrtx | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 29 | \n",
" endrtx | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 30 | \n",
" begbidlo | \n",
" True | \n",
" DATE | \n",
"
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" \n",
" 31 | \n",
" endbidlo | \n",
" True | \n",
" DATE | \n",
"
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" 32 | \n",
" begaskhi | \n",
" True | \n",
" DATE | \n",
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" 33 | \n",
" endaskhi | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 34 | \n",
" begvol | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 35 | \n",
" endvol | \n",
" True | \n",
" DATE | \n",
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" 36 | \n",
" begbid | \n",
" True | \n",
" DATE | \n",
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" hsicmg | \n",
" True | \n",
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" True | \n",
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},
"metadata": {},
"execution_count": 10
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]
},
{
"cell_type": "code",
"metadata": {
"id": "qZApj0eRUwyw",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "dbac12b7-b9d2-4dea-b35a-80e1ba9f582e"
},
"source": [
"conn.describe_table('crsp', 'dse')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 12127940 rows in crsp.dse.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 event True VARCHAR(8)\n",
"1 date True DATE\n",
"2 hsicmg True DOUBLE_PRECISION\n",
"3 hsicig True DOUBLE_PRECISION\n",
"4 comnam True VARCHAR(32)\n",
"5 cusip True VARCHAR(8)\n",
"6 dclrdt True DATE\n",
"7 dlamt True DOUBLE_PRECISION\n",
"8 dlpdt True DATE\n",
"9 dlstcd True DOUBLE_PRECISION\n",
"10 hsiccd True DOUBLE_PRECISION\n",
"11 issuno True DOUBLE_PRECISION\n",
"12 ncusip True VARCHAR(8)\n",
"13 nextdt True DATE\n",
"14 paydt True DATE\n",
"15 rcrddt True DATE\n",
"16 shrcls True VARCHAR(1)\n",
"17 shrflg True DOUBLE_PRECISION\n",
"18 ticker True VARCHAR(5)\n",
"19 permno True DOUBLE_PRECISION\n",
"20 nameendt True DATE\n",
"21 shrcd True DOUBLE_PRECISION\n",
"22 exchcd True DOUBLE_PRECISION\n",
"23 siccd True DOUBLE_PRECISION\n",
"24 tsymbol True VARCHAR(10)\n",
"25 naics True VARCHAR(7)\n",
"26 primexch True VARCHAR(1)\n",
"27 trdstat True VARCHAR(1)\n",
"28 secstat True VARCHAR(1)\n",
"29 permco True DOUBLE_PRECISION\n",
"30 compno True DOUBLE_PRECISION\n",
"31 hexcd True DOUBLE_PRECISION\n",
"32 distcd True DOUBLE_PRECISION\n",
"33 divamt True DOUBLE_PRECISION\n",
"34 facpr True DOUBLE_PRECISION\n",
"35 facshr True DOUBLE_PRECISION\n",
"36 acperm True DOUBLE_PRECISION\n",
"37 accomp True DOUBLE_PRECISION\n",
"38 nwperm True DOUBLE_PRECISION\n",
"39 nwcomp True DOUBLE_PRECISION\n",
"40 dlretx True DOUBLE_PRECISION\n",
"41 dlprc True DOUBLE_PRECISION\n",
"42 dlret True DOUBLE_PRECISION\n",
"43 shrout True DOUBLE_PRECISION\n",
"44 shrenddt True DATE\n",
"45 trtscd True DOUBLE_PRECISION\n",
"46 trtsendt True DATE\n",
"47 nmsind True DOUBLE_PRECISION\n",
"48 mmcnt True DOUBLE_PRECISION\n",
"49 nsdinx True DOUBLE_PRECISION"
],
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" True | \n",
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" comnam | \n",
" True | \n",
" VARCHAR(32) | \n",
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" cusip | \n",
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" True | \n",
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" ticker | \n",
" True | \n",
" VARCHAR(5) | \n",
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" 19 | \n",
" permno | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 20 | \n",
" nameendt | \n",
" True | \n",
" DATE | \n",
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" 21 | \n",
" shrcd | \n",
" True | \n",
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" 22 | \n",
" exchcd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 23 | \n",
" siccd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 24 | \n",
" tsymbol | \n",
" True | \n",
" VARCHAR(10) | \n",
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" 25 | \n",
" naics | \n",
" True | \n",
" VARCHAR(7) | \n",
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" 26 | \n",
" primexch | \n",
" True | \n",
" VARCHAR(1) | \n",
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" 27 | \n",
" trdstat | \n",
" True | \n",
" VARCHAR(1) | \n",
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" 28 | \n",
" secstat | \n",
" True | \n",
" VARCHAR(1) | \n",
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" 29 | \n",
" permco | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 30 | \n",
" compno | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 31 | \n",
" hexcd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 32 | \n",
" distcd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 33 | \n",
" divamt | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 34 | \n",
" facpr | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" facshr | \n",
" True | \n",
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" acperm | \n",
" True | \n",
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" 37 | \n",
" accomp | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 38 | \n",
" nwperm | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 39 | \n",
" nwcomp | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 40 | \n",
" dlretx | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 41 | \n",
" dlprc | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 42 | \n",
" dlret | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 43 | \n",
" shrout | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 44 | \n",
" shrenddt | \n",
" True | \n",
" DATE | \n",
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" 45 | \n",
" trtscd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 46 | \n",
" trtsendt | \n",
" True | \n",
" DATE | \n",
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" nmsind | \n",
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" mmcnt | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" True | \n",
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"metadata": {},
"execution_count": 11
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]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 694
},
"id": "M2JMeX3o97oy",
"outputId": "a41ae955-e017-42cf-a03f-5f0ed4e12c4e"
},
"source": [
"conn.describe_table('crspm', 'dsf')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 101263896 rows in crspm.dsf.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 cusip True VARCHAR(8)\n",
"1 permno True DOUBLE_PRECISION\n",
"2 permco True DOUBLE_PRECISION\n",
"3 issuno True DOUBLE_PRECISION\n",
"4 hexcd True DOUBLE_PRECISION\n",
"5 hsiccd True DOUBLE_PRECISION\n",
"6 date True DATE\n",
"7 bidlo True DOUBLE_PRECISION\n",
"8 askhi True DOUBLE_PRECISION\n",
"9 prc True DOUBLE_PRECISION\n",
"10 vol True DOUBLE_PRECISION\n",
"11 ret True DOUBLE_PRECISION\n",
"12 bid True DOUBLE_PRECISION\n",
"13 ask True DOUBLE_PRECISION\n",
"14 shrout True DOUBLE_PRECISION\n",
"15 cfacpr True DOUBLE_PRECISION\n",
"16 cfacshr True DOUBLE_PRECISION\n",
"17 openprc True DOUBLE_PRECISION\n",
"18 numtrd True DOUBLE_PRECISION\n",
"19 retx True DOUBLE_PRECISION"
],
"text/html": [
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" True | \n",
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" True | \n",
" DOUBLE_PRECISION | \n",
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" 17 | \n",
" openprc | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" 18 | \n",
" numtrd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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" retx | \n",
" True | \n",
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},
"metadata": {},
"execution_count": 12
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "JwpZE4iLVAA8",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 568
},
"outputId": "edb401a4-2185-4c55-ee8d-f777c8ec5073"
},
"source": [
"conn.describe_table('crsp', 'stocknames')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 77779 rows in crsp.stocknames.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 permno True DOUBLE_PRECISION\n",
"1 namedt True DATE\n",
"2 nameenddt True DATE\n",
"3 shrcd True DOUBLE_PRECISION\n",
"4 exchcd True DOUBLE_PRECISION\n",
"5 siccd True DOUBLE_PRECISION\n",
"6 ncusip True VARCHAR(8)\n",
"7 ticker True VARCHAR(8)\n",
"8 comnam True VARCHAR(35)\n",
"9 shrcls True VARCHAR(4)\n",
"10 permco True DOUBLE_PRECISION\n",
"11 hexcd True DOUBLE_PRECISION\n",
"12 cusip True VARCHAR(8)\n",
"13 st_date True DATE\n",
"14 end_date True DATE\n",
"15 namedum True DOUBLE_PRECISION"
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" True | \n",
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" True | \n",
" VARCHAR(8) | \n",
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" 13 | \n",
" st_date | \n",
" True | \n",
" DATE | \n",
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" 14 | \n",
" end_date | \n",
" True | \n",
" DATE | \n",
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" 15 | \n",
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},
"metadata": {},
"execution_count": 13
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "mP6vHtzrVADn",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 725
},
"outputId": "61b4b176-a623-43c4-9d0b-787f5b037966"
},
"source": [
"conn.describe_table('crsp', 'dsenames')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 110198 rows in crsp.dsenames.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 permno True DOUBLE_PRECISION\n",
"1 namedt True DATE\n",
"2 nameendt True DATE\n",
"3 shrcd True DOUBLE_PRECISION\n",
"4 exchcd True DOUBLE_PRECISION\n",
"5 siccd True DOUBLE_PRECISION\n",
"6 ncusip True VARCHAR(8)\n",
"7 ticker True VARCHAR(8)\n",
"8 comnam True VARCHAR(35)\n",
"9 shrcls True VARCHAR(4)\n",
"10 tsymbol True VARCHAR(10)\n",
"11 naics True VARCHAR(7)\n",
"12 primexch True VARCHAR(1)\n",
"13 trdstat True VARCHAR(1)\n",
"14 secstat True VARCHAR(1)\n",
"15 permco True DOUBLE_PRECISION\n",
"16 compno True DOUBLE_PRECISION\n",
"17 issuno True DOUBLE_PRECISION\n",
"18 hexcd True DOUBLE_PRECISION\n",
"19 hsiccd True DOUBLE_PRECISION\n",
"20 cusip True VARCHAR(8)"
],
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" | \n",
" name | \n",
" nullable | \n",
" type | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" permno | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 1 | \n",
" namedt | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 2 | \n",
" nameendt | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 3 | \n",
" shrcd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 4 | \n",
" exchcd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 5 | \n",
" siccd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 6 | \n",
" ncusip | \n",
" True | \n",
" VARCHAR(8) | \n",
"
\n",
" \n",
" 7 | \n",
" ticker | \n",
" True | \n",
" VARCHAR(8) | \n",
"
\n",
" \n",
" 8 | \n",
" comnam | \n",
" True | \n",
" VARCHAR(35) | \n",
"
\n",
" \n",
" 9 | \n",
" shrcls | \n",
" True | \n",
" VARCHAR(4) | \n",
"
\n",
" \n",
" 10 | \n",
" tsymbol | \n",
" True | \n",
" VARCHAR(10) | \n",
"
\n",
" \n",
" 11 | \n",
" naics | \n",
" True | \n",
" VARCHAR(7) | \n",
"
\n",
" \n",
" 12 | \n",
" primexch | \n",
" True | \n",
" VARCHAR(1) | \n",
"
\n",
" \n",
" 13 | \n",
" trdstat | \n",
" True | \n",
" VARCHAR(1) | \n",
"
\n",
" \n",
" 14 | \n",
" secstat | \n",
" True | \n",
" VARCHAR(1) | \n",
"
\n",
" \n",
" 15 | \n",
" permco | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 16 | \n",
" compno | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 17 | \n",
" issuno | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 18 | \n",
" hexcd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 19 | \n",
" hsiccd | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 20 | \n",
" cusip | \n",
" True | \n",
" VARCHAR(8) | \n",
"
\n",
" \n",
"
\n",
"
\n",
"
\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"
\n",
" "
]
},
"metadata": {},
"execution_count": 14
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ipkafyNTO7Or",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 255
},
"outputId": "32a89560-72a9-4dc0-c593-431ff464d38a"
},
"source": [
"conn.describe_table('crsp', 'crsp_header')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 673 rows in crsp.crsp_header.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 permno True DOUBLE_PRECISION\n",
"1 permco True DOUBLE_PRECISION\n",
"2 begdt True DATE\n",
"3 enddt True DATE\n",
"4 comnam True VARCHAR(64)\n",
"5 hdlstcd True DOUBLE_PRECISION"
],
"text/html": [
"\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" name | \n",
" nullable | \n",
" type | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" permno | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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\n",
" \n",
" 1 | \n",
" permco | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
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\n",
" \n",
" 2 | \n",
" begdt | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 3 | \n",
" enddt | \n",
" True | \n",
" DATE | \n",
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" \n",
" 4 | \n",
" comnam | \n",
" True | \n",
" VARCHAR(64) | \n",
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" \n",
" 5 | \n",
" hdlstcd | \n",
" True | \n",
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},
"metadata": {},
"execution_count": 15
}
]
},
{
"cell_type": "markdown",
"source": [
"**CRSP** is a **library**, and the monthly stock file **CRSP.MSF** is a **table**. "
],
"metadata": {
"id": "re7gdd11OViT"
}
},
{
"cell_type": "code",
"source": [
"stock_names = conn.get_table(library = 'crsp', table ='stocknames', \n",
" columns=['permno', 'comnam','ticker', 'siccd','shrcd', 'namedt','nameenddt'])\n",
"stock_names.info()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "yV49xeClN8Qv",
"outputId": "574498a7-3f3f-47f9-ab8c-befc488432ed"
},
"execution_count": 13,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"RangeIndex: 77779 entries, 0 to 77778\n",
"Data columns (total 7 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 permno 77779 non-null float64\n",
" 1 comnam 77779 non-null object \n",
" 2 ticker 72881 non-null object \n",
" 3 siccd 77779 non-null float64\n",
" 4 shrcd 77779 non-null float64\n",
" 5 namedt 77779 non-null object \n",
" 6 nameenddt 77779 non-null object \n",
"dtypes: float64(3), object(4)\n",
"memory usage: 4.2+ MB\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"conn.list_tables(library=\"comp\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "kCDQueNfP2_B",
"outputId": "dd121a9f-b93b-45b0-e8b0-858f953fba6d"
},
"execution_count": 17,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"['aco_amda',\n",
" 'aco_imda',\n",
" 'aco_indfnta',\n",
" 'aco_indfntq',\n",
" 'aco_indfntytd',\n",
" 'aco_indsta',\n",
" 'aco_indstq',\n",
" 'aco_indstytd',\n",
" 'aco_notesa',\n",
" 'aco_notesq',\n",
" 'aco_notessa',\n",
" 'aco_notesytd',\n",
" 'aco_pnfnda',\n",
" 'aco_pnfndq',\n",
" 'aco_pnfndytd',\n",
" 'aco_pnfnta',\n",
" 'aco_pnfntq',\n",
" 'aco_pnfntytd',\n",
" 'aco_transa',\n",
" 'aco_transq',\n",
" 'aco_transsa',\n",
" 'aco_transytd',\n",
" 'adsprate',\n",
" 'asec_amda',\n",
" 'asec_imda',\n",
" 'asec_notesa',\n",
" 'asec_notesq',\n",
" 'asec_transa',\n",
" 'asec_transq',\n",
" 'bank_aacctchg',\n",
" 'bank_adesind',\n",
" 'bank_afnd1',\n",
" 'bank_afnd2',\n",
" 'bank_afnddc1',\n",
" 'bank_afnddc2',\n",
" 'bank_afntind',\n",
" 'bank_funda',\n",
" 'bank_funda_fncd',\n",
" 'bank_fundq',\n",
" 'bank_fundq_fncd',\n",
" 'bank_iacctchg',\n",
" 'bank_idesind',\n",
" 'bank_ifndq',\n",
" 'bank_ifndytd',\n",
" 'bank_ifntq',\n",
" 'bank_ifntytd',\n",
" 'bank_names',\n",
" 'bank_namesq',\n",
" 'chars',\n",
" 'co_aacctchg',\n",
" 'co_aaudit',\n",
" 'co_adesind',\n",
" 'co_adjfact',\n",
" 'co_afnd1',\n",
" 'co_afnd2',\n",
" 'co_afnddc1',\n",
" 'co_afnddc2',\n",
" 'co_afntind1',\n",
" 'co_afntind2',\n",
" 'co_ainvval',\n",
" 'co_amkt',\n",
" 'co_busdescl',\n",
" 'co_cotype',\n",
" 'co_filedate',\n",
" 'co_fortune',\n",
" 'co_hgic',\n",
" 'co_iacctchg',\n",
" 'co_iaudit',\n",
" 'co_idesind',\n",
" 'co_ifndq',\n",
" 'co_ifndsa',\n",
" 'co_ifndytd',\n",
" 'co_ifntq',\n",
" 'co_ifntsa',\n",
" 'co_ifntytd',\n",
" 'co_imkt',\n",
" 'co_industry',\n",
" 'co_ipcd',\n",
" 'co_mthly',\n",
" 'co_offtitl',\n",
" 'company',\n",
" 'currency',\n",
" 'dd_group',\n",
" 'dd_group_xref',\n",
" 'dd_item',\n",
" 'dd_package',\n",
" 'ecind_desc',\n",
" 'ecind_mth',\n",
" 'exrt_dly',\n",
" 'exrt_mth',\n",
" 'filings',\n",
" 'funda',\n",
" 'funda_fncd',\n",
" 'fundq',\n",
" 'fundq_fncd',\n",
" 'g_chars',\n",
" 'g_co_aaudit',\n",
" 'g_co_adesind',\n",
" 'g_co_afnd1',\n",
" 'g_co_afnd2',\n",
" 'g_co_afnddc1',\n",
" 'g_co_afnddc2',\n",
" 'g_co_afntind1',\n",
" 'g_co_afntind2',\n",
" 'g_co_ainvval',\n",
" 'g_co_gsuppl',\n",
" 'g_co_hgic',\n",
" 'g_co_iaudit',\n",
" 'g_co_idesind',\n",
" 'g_co_ifndq',\n",
" 'g_co_ifndsa',\n",
" 'g_co_ifndytd',\n",
" 'g_co_ifntq',\n",
" 'g_co_ifntsa',\n",
" 'g_co_ifntytd',\n",
" 'g_co_industry',\n",
" 'g_co_ipcd',\n",
" 'g_co_offtitl',\n",
" 'g_company',\n",
" 'g_currency',\n",
" 'g_ecind_desc',\n",
" 'g_ecind_mth',\n",
" 'g_exrt_dly',\n",
" 'g_exrt_mth',\n",
" 'g_funda',\n",
" 'g_funda_fncd',\n",
" 'g_fundq',\n",
" 'g_fundq_fncd',\n",
" 'g_idx_daily',\n",
" 'g_idx_index',\n",
" 'g_idx_mth',\n",
" 'g_idxcst_his',\n",
" 'g_names',\n",
" 'g_names_ix',\n",
" 'g_names_ix_cst',\n",
" 'g_namesq',\n",
" 'g_sec_adesind',\n",
" 'g_sec_adjfact',\n",
" 'g_sec_afnd',\n",
" 'g_sec_afnddc',\n",
" 'g_sec_afnt',\n",
" 'g_sec_divid',\n",
" 'g_sec_dprc',\n",
" 'g_sec_dtrt',\n",
" 'g_sec_history',\n",
" 'g_sec_idesind',\n",
" 'g_sec_ifnd',\n",
" 'g_sec_ifnt',\n",
" 'g_sec_split',\n",
" 'g_secd',\n",
" 'g_secnamesd',\n",
" 'g_security',\n",
" 'g_sedolgvkey',\n",
" 'g_tmptable_pkg6153_tbl4023',\n",
" 'idx_ann',\n",
" 'idx_anndes',\n",
" 'idx_daily',\n",
" 'idx_index',\n",
" 'idx_mth',\n",
" 'idx_qrt',\n",
" 'idx_qrtdes',\n",
" 'idxcst_his',\n",
" 'io_qaggregate',\n",
" 'io_qbuysell',\n",
" 'io_qchanges',\n",
" 'io_qfloatadj',\n",
" 'io_qholders',\n",
" 'it_mbuysell',\n",
" 'it_msummary',\n",
" 'it_r_rltn',\n",
" 'names',\n",
" 'names_aco_indsta',\n",
" 'names_aco_indstq',\n",
" 'names_aco_pnfnda',\n",
" 'names_aco_pnfndq',\n",
" 'names_adsprate',\n",
" 'names_ix',\n",
" 'names_ix_cst',\n",
" 'names_seg',\n",
" 'namesd',\n",
" 'namesm',\n",
" 'namesq',\n",
" 'r_accstd',\n",
" 'r_acqmeth',\n",
" 'r_auditors',\n",
" 'r_auopic',\n",
" 'r_balpres',\n",
" 'r_cf_formt',\n",
" 'r_co_status',\n",
" 'r_coindpre',\n",
" 'r_compstat',\n",
" 'r_consol',\n",
" 'r_country',\n",
" 'r_cstclscd',\n",
" 'r_datacode',\n",
" 'r_datafmt',\n",
" 'r_divtaxmarker',\n",
" 'r_docsrce',\n",
" 'r_ex_codes',\n",
" 'r_exchgtier',\n",
" 'r_exrt_typ',\n",
" 'r_fndfntcd',\n",
" 'r_footnts',\n",
" 'r_foricd',\n",
" 'r_giccd',\n",
" 'r_hcalendr',\n",
" 'r_idxclscd',\n",
" 'r_inactvcd',\n",
" 'r_incstats',\n",
" 'r_indfmt',\n",
" 'r_indsec',\n",
" 'r_invval',\n",
" 'r_issuetyp',\n",
" 'r_majidxcl',\n",
" 'r_mic_codes',\n",
" 'r_naiccd',\n",
" 'r_notetype',\n",
" 'r_ntsubtype',\n",
" 'r_offcrso',\n",
" 'r_ogmethod',\n",
" 'r_opinions',\n",
" 'r_prc_stat',\n",
" 'r_qsrcdoc',\n",
" 'r_sec_stat',\n",
" 'r_secannfn',\n",
" 'r_sectors',\n",
" 'r_siccd',\n",
" 'r_spiicd',\n",
" 'r_spmicd',\n",
" 'r_statalrt',\n",
" 'r_states',\n",
" 'r_stko',\n",
" 'r_titles',\n",
" 'r_updates',\n",
" 'sec_adesind',\n",
" 'sec_adjfact',\n",
" 'sec_afnd',\n",
" 'sec_afnddc',\n",
" 'sec_afnt',\n",
" 'sec_divid',\n",
" 'sec_dprc',\n",
" 'sec_dtrt',\n",
" 'sec_history',\n",
" 'sec_idesind',\n",
" 'sec_ifnd',\n",
" 'sec_ifnt',\n",
" 'sec_mdivfn',\n",
" 'sec_mshare',\n",
" 'sec_msptfn',\n",
" 'sec_mth',\n",
" 'sec_mthdiv',\n",
" 'sec_mthprc',\n",
" 'sec_mthspt',\n",
" 'sec_mthtrt',\n",
" 'sec_shortint',\n",
" 'sec_spind',\n",
" 'sec_split',\n",
" 'secd',\n",
" 'secm',\n",
" 'security',\n",
" 'sedolgvkey',\n",
" 'seg_ann',\n",
" 'seg_annfund',\n",
" 'seg_customer',\n",
" 'seg_geo',\n",
" 'seg_naics',\n",
" 'seg_product',\n",
" 'seg_type',\n",
" 'spidx_cst',\n",
" 'spind',\n",
" 'spind_dly',\n",
" 'spind_mth',\n",
" 'tmptable_pkg6153_tbl4023',\n",
" 'wrds_seg_customer',\n",
" 'wrds_seg_geo',\n",
" 'wrds_seg_product',\n",
" 'wrds_segmerged',\n",
" 'xfl_column',\n",
" 'xfl_table']"
]
},
"metadata": {},
"execution_count": 17
}
]
},
{
"cell_type": "code",
"source": [
"conn.describe_table('comp', 'funda')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 441
},
"id": "vj-8i-5UOp9H",
"outputId": "35364a48-a50f-453c-dff9-3b0810e1a0d9"
},
"execution_count": 18,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 858064 rows in comp.funda.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 gvkey True VARCHAR(6)\n",
"1 datadate True DATE\n",
"2 fyear True DOUBLE_PRECISION\n",
"3 indfmt True VARCHAR(12)\n",
"4 consol True VARCHAR(2)\n",
".. ... ... ...\n",
"943 au True VARCHAR(8)\n",
"944 auop True VARCHAR(8)\n",
"945 auopic True VARCHAR(1)\n",
"946 ceoso True VARCHAR(1)\n",
"947 cfoso True VARCHAR(1)\n",
"\n",
"[948 rows x 3 columns]"
],
"text/html": [
"\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" name | \n",
" nullable | \n",
" type | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" gvkey | \n",
" True | \n",
" VARCHAR(6) | \n",
"
\n",
" \n",
" 1 | \n",
" datadate | \n",
" True | \n",
" DATE | \n",
"
\n",
" \n",
" 2 | \n",
" fyear | \n",
" True | \n",
" DOUBLE_PRECISION | \n",
"
\n",
" \n",
" 3 | \n",
" indfmt | \n",
" True | \n",
" VARCHAR(12) | \n",
"
\n",
" \n",
" 4 | \n",
" consol | \n",
" True | \n",
" VARCHAR(2) | \n",
"
\n",
" \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
"
\n",
" \n",
" 943 | \n",
" au | \n",
" True | \n",
" VARCHAR(8) | \n",
"
\n",
" \n",
" 944 | \n",
" auop | \n",
" True | \n",
" VARCHAR(8) | \n",
"
\n",
" \n",
" 945 | \n",
" auopic | \n",
" True | \n",
" VARCHAR(1) | \n",
"
\n",
" \n",
" 946 | \n",
" ceoso | \n",
" True | \n",
" VARCHAR(1) | \n",
"
\n",
" \n",
" 947 | \n",
" cfoso | \n",
" True | \n",
" VARCHAR(1) | \n",
"
\n",
" \n",
"
\n",
"
948 rows × 3 columns
\n",
"
\n",
"
\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"
\n",
" "
]
},
"metadata": {},
"execution_count": 18
}
]
},
{
"cell_type": "code",
"source": [
""
],
"metadata": {
"id": "wzQwPWPTP8UK"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"firm_names = conn.get_table(library = 'comp', table ='funda', \n",
" columns=['gvkey', 'fyear','datadate', 'tic','conm'])\n",
"firm_names.info()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "gtaxig-mO2Vk",
"outputId": "fca94e21-0c68-4e6d-87fc-071743fc9912"
},
"execution_count": 20,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"Int64Index: 858064 entries, 0 to 358063\n",
"Data columns (total 5 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 gvkey 858064 non-null object \n",
" 1 fyear 857868 non-null float64\n",
" 2 datadate 858064 non-null object \n",
" 3 tic 857836 non-null object \n",
" 4 conm 858064 non-null object \n",
"dtypes: float64(1), object(4)\n",
"memory usage: 39.3+ MB\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"help(conn.raw_sql)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "g00I2tQES8ra",
"outputId": "5af3c201-a640-4512-e863-370872b962e2"
},
"execution_count": 22,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Help on method raw_sql in module wrds.sql:\n",
"\n",
"raw_sql(sql, coerce_float=True, date_cols=None, index_col=None, params=None, chunksize=500000, return_iter=False) method of wrds.sql.Connection instance\n",
" Queries the database using a raw SQL string.\n",
" \n",
" :param sql: SQL code in string object.\n",
" :param coerce_float: (optional) boolean, default: True\n",
" Attempt to convert values to non-string, non-numeric objects\n",
" to floating point. Can result in loss of precision.\n",
" :param date_cols: (optional) list or dict, default: None\n",
" - List of column names to parse as date\n",
" - Dict of ``{column_name: format string}`` where\n",
" format string is:\n",
" strftime compatible in case of parsing string times or\n",
" is one of (D, s, ns, ms, us) in case of parsing\n",
" integer timestamps\n",
" - Dict of ``{column_name: arg dict}``,\n",
" where the arg dict corresponds to the keyword arguments of\n",
" :func:`pandas.to_datetime`\n",
" :param index_col: (optional) string or list of strings,\n",
" default: None\n",
" Column(s) to set as index(MultiIndex)\n",
" :param params: parameters to SQL query, if parameterized.\n",
" :param chunksize: (optional) integer or None default: 500000\n",
" Process query in chunks of this size. Smaller chunksizes can save\n",
" a considerable amount of memory while query is being processed.\n",
" Set to None run query w/o chunking.\n",
" :param return_iter: (optional) boolean, default:False\n",
" When chunksize is not None, return an iterator where chunksize\n",
" number of rows is included in each chunk.\n",
" \n",
" :rtype: pandas.DataFrame or or Iterator[pandas.DataFrame]\n",
" \n",
" \n",
" Usage ::\n",
" # Basic Usage\n",
" >>> data = db.raw_sql('select cik, fdate, coname from wrdssec_all.dforms;', date_cols=['fdate'], index_col='cik')\n",
" >>> data.head()\n",
" cik fdate coname\n",
" 0000000003 1995-02-15 DEFINED ASSET FUNDS MUNICIPAL INVT TR FD NEW Y...\n",
" 0000000003 1996-02-14 DEFINED ASSET FUNDS MUNICIPAL INVT TR FD NEW Y...\n",
" 0000000003 1997-02-19 DEFINED ASSET FUNDS MUNICIPAL INVT TR FD NEW Y...\n",
" 0000000003 1998-03-02 DEFINED ASSET FUNDS MUNICIPAL INVT TR FD NEW Y...\n",
" 0000000003 1998-03-10 DEFINED ASSET FUNDS MUNICIPAL INVT TR FD NEW Y..\n",
" ...\n",
" \n",
" # Parameterized SQL query\n",
" >>> parm = {'syms': ('A', 'AA', 'AAPL'), 'num_shares': 50000}\n",
" >>> data = db.raw_sql('select * from taqmsec.ctm_20030910 where sym_root in %(syms)s and size > %(num_shares)s', params=parm)\n",
" >>> data.head()\n",
" date time_m ex sym_root sym_suffix tr_scond size price tr_stopind tr_corr tr_seqnum tr_source tr_rf\n",
" 2003-09-10 11:02:09.485000 T A None None 211400.0 25.350 N 00 1.929952e+15 C None\n",
" 2003-09-10 11:04:29.508000 N A None None 55500.0 25.180 N 00 1.929952e+15 C None\n",
" 2003-09-10 15:08:21.155000 N A None None 50500.0 24.470 N 00 1.929967e+15 C None\n",
" 2003-09-10 16:10:35.522000 T A None B 71900.0 24.918 N 00 1.929970e+15 C None\n",
" 2003-09-10 09:35:20.709000 N AA None None 108100.0 28.200 N 00 1.929947e+15 C None\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"crsp = conn.raw_sql(\"\"\"\n",
" SELECT permno, date, cusip, permco, ret, vol, shrout, prc, cfacpr, cfacshr\n",
" FROM crsp.msf \n",
" WHERE date BETWEEN '01/01/2020' AND '12/31/2021'\n",
" \n",
" \"\"\", date_cols = ['date']) \n",
"print(crsp.head(10))\n",
"print(crsp.info())"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "CExBHXZNSwwb",
"outputId": "986f4062-803d-40a5-f6c5-da1544d1e8b1"
},
"execution_count": 29,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" permno date cusip permco ret vol shrout \\\n",
"0 10026.0 2020-01-31 46603210 7976.0 -0.100016 22433.0 18919.0 \n",
"1 10028.0 2020-01-31 29402E10 7978.0 0.607407 27373.0 26924.0 \n",
"2 10032.0 2020-01-31 72913210 7980.0 -0.075643 41351.0 29222.0 \n",
"3 10044.0 2020-01-31 77467X10 7992.0 -0.098592 4414.0 6000.0 \n",
"4 10051.0 2020-01-31 41043F20 7999.0 -0.115176 51275.0 37338.0 \n",
"5 10065.0 2020-01-31 00621210 20023.0 0.005707 58175.0 105413.0 \n",
"6 10066.0 2020-01-31 35518410 6331.0 NaN NaN 43809.0 \n",
"7 10104.0 2020-01-31 68389X10 8045.0 -0.005474 2005627.0 3207649.0 \n",
"8 10107.0 2020-01-31 59491810 8048.0 0.079455 5588346.0 7606047.0 \n",
"9 10113.0 2020-01-31 00768Y20 53202.0 -0.001206 5322.0 2250.0 \n",
"\n",
" prc cfacpr cfacshr \n",
"0 165.839996 1.0 1.0 \n",
"1 2.170000 1.0 1.0 \n",
"2 71.120003 1.0 1.0 \n",
"3 8.320000 1.0 1.0 \n",
"4 24.430000 1.0 1.0 \n",
"5 15.860000 1.0 1.0 \n",
"6 NaN 1.0 1.0 \n",
"7 52.450001 1.0 1.0 \n",
"8 170.229996 1.0 1.0 \n",
"9 53.825001 1.0 1.0 \n",
"\n",
"RangeIndex: 200262 entries, 0 to 200261\n",
"Data columns (total 10 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 permno 200262 non-null float64 \n",
" 1 date 200262 non-null datetime64[ns]\n",
" 2 cusip 200262 non-null object \n",
" 3 permco 200262 non-null float64 \n",
" 4 ret 193846 non-null float64 \n",
" 5 vol 197238 non-null float64 \n",
" 6 shrout 197797 non-null float64 \n",
" 7 prc 196431 non-null float64 \n",
" 8 cfacpr 197797 non-null float64 \n",
" 9 cfacshr 197797 non-null float64 \n",
"dtypes: datetime64[ns](1), float64(8), object(1)\n",
"memory usage: 15.3+ MB\n",
"None\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "yB5_XBDsNhBx",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "b980a3b2-bb6b-433f-9b65-20f8e0ec27ba"
},
"source": [
"#checking data intergrity\n",
"check = {\"tickers\": (\"MSFT\", \"TSLA\", \"COP\", \"AAPL\", \"WMT\")}\n",
"checking = conn.raw_sql('select * from crsp.dse WHERE ticker in %(tickers)s', params=check)\n",
"checking"
],
"execution_count": 33,
"outputs": [
{
"output_type": "execute_result",
"data": {
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"0 NAMES 1980-12-12 35.0 357.0 APPLE COMPUTER INC 03783310 \n",
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"5 NAMES 2002-09-03 13.0 138.0 CONOCOPHILLIPS 20825C10 \n",
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"7 NAMES 2004-06-10 13.0 138.0 CONOCOPHILLIPS 20825C10 \n",
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"13 NAMES 2010-06-29 99.0 999.0 TESLA MOTORS INC 88160R10 \n",
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"15 NAMES 1972-11-20 53.0 531.0 WAL MART STORES INC 93114210 \n",
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"18 NAMES 2012-03-01 53.0 531.0 WAL MART STORES INC 93114210 \n",
"19 NAMES 2014-01-07 53.0 531.0 WAL MART STORES INC 93114210 \n",
"20 NAMES 2018-02-01 53.0 531.0 WALMART INC 93114210 \n",
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"\n",
" dclrdt dlamt dlpdt dlstcd ... dlretx dlprc dlret shrout shrenddt trtscd \\\n",
"0 None None None None ... None None None None None None \n",
"1 None None None None ... None None None None None None \n",
"2 None None None None ... None None None None None None \n",
"3 None None None None ... None None None None None None \n",
"4 None None None None ... None None None None None None \n",
"5 None None None None ... None None None None None None \n",
"6 None None None None ... None None None None None None \n",
"7 None None None None ... None None None None None None \n",
"8 None None None None ... None None None None None None \n",
"9 None None None None ... None None None None None None \n",
"10 None None None None ... None None None None None None \n",
"11 None None None None ... None None None None None None \n",
"12 None None None None ... None None None None None None \n",
"13 None None None None ... None None None None None None \n",
"14 None None None None ... None None None None None None \n",
"15 None None None None ... None None None None None None \n",
"16 None None None None ... None None None None None None \n",
"17 None None None None ... None None None None None None \n",
"18 None None None None ... None None None None None None \n",
"19 None None None None ... None None None None None None \n",
"20 None None None None ... None None None None None None \n",
"21 None None None None ... None None None None None None \n",
"\n",
" trtsendt nmsind mmcnt nsdinx \n",
"0 None None None None \n",
"1 None None None None \n",
"2 None None None None \n",
"3 None None None None \n",
"4 None None None None \n",
"5 None None None None \n",
"6 None None None None \n",
"7 None None None None \n",
"8 None None None None \n",
"9 None None None None \n",
"10 None None None None \n",
"11 None None None None \n",
"12 None None None None \n",
"13 None None None None \n",
"14 None None None None \n",
"15 None None None None \n",
"16 None None None None \n",
"17 None None None None \n",
"18 None None None None \n",
"19 None None None None \n",
"20 None None None None \n",
"21 None None None None \n",
"\n",
"[22 rows x 50 columns]"
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" 14 | \n",
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" None | \n",
" None | \n",
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" None | \n",
" None | \n",
" None | \n",
" None | \n",
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\n",
" \n",
" 20 | \n",
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" 53.0 | \n",
" 531.0 | \n",
" WALMART INC | \n",
" 93114210 | \n",
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" None | \n",
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" None | \n",
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\n",
" \n",
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" 93114210 | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" ... | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
" None | \n",
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"metadata": {},
"execution_count": 33
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "jsf6pBO7NK1e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 873
},
"outputId": "2bea403a-991b-4aff-b25e-3e66883f2756"
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"source": [
"checking = conn.raw_sql('select * from crsp.stocknames WHERE ticker in %(tickers)s', params=check)\n",
"checking"
],
"execution_count": 34,
"outputs": [
{
"output_type": "execute_result",
"data": {
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" permno namedt nameenddt shrcd exchcd siccd ncusip ticker \\\n",
"0 10107.0 1986-03-13 2022-03-31 11.0 3.0 7370.0 59491810 MSFT \n",
"1 13928.0 2002-09-03 2004-02-17 11.0 1.0 1311.0 20825C10 COP \n",
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"4 14593.0 1980-12-12 2007-01-10 11.0 3.0 3573.0 03783310 AAPL \n",
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"\n",
" comnam shrcls permco hexcd cusip st_date \\\n",
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"2 CONOCOPHILLIPS None 21401.0 1.0 20825C10 1925-12-31 \n",
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"9 WAL MART STORES INC None 21880.0 1.0 93114210 1972-11-20 \n",
"10 WAL MART STORES INC None 21880.0 1.0 93114210 1972-11-20 \n",
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"14 TESLA MOTORS INC None 53453.0 3.0 88160R10 2010-06-29 \n",
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" 93114210 | \n",
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" 1.0 | \n",
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\n",
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" 2018-01-31 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5331.0 | \n",
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" 5311.0 | \n",
" 93114210 | \n",
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" 93114210 | \n",
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\n",
" \n",
" 15 | \n",
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" 3.0 | \n",
" 9999.0 | \n",
" 88160R10 | \n",
" TSLA | \n",
" TESLA INC | \n",
" None | \n",
" 53453.0 | \n",
" 3.0 | \n",
" 88160R10 | \n",
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},
"metadata": {},
"execution_count": 34
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "_Sk8tKJnKRYj",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "399c40fd-90d4-443f-c7e5-2aeac5580871"
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"source": [
"checking = conn.raw_sql('select * from crsp.dsenames WHERE ticker in %(tickers)s', params=check)\n",
"checking"
],
"execution_count": 35,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" permno namedt nameendt shrcd exchcd siccd ncusip ticker \\\n",
"0 14593.0 1980-12-12 1982-10-31 11.0 3.0 3573.0 03783310 AAPL \n",
"1 14593.0 1982-11-01 2004-06-09 11.0 3.0 3573.0 03783310 AAPL \n",
"2 14593.0 2004-06-10 2007-01-10 11.0 3.0 3573.0 03783310 AAPL \n",
"3 14593.0 2007-01-11 2017-12-27 11.0 3.0 3571.0 03783310 AAPL \n",
"4 14593.0 2017-12-28 2022-03-31 11.0 3.0 3571.0 03783310 AAPL \n",
"5 13928.0 2002-09-03 2004-02-17 11.0 1.0 1311.0 20825C10 COP \n",
"6 13928.0 2004-02-18 2004-06-09 11.0 1.0 2911.0 20825C10 COP \n",
"7 13928.0 2004-06-10 2014-01-30 11.0 1.0 2911.0 20825C10 COP \n",
"8 13928.0 2014-01-31 2022-03-31 11.0 1.0 1382.0 20825C10 COP \n",
"9 26607.0 1996-11-19 2001-02-11 11.0 1.0 5812.0 20979810 COP \n",
"10 67854.0 1985-07-19 1996-06-19 18.0 2.0 6799.0 21745410 COP \n",
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"15 55976.0 1972-11-20 2002-01-01 11.0 1.0 5311.0 93114210 WMT \n",
"16 55976.0 2002-01-02 2004-06-09 11.0 1.0 5331.0 93114210 WMT \n",
"17 55976.0 2004-06-10 2012-02-29 11.0 1.0 5331.0 93114210 WMT \n",
"18 55976.0 2012-03-01 2014-01-06 11.0 1.0 5311.0 93114210 WMT \n",
"19 55976.0 2014-01-07 2018-01-31 11.0 1.0 5331.0 93114210 WMT \n",
"20 55976.0 2018-02-01 2020-11-17 11.0 1.0 5331.0 93114210 WMT \n",
"21 55976.0 2020-11-18 2022-03-31 11.0 1.0 5311.0 93114210 WMT \n",
"\n",
" comnam shrcls ... naics primexch trdstat secstat \\\n",
"0 APPLE COMPUTER INC None ... None Q A R \n",
"1 APPLE COMPUTER INC None ... None Q A R \n",
"2 APPLE COMPUTER INC None ... 334111 Q A R \n",
"3 APPLE INC None ... 334111 Q A R \n",
"4 APPLE INC None ... 334220 Q A R \n",
"5 CONOCOPHILLIPS None ... None N A R \n",
"6 CONOCOPHILLIPS None ... None N A R \n",
"7 CONOCOPHILLIPS None ... 324110 N A R \n",
"8 CONOCOPHILLIPS None ... 213112 N A R \n",
"9 CONSOLIDATED PRODUCTS INC None ... None N A R \n",
"10 COPLEY PROPERTY INC None ... None A A R \n",
"11 MICROSOFT CORP None ... None Q A R \n",
"12 MICROSOFT CORP None ... 511210 Q A R \n",
"13 TESLA MOTORS INC None ... 336111 Q A R \n",
"14 TESLA INC None ... 336111 Q A R \n",
"15 WAL MART STORES INC None ... None N A R \n",
"16 WAL MART STORES INC None ... None N A R \n",
"17 WAL MART STORES INC None ... 452990 N A R \n",
"18 WAL MART STORES INC None ... 452990 N A R \n",
"19 WAL MART STORES INC None ... 452990 N A R \n",
"20 WALMART INC None ... 452990 N A R \n",
"21 WALMART INC None ... 452210 N A R \n",
"\n",
" permco compno issuno hexcd hsiccd cusip \n",
"0 7.0 60000006.0 8.0 3.0 3571.0 03783310 \n",
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"2 7.0 60000006.0 8.0 3.0 3571.0 03783310 \n",
"3 7.0 60000006.0 8.0 3.0 3571.0 03783310 \n",
"4 7.0 60000006.0 8.0 3.0 3571.0 03783310 \n",
"5 21401.0 0.0 0.0 1.0 1382.0 20825C10 \n",
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"7 21401.0 0.0 0.0 1.0 1382.0 20825C10 \n",
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"9 4255.0 60004254.0 5399.0 1.0 2099.0 08986R30 \n",
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"11 8048.0 60008001.0 10539.0 3.0 7370.0 59491810 \n",
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"13 53453.0 60069832.0 66252.0 3.0 9999.0 88160R10 \n",
"14 53453.0 60069832.0 66252.0 3.0 9999.0 88160R10 \n",
"15 21880.0 0.0 0.0 1.0 5311.0 93114210 \n",
"16 21880.0 0.0 0.0 1.0 5311.0 93114210 \n",
"17 21880.0 0.0 0.0 1.0 5311.0 93114210 \n",
"18 21880.0 0.0 0.0 1.0 5311.0 93114210 \n",
"19 21880.0 0.0 0.0 1.0 5311.0 93114210 \n",
"20 21880.0 0.0 0.0 1.0 5311.0 93114210 \n",
"21 21880.0 0.0 0.0 1.0 5311.0 93114210 \n",
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" 3.0 | \n",
" 3573.0 | \n",
" 03783310 | \n",
" AAPL | \n",
" APPLE COMPUTER INC | \n",
" None | \n",
" ... | \n",
" None | \n",
" Q | \n",
" A | \n",
" R | \n",
" 7.0 | \n",
" 60000006.0 | \n",
" 8.0 | \n",
" 3.0 | \n",
" 3571.0 | \n",
" 03783310 | \n",
"
\n",
" \n",
" 1 | \n",
" 14593.0 | \n",
" 1982-11-01 | \n",
" 2004-06-09 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 3573.0 | \n",
" 03783310 | \n",
" AAPL | \n",
" APPLE COMPUTER INC | \n",
" None | \n",
" ... | \n",
" None | \n",
" Q | \n",
" A | \n",
" R | \n",
" 7.0 | \n",
" 60000006.0 | \n",
" 8.0 | \n",
" 3.0 | \n",
" 3571.0 | \n",
" 03783310 | \n",
"
\n",
" \n",
" 2 | \n",
" 14593.0 | \n",
" 2004-06-10 | \n",
" 2007-01-10 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 3573.0 | \n",
" 03783310 | \n",
" AAPL | \n",
" APPLE COMPUTER INC | \n",
" None | \n",
" ... | \n",
" 334111 | \n",
" Q | \n",
" A | \n",
" R | \n",
" 7.0 | \n",
" 60000006.0 | \n",
" 8.0 | \n",
" 3.0 | \n",
" 3571.0 | \n",
" 03783310 | \n",
"
\n",
" \n",
" 3 | \n",
" 14593.0 | \n",
" 2007-01-11 | \n",
" 2017-12-27 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 3571.0 | \n",
" 03783310 | \n",
" AAPL | \n",
" APPLE INC | \n",
" None | \n",
" ... | \n",
" 334111 | \n",
" Q | \n",
" A | \n",
" R | \n",
" 7.0 | \n",
" 60000006.0 | \n",
" 8.0 | \n",
" 3.0 | \n",
" 3571.0 | \n",
" 03783310 | \n",
"
\n",
" \n",
" 4 | \n",
" 14593.0 | \n",
" 2017-12-28 | \n",
" 2022-03-31 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 3571.0 | \n",
" 03783310 | \n",
" AAPL | \n",
" APPLE INC | \n",
" None | \n",
" ... | \n",
" 334220 | \n",
" Q | \n",
" A | \n",
" R | \n",
" 7.0 | \n",
" 60000006.0 | \n",
" 8.0 | \n",
" 3.0 | \n",
" 3571.0 | \n",
" 03783310 | \n",
"
\n",
" \n",
" 5 | \n",
" 13928.0 | \n",
" 2002-09-03 | \n",
" 2004-02-17 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 1311.0 | \n",
" 20825C10 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" None | \n",
" ... | \n",
" None | \n",
" N | \n",
" A | \n",
" R | \n",
" 21401.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 1382.0 | \n",
" 20825C10 | \n",
"
\n",
" \n",
" 6 | \n",
" 13928.0 | \n",
" 2004-02-18 | \n",
" 2004-06-09 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 2911.0 | \n",
" 20825C10 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" None | \n",
" ... | \n",
" None | \n",
" N | \n",
" A | \n",
" R | \n",
" 21401.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 1382.0 | \n",
" 20825C10 | \n",
"
\n",
" \n",
" 7 | \n",
" 13928.0 | \n",
" 2004-06-10 | \n",
" 2014-01-30 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 2911.0 | \n",
" 20825C10 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" None | \n",
" ... | \n",
" 324110 | \n",
" N | \n",
" A | \n",
" R | \n",
" 21401.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 1382.0 | \n",
" 20825C10 | \n",
"
\n",
" \n",
" 8 | \n",
" 13928.0 | \n",
" 2014-01-31 | \n",
" 2022-03-31 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 1382.0 | \n",
" 20825C10 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" None | \n",
" ... | \n",
" 213112 | \n",
" N | \n",
" A | \n",
" R | \n",
" 21401.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 1382.0 | \n",
" 20825C10 | \n",
"
\n",
" \n",
" 9 | \n",
" 26607.0 | \n",
" 1996-11-19 | \n",
" 2001-02-11 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5812.0 | \n",
" 20979810 | \n",
" COP | \n",
" CONSOLIDATED PRODUCTS INC | \n",
" None | \n",
" ... | \n",
" None | \n",
" N | \n",
" A | \n",
" R | \n",
" 4255.0 | \n",
" 60004254.0 | \n",
" 5399.0 | \n",
" 1.0 | \n",
" 2099.0 | \n",
" 08986R30 | \n",
"
\n",
" \n",
" 10 | \n",
" 67854.0 | \n",
" 1985-07-19 | \n",
" 1996-06-19 | \n",
" 18.0 | \n",
" 2.0 | \n",
" 6799.0 | \n",
" 21745410 | \n",
" COP | \n",
" COPLEY PROPERTY INC | \n",
" None | \n",
" ... | \n",
" None | \n",
" A | \n",
" A | \n",
" R | \n",
" 20519.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 2.0 | \n",
" 6799.0 | \n",
" 21745410 | \n",
"
\n",
" \n",
" 11 | \n",
" 10107.0 | \n",
" 1986-03-13 | \n",
" 2004-06-09 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 7370.0 | \n",
" 59491810 | \n",
" MSFT | \n",
" MICROSOFT CORP | \n",
" None | \n",
" ... | \n",
" None | \n",
" Q | \n",
" A | \n",
" R | \n",
" 8048.0 | \n",
" 60008001.0 | \n",
" 10539.0 | \n",
" 3.0 | \n",
" 7370.0 | \n",
" 59491810 | \n",
"
\n",
" \n",
" 12 | \n",
" 10107.0 | \n",
" 2004-06-10 | \n",
" 2022-03-31 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 7370.0 | \n",
" 59491810 | \n",
" MSFT | \n",
" MICROSOFT CORP | \n",
" None | \n",
" ... | \n",
" 511210 | \n",
" Q | \n",
" A | \n",
" R | \n",
" 8048.0 | \n",
" 60008001.0 | \n",
" 10539.0 | \n",
" 3.0 | \n",
" 7370.0 | \n",
" 59491810 | \n",
"
\n",
" \n",
" 13 | \n",
" 93436.0 | \n",
" 2010-06-29 | \n",
" 2017-02-01 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 9999.0 | \n",
" 88160R10 | \n",
" TSLA | \n",
" TESLA MOTORS INC | \n",
" None | \n",
" ... | \n",
" 336111 | \n",
" Q | \n",
" A | \n",
" R | \n",
" 53453.0 | \n",
" 60069832.0 | \n",
" 66252.0 | \n",
" 3.0 | \n",
" 9999.0 | \n",
" 88160R10 | \n",
"
\n",
" \n",
" 14 | \n",
" 93436.0 | \n",
" 2017-02-02 | \n",
" 2022-03-31 | \n",
" 11.0 | \n",
" 3.0 | \n",
" 9999.0 | \n",
" 88160R10 | \n",
" TSLA | \n",
" TESLA INC | \n",
" None | \n",
" ... | \n",
" 336111 | \n",
" Q | \n",
" A | \n",
" R | \n",
" 53453.0 | \n",
" 60069832.0 | \n",
" 66252.0 | \n",
" 3.0 | \n",
" 9999.0 | \n",
" 88160R10 | \n",
"
\n",
" \n",
" 15 | \n",
" 55976.0 | \n",
" 1972-11-20 | \n",
" 2002-01-01 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
" WMT | \n",
" WAL MART STORES INC | \n",
" None | \n",
" ... | \n",
" None | \n",
" N | \n",
" A | \n",
" R | \n",
" 21880.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
"
\n",
" \n",
" 16 | \n",
" 55976.0 | \n",
" 2002-01-02 | \n",
" 2004-06-09 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5331.0 | \n",
" 93114210 | \n",
" WMT | \n",
" WAL MART STORES INC | \n",
" None | \n",
" ... | \n",
" None | \n",
" N | \n",
" A | \n",
" R | \n",
" 21880.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
"
\n",
" \n",
" 17 | \n",
" 55976.0 | \n",
" 2004-06-10 | \n",
" 2012-02-29 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5331.0 | \n",
" 93114210 | \n",
" WMT | \n",
" WAL MART STORES INC | \n",
" None | \n",
" ... | \n",
" 452990 | \n",
" N | \n",
" A | \n",
" R | \n",
" 21880.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
"
\n",
" \n",
" 18 | \n",
" 55976.0 | \n",
" 2012-03-01 | \n",
" 2014-01-06 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
" WMT | \n",
" WAL MART STORES INC | \n",
" None | \n",
" ... | \n",
" 452990 | \n",
" N | \n",
" A | \n",
" R | \n",
" 21880.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
"
\n",
" \n",
" 19 | \n",
" 55976.0 | \n",
" 2014-01-07 | \n",
" 2018-01-31 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5331.0 | \n",
" 93114210 | \n",
" WMT | \n",
" WAL MART STORES INC | \n",
" None | \n",
" ... | \n",
" 452990 | \n",
" N | \n",
" A | \n",
" R | \n",
" 21880.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
"
\n",
" \n",
" 20 | \n",
" 55976.0 | \n",
" 2018-02-01 | \n",
" 2020-11-17 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5331.0 | \n",
" 93114210 | \n",
" WMT | \n",
" WALMART INC | \n",
" None | \n",
" ... | \n",
" 452990 | \n",
" N | \n",
" A | \n",
" R | \n",
" 21880.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
"
\n",
" \n",
" 21 | \n",
" 55976.0 | \n",
" 2020-11-18 | \n",
" 2022-03-31 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
" WMT | \n",
" WALMART INC | \n",
" None | \n",
" ... | \n",
" 452210 | \n",
" N | \n",
" A | \n",
" R | \n",
" 21880.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 1.0 | \n",
" 5311.0 | \n",
" 93114210 | \n",
"
\n",
" \n",
"
\n",
"
22 rows × 21 columns
\n",
"
\n",
"
\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"
\n",
" "
]
},
"metadata": {},
"execution_count": 35
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "-X6vLSx_Jfb5",
"outputId": "6558f7c3-c45f-4515-f242-fac052ec0c70"
},
"source": [
"check = {'tickers': ('JNJ','COP')}\n",
"check"
],
"execution_count": 36,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'tickers': ('JNJ', 'COP')}"
]
},
"metadata": {},
"execution_count": 36
}
]
},
{
"cell_type": "code",
"source": [
"crsp = conn.raw_sql(\"\"\"\n",
" select a.permno, a.date, a.ret, b.rf, b.mktrf, b.smb, b.hml\n",
" from crsp.dsf as a\n",
" left join ff.factors_daily as b\n",
" on a.date=b.date\n",
" where a.date > '01/01/2020'\n",
" \"\"\")"
],
"metadata": {
"id": "gHNT9yMGSvij"
},
"execution_count": 37,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "wJAwstNwJVxR",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"outputId": "075bcb1b-c4e7-434b-fbfb-13b8a41553a5"
},
"source": [
"# this example shows that tickers are not a good screening id\n",
"checking = conn.raw_sql('select a.permno, a.ticker, a.comnam, b.date, b.prc, b.ret, b.retx, b.cfacpr from crsp.stocknames a join crsp.dsf b on a.permno = b.permno WHERE a.ticker in %(tickers)s and a.st_date <= b.date and b.date <= a.end_date', params=check)\n",
"checking"
],
"execution_count": 38,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" permno ticker comnam date prc ret \\\n",
"0 13928.0 COP CONOCOPHILLIPS 1925-12-31 46.500 NaN \n",
"1 13928.0 COP CONOCOPHILLIPS 1926-01-02 46.625 0.002688 \n",
"2 13928.0 COP CONOCOPHILLIPS 1926-01-04 46.500 -0.002681 \n",
"3 13928.0 COP CONOCOPHILLIPS 1926-01-05 45.750 -0.016129 \n",
"4 13928.0 COP CONOCOPHILLIPS 1926-01-06 45.750 0.000000 \n",
"... ... ... ... ... ... ... \n",
"209834 67854.0 COP COPLEY PROPERTY INC 1996-06-13 15.625 0.000000 \n",
"209835 67854.0 COP COPLEY PROPERTY INC 1996-06-14 15.250 -0.006720 \n",
"209836 67854.0 COP COPLEY PROPERTY INC 1996-06-17 15.375 0.008197 \n",
"209837 67854.0 COP COPLEY PROPERTY INC 1996-06-18 15.375 0.000000 \n",
"209838 67854.0 COP COPLEY PROPERTY INC 1996-06-19 15.375 0.000000 \n",
"\n",
" retx cfacpr \n",
"0 NaN 161.302414 \n",
"1 0.002688 161.302414 \n",
"2 -0.002681 161.302414 \n",
"3 -0.016129 161.302414 \n",
"4 0.000000 161.302414 \n",
"... ... ... \n",
"209834 0.000000 1.000000 \n",
"209835 -0.024000 1.000000 \n",
"209836 0.008197 1.000000 \n",
"209837 0.000000 1.000000 \n",
"209838 0.000000 1.000000 \n",
"\n",
"[209839 rows x 8 columns]"
],
"text/html": [
"\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" permno | \n",
" ticker | \n",
" comnam | \n",
" date | \n",
" prc | \n",
" ret | \n",
" retx | \n",
" cfacpr | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 13928.0 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" 1925-12-31 | \n",
" 46.500 | \n",
" NaN | \n",
" NaN | \n",
" 161.302414 | \n",
"
\n",
" \n",
" 1 | \n",
" 13928.0 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" 1926-01-02 | \n",
" 46.625 | \n",
" 0.002688 | \n",
" 0.002688 | \n",
" 161.302414 | \n",
"
\n",
" \n",
" 2 | \n",
" 13928.0 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" 1926-01-04 | \n",
" 46.500 | \n",
" -0.002681 | \n",
" -0.002681 | \n",
" 161.302414 | \n",
"
\n",
" \n",
" 3 | \n",
" 13928.0 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" 1926-01-05 | \n",
" 45.750 | \n",
" -0.016129 | \n",
" -0.016129 | \n",
" 161.302414 | \n",
"
\n",
" \n",
" 4 | \n",
" 13928.0 | \n",
" COP | \n",
" CONOCOPHILLIPS | \n",
" 1926-01-06 | \n",
" 45.750 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 161.302414 | \n",
"
\n",
" \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
"
\n",
" \n",
" 209834 | \n",
" 67854.0 | \n",
" COP | \n",
" COPLEY PROPERTY INC | \n",
" 1996-06-13 | \n",
" 15.625 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 1.000000 | \n",
"
\n",
" \n",
" 209835 | \n",
" 67854.0 | \n",
" COP | \n",
" COPLEY PROPERTY INC | \n",
" 1996-06-14 | \n",
" 15.250 | \n",
" -0.006720 | \n",
" -0.024000 | \n",
" 1.000000 | \n",
"
\n",
" \n",
" 209836 | \n",
" 67854.0 | \n",
" COP | \n",
" COPLEY PROPERTY INC | \n",
" 1996-06-17 | \n",
" 15.375 | \n",
" 0.008197 | \n",
" 0.008197 | \n",
" 1.000000 | \n",
"
\n",
" \n",
" 209837 | \n",
" 67854.0 | \n",
" COP | \n",
" COPLEY PROPERTY INC | \n",
" 1996-06-18 | \n",
" 15.375 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 1.000000 | \n",
"
\n",
" \n",
" 209838 | \n",
" 67854.0 | \n",
" COP | \n",
" COPLEY PROPERTY INC | \n",
" 1996-06-19 | \n",
" 15.375 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 1.000000 | \n",
"
\n",
" \n",
"
\n",
"
209839 rows × 8 columns
\n",
"
\n",
"
\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"
\n",
" "
]
},
"metadata": {},
"execution_count": 38
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "sbw8MWQVILM5"
},
"source": [
""
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "eXB3GxY565Ox"
},
"source": [
"# It looks that **COP** was assigned to two different companies, so I used `dsenames` file to find unique ticker using \"tsymbol\", instead of \"ticker\".\n",
"Now let's extract price data from CRSP using `sql` statement"
]
},
{
"cell_type": "code",
"metadata": {
"id": "ahicn5juOooI"
},
"source": [
"stocks = ['AAPL','TSLA','AMZN','FB', 'MSFT', 'WMT', 'HD', 'JNJ', 'JPM', 't']\n"
],
"execution_count": 39,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "3VA7hh4hWwR_",
"outputId": "737d5b37-cb57-4504-b876-32a10e89c68d"
},
"source": [
"# CRSP command takes tuples, not lists, so let's create tuples. \n",
"stocks = {'tickers': ('AAPL','TSLA','AMZN','FB', 'MSFT', 'WMT', 'HD', 'JNJ', 'JPM', 'COP')}\n",
"\n",
"print(stocks)\n",
"type(stocks)"
],
"execution_count": 40,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"{'tickers': ('AAPL', 'TSLA', 'AMZN', 'FB', 'MSFT', 'WMT', 'HD', 'JNJ', 'JPM', 'COP')}\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"dict"
]
},
"metadata": {},
"execution_count": 40
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "djhT8cNyu2Td",
"outputId": "f7c22876-ab31-40d4-dd51-726e9ecc942c"
},
"source": [
"raw_data_from_crsp = conn.raw_sql('select a.permno, a.ticker, a.comnam, a.tsymbol, b.date, b.prc, b.ret, b.retx, b.cfacpr from crsp.dsenames a join crsp.dsf b on a.permno = b.permno WHERE a.tsymbol in %(tickers)s and a.namedt <= b.date and b.date <= a.nameendt', params=stocks)\n",
"pd_data = pd.DataFrame(raw_data_from_crsp)\n",
"pd_data.info()"
],
"execution_count": 41,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"RangeIndex: 56367 entries, 0 to 56366\n",
"Data columns (total 9 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 permno 56367 non-null float64\n",
" 1 ticker 56367 non-null object \n",
" 2 comnam 56367 non-null object \n",
" 3 tsymbol 56367 non-null object \n",
" 4 date 56367 non-null object \n",
" 5 prc 56367 non-null float64\n",
" 6 ret 56363 non-null float64\n",
" 7 retx 56363 non-null float64\n",
" 8 cfacpr 56367 non-null float64\n",
"dtypes: float64(5), object(4)\n",
"memory usage: 3.9+ MB\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "AbLtSyVHJFEO",
"outputId": "78862c20-abed-4796-cf07-0a7c17af7f77"
},
"source": [
"# note that the most recent date for which data is available is the March 31 2022\n",
"pd_data.tail()"
],
"execution_count": 42,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" permno ticker comnam tsymbol date prc ret \\\n",
"56362 93436.0 TSLA TESLA INC TSLA 2022-03-25 1010.640015 -0.003235 \n",
"56363 93436.0 TSLA TESLA INC TSLA 2022-03-28 1091.839966 0.080345 \n",
"56364 93436.0 TSLA TESLA INC TSLA 2022-03-29 1099.569946 0.007080 \n",
"56365 93436.0 TSLA TESLA INC TSLA 2022-03-30 1093.989990 -0.005075 \n",
"56366 93436.0 TSLA TESLA INC TSLA 2022-03-31 1077.599976 -0.014982 \n",
"\n",
" retx cfacpr \n",
"56362 -0.003235 1.0 \n",
"56363 0.080345 1.0 \n",
"56364 0.007080 1.0 \n",
"56365 -0.005075 1.0 \n",
"56366 -0.014982 1.0 "
],
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"metadata": {},
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},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "FPyZQ3pOBC7X",
"outputId": "36410c70-598e-456d-ad36-567daa6da6b9"
},
"source": [
"# convert date to datetime\n",
"pd_data['date'] = pd.to_datetime(pd_data['date'], format='%Y-%m-%d')\n",
"pd_data.info()"
],
"execution_count": 43,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"RangeIndex: 56367 entries, 0 to 56366\n",
"Data columns (total 9 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 permno 56367 non-null float64 \n",
" 1 ticker 56367 non-null object \n",
" 2 comnam 56367 non-null object \n",
" 3 tsymbol 56367 non-null object \n",
" 4 date 56367 non-null datetime64[ns]\n",
" 5 prc 56367 non-null float64 \n",
" 6 ret 56363 non-null float64 \n",
" 7 retx 56363 non-null float64 \n",
" 8 cfacpr 56367 non-null float64 \n",
"dtypes: datetime64[ns](1), float64(5), object(3)\n",
"memory usage: 3.9+ MB\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"id": "WD8V4c_INr1n",
"outputId": "98f37ce9-73a4-4ba2-849d-621b1db574d4"
},
"source": [
"# setting index\n",
"pd_data_index= pd_data.set_index('date')\n",
"pd_data_index.head()"
],
"execution_count": 44,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" permno ticker comnam tsymbol prc ret retx \\\n",
"date \n",
"1986-03-13 10107.0 MSFT MICROSOFT CORP MSFT 28.00 NaN NaN \n",
"1986-03-14 10107.0 MSFT MICROSOFT CORP MSFT 29.00 0.035714 0.035714 \n",
"1986-03-17 10107.0 MSFT MICROSOFT CORP MSFT 29.50 0.017241 0.017241 \n",
"1986-03-18 10107.0 MSFT MICROSOFT CORP MSFT 28.75 -0.025424 -0.025424 \n",
"1986-03-19 10107.0 MSFT MICROSOFT CORP MSFT 28.25 -0.017391 -0.017391 \n",
"\n",
" cfacpr \n",
"date \n",
"1986-03-13 288.0 \n",
"1986-03-14 288.0 \n",
"1986-03-17 288.0 \n",
"1986-03-18 288.0 \n",
"1986-03-19 288.0 "
],
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"metadata": {},
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]
},
{
"cell_type": "code",
"metadata": {
"id": "MrsBwCQKAkc1"
},
"source": [
"# important: you need to adjust prices for splits\n",
"pd_data_index['adj_price'] = pd_data_index['prc'] / pd_data_index['cfacpr']\n"
],
"execution_count": 45,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "RWpcQHv4nQcx",
"outputId": "de6d413d-a4ad-4e46-8d26-48aacc043c00"
},
"source": [
"pd_data_index.info()"
],
"execution_count": 46,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"DatetimeIndex: 56367 entries, 1986-03-13 to 2022-03-31\n",
"Data columns (total 9 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 permno 56367 non-null float64\n",
" 1 ticker 56367 non-null object \n",
" 2 comnam 56367 non-null object \n",
" 3 tsymbol 56367 non-null object \n",
" 4 prc 56367 non-null float64\n",
" 5 ret 56363 non-null float64\n",
" 6 retx 56363 non-null float64\n",
" 7 cfacpr 56367 non-null float64\n",
" 8 adj_price 56367 non-null float64\n",
"dtypes: float64(6), object(3)\n",
"memory usage: 4.3+ MB\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "clrxb1DBn7DS",
"outputId": "096d86b6-39f5-4b40-f7a4-d4d62db96bd5"
},
"source": [
"#slicing ticker and price column\n",
"pd_data_index_tic_prc = pd_data_index[['ticker', 'prc']]\n",
"pd_data_index_tic_prc.info()"
],
"execution_count": 47,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"DatetimeIndex: 56367 entries, 1986-03-13 to 2022-03-31\n",
"Data columns (total 2 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 ticker 56367 non-null object \n",
" 1 prc 56367 non-null float64\n",
"dtypes: float64(1), object(1)\n",
"memory usage: 1.3+ MB\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"id": "gABjjK6Lo3vM",
"outputId": "e2b24bc3-d41b-491f-eb28-e5a4e1181c1a"
},
"source": [
"b = pd_data_index_tic_prc['2016-01-01' <= pd_data_index_tic_prc.index]\n",
"b.head()"
],
"execution_count": 48,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ticker prc\n",
"date \n",
"2016-01-04 MSFT 54.799999\n",
"2016-01-05 MSFT 55.049999\n",
"2016-01-06 MSFT 54.049999\n",
"2016-01-07 MSFT 52.169998\n",
"2016-01-08 MSFT 52.330002"
],
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"metadata": {},
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},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"id": "jvoMEtEXo36f",
"outputId": "9031af7b-56af-49de-ee5a-688d44fe304b"
},
"source": [
"c = b[b.index <= '2022-03-30']\n",
"c.tail()"
],
"execution_count": 49,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ticker prc\n",
"date \n",
"2022-03-24 TSLA 1013.919983\n",
"2022-03-25 TSLA 1010.640015\n",
"2022-03-28 TSLA 1091.839966\n",
"2022-03-29 TSLA 1099.569946\n",
"2022-03-30 TSLA 1093.989990"
],
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"metadata": {},
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},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "2INZWH2hZz85",
"outputId": "0d234321-9502-4459-a61a-b9c888725a81"
},
"source": [
"# 564 obs for each stock times 10 = 5640\n",
"c.info()"
],
"execution_count": 50,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"DatetimeIndex: 15720 entries, 2016-01-04 to 2022-03-30\n",
"Data columns (total 2 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 ticker 15720 non-null object \n",
" 1 prc 15720 non-null float64\n",
"dtypes: float64(1), object(1)\n",
"memory usage: 368.4+ KB\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"id": "oYC259BWOFY_",
"outputId": "e6b19888-bc9d-430c-c2f9-de74ef4cee32"
},
"source": [
"# I am transposing the table\n",
"table = c.pivot(columns='ticker')\n",
"# By specifying col[1] in below list comprehension\n",
"# You can select the stock names under multi-level column\n",
"table.columns = [col[1] for col in table.columns]\n",
"table.head()"
],
"execution_count": 51,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" AAPL AMZN COP FB HD \\\n",
"date \n",
"2016-01-04 105.349998 636.989990 46.880001 102.220001 131.070007 \n",
"2016-01-05 102.709999 633.789978 47.400002 102.730003 130.429993 \n",
"2016-01-06 100.699997 632.650024 45.349998 102.970001 129.080002 \n",
"2016-01-07 96.449997 607.940002 44.060001 97.919998 125.400002 \n",
"2016-01-08 96.959999 607.049988 43.290001 97.330002 123.900002 \n",
"\n",
" JNJ JPM MSFT TSLA WMT \n",
"date \n",
"2016-01-04 100.480003 63.619999 54.799999 223.410004 61.459999 \n",
"2016-01-05 100.900002 63.730000 55.049999 223.429993 62.919998 \n",
"2016-01-06 100.389999 62.810001 54.049999 219.039993 63.549999 \n",
"2016-01-07 99.220001 60.270000 52.169998 215.649994 65.029999 \n",
"2016-01-08 98.160004 58.919998 52.330002 211.000000 63.540001 "
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" 63.549999 | \n",
"
\n",
" \n",
" 2016-01-07 | \n",
" 96.449997 | \n",
" 607.940002 | \n",
" 44.060001 | \n",
" 97.919998 | \n",
" 125.400002 | \n",
" 99.220001 | \n",
" 60.270000 | \n",
" 52.169998 | \n",
" 215.649994 | \n",
" 65.029999 | \n",
"
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" \n",
" 2016-01-08 | \n",
" 96.959999 | \n",
" 607.049988 | \n",
" 43.290001 | \n",
" 97.330002 | \n",
" 123.900002 | \n",
" 98.160004 | \n",
" 58.919998 | \n",
" 52.330002 | \n",
" 211.000000 | \n",
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},
"metadata": {},
"execution_count": 51
}
]
},
{
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"id": "RH4aI7HhOE_E",
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},
"source": [
"table.describe()"
],
"execution_count": 52,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" AAPL AMZN COP FB HD \\\n",
"count 1572.000000 1572.000000 1572.000000 1572.000000 1572.000000 \n",
"mean 175.330286 1902.983279 54.482258 199.213537 214.836648 \n",
"std 69.720936 966.461703 13.797170 70.315908 72.500571 \n",
"min 90.339996 482.070007 22.670000 94.160004 111.849998 \n",
"25% 126.887501 978.232498 43.677500 148.205006 154.894997 \n",
"50% 159.724998 1768.514954 53.010000 180.589996 197.290001 \n",
"75% 198.482498 3042.352539 63.842500 239.764996 266.589989 \n",
"max 506.089996 3731.409912 107.500000 382.179993 416.179993 \n",
"\n",
" JNJ JPM MSFT TSLA WMT \n",
"count 1572.000000 1572.000000 1572.000000 1572.000000 1572.000000 \n",
"mean 138.392242 108.955929 144.355251 466.159653 104.908893 \n",
"std 18.057629 29.268680 83.147982 313.004977 27.596488 \n",
"min 95.750000 53.070000 48.430000 143.669998 60.840000 \n",
"25% 126.040003 90.672501 72.514997 253.690002 78.907503 \n",
"50% 136.875000 107.010002 112.660000 333.779999 100.004997 \n",
"75% 148.975002 126.087500 210.292500 652.897491 132.330002 \n",
"max 179.589996 171.779999 343.109985 2238.750000 152.789993 "
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"text/html": [
"\n",
" \n",
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"\n",
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" \n",
" \n",
" | \n",
" AAPL | \n",
" AMZN | \n",
" COP | \n",
" FB | \n",
" HD | \n",
" JNJ | \n",
" JPM | \n",
" MSFT | \n",
" TSLA | \n",
" WMT | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 175.330286 | \n",
" 1902.983279 | \n",
" 54.482258 | \n",
" 199.213537 | \n",
" 214.836648 | \n",
" 138.392242 | \n",
" 108.955929 | \n",
" 144.355251 | \n",
" 466.159653 | \n",
" 104.908893 | \n",
"
\n",
" \n",
" std | \n",
" 69.720936 | \n",
" 966.461703 | \n",
" 13.797170 | \n",
" 70.315908 | \n",
" 72.500571 | \n",
" 18.057629 | \n",
" 29.268680 | \n",
" 83.147982 | \n",
" 313.004977 | \n",
" 27.596488 | \n",
"
\n",
" \n",
" min | \n",
" 90.339996 | \n",
" 482.070007 | \n",
" 22.670000 | \n",
" 94.160004 | \n",
" 111.849998 | \n",
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" 53.070000 | \n",
" 48.430000 | \n",
" 143.669998 | \n",
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"
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" \n",
" 25% | \n",
" 126.887501 | \n",
" 978.232498 | \n",
" 43.677500 | \n",
" 148.205006 | \n",
" 154.894997 | \n",
" 126.040003 | \n",
" 90.672501 | \n",
" 72.514997 | \n",
" 253.690002 | \n",
" 78.907503 | \n",
"
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" \n",
" 50% | \n",
" 159.724998 | \n",
" 1768.514954 | \n",
" 53.010000 | \n",
" 180.589996 | \n",
" 197.290001 | \n",
" 136.875000 | \n",
" 107.010002 | \n",
" 112.660000 | \n",
" 333.779999 | \n",
" 100.004997 | \n",
"
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" 75% | \n",
" 198.482498 | \n",
" 3042.352539 | \n",
" 63.842500 | \n",
" 239.764996 | \n",
" 266.589989 | \n",
" 148.975002 | \n",
" 126.087500 | \n",
" 210.292500 | \n",
" 652.897491 | \n",
" 132.330002 | \n",
"
\n",
" \n",
" max | \n",
" 506.089996 | \n",
" 3731.409912 | \n",
" 107.500000 | \n",
" 382.179993 | \n",
" 416.179993 | \n",
" 179.589996 | \n",
" 171.779999 | \n",
" 343.109985 | \n",
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"table.describe([.01,.1, .9, .99])"
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"height": 363
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"id": "wWUkJO2tWOVP",
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},
"execution_count": 53,
"outputs": [
{
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"data": {
"text/plain": [
" AAPL AMZN COP FB HD \\\n",
"count 1572.000000 1572.000000 1572.000000 1572.000000 1572.000000 \n",
"mean 175.330286 1902.983279 54.482258 199.213537 214.836648 \n",
"std 69.720936 966.461703 13.797170 70.315908 72.500571 \n",
"min 90.339996 482.070007 22.670000 94.160004 111.849998 \n",
"1% 93.958098 553.678387 30.198100 100.637500 120.730203 \n",
"10% 108.184000 757.186993 39.472001 119.535997 132.811993 \n",
"50% 159.724998 1768.514954 53.010000 180.589996 197.290001 \n",
"90% 271.390991 3320.144116 71.685997 323.749991 325.509991 \n",
"99% 441.468004 3589.468743 97.592703 370.564304 407.781591 \n",
"max 506.089996 3731.409912 107.500000 382.179993 416.179993 \n",
"\n",
" JNJ JPM MSFT TSLA WMT \n",
"count 1572.000000 1572.000000 1572.000000 1572.000000 1572.000000 \n",
"mean 138.392242 108.955929 144.355251 466.159653 104.908893 \n",
"std 18.057629 29.268680 83.147982 313.004977 27.596488 \n",
"min 95.750000 53.070000 48.430000 143.669998 60.840000 \n",
"1% 101.098801 57.068402 50.070000 180.739498 64.085202 \n",
"10% 115.341997 65.810998 57.189999 212.926004 69.706997 \n",
"50% 136.875000 107.010002 112.660000 333.779999 100.004997 \n",
"90% 165.528999 155.119995 286.537009 879.536011 143.327997 \n",
"99% 175.211599 168.477704 336.495103 1548.547510 150.232899 \n",
"max 179.589996 171.779999 343.109985 2238.750000 152.789993 "
],
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"\n",
" \n",
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"\n",
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" \n",
" \n",
" | \n",
" AAPL | \n",
" AMZN | \n",
" COP | \n",
" FB | \n",
" HD | \n",
" JNJ | \n",
" JPM | \n",
" MSFT | \n",
" TSLA | \n",
" WMT | \n",
"
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" \n",
" \n",
" \n",
" count | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
" 1572.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 175.330286 | \n",
" 1902.983279 | \n",
" 54.482258 | \n",
" 199.213537 | \n",
" 214.836648 | \n",
" 138.392242 | \n",
" 108.955929 | \n",
" 144.355251 | \n",
" 466.159653 | \n",
" 104.908893 | \n",
"
\n",
" \n",
" std | \n",
" 69.720936 | \n",
" 966.461703 | \n",
" 13.797170 | \n",
" 70.315908 | \n",
" 72.500571 | \n",
" 18.057629 | \n",
" 29.268680 | \n",
" 83.147982 | \n",
" 313.004977 | \n",
" 27.596488 | \n",
"
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" \n",
" min | \n",
" 90.339996 | \n",
" 482.070007 | \n",
" 22.670000 | \n",
" 94.160004 | \n",
" 111.849998 | \n",
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" 53.070000 | \n",
" 48.430000 | \n",
" 143.669998 | \n",
" 60.840000 | \n",
"
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" \n",
" 1% | \n",
" 93.958098 | \n",
" 553.678387 | \n",
" 30.198100 | \n",
" 100.637500 | \n",
" 120.730203 | \n",
" 101.098801 | \n",
" 57.068402 | \n",
" 50.070000 | \n",
" 180.739498 | \n",
" 64.085202 | \n",
"
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" \n",
" 10% | \n",
" 108.184000 | \n",
" 757.186993 | \n",
" 39.472001 | \n",
" 119.535997 | \n",
" 132.811993 | \n",
" 115.341997 | \n",
" 65.810998 | \n",
" 57.189999 | \n",
" 212.926004 | \n",
" 69.706997 | \n",
"
\n",
" \n",
" 50% | \n",
" 159.724998 | \n",
" 1768.514954 | \n",
" 53.010000 | \n",
" 180.589996 | \n",
" 197.290001 | \n",
" 136.875000 | \n",
" 107.010002 | \n",
" 112.660000 | \n",
" 333.779999 | \n",
" 100.004997 | \n",
"
\n",
" \n",
" 90% | \n",
" 271.390991 | \n",
" 3320.144116 | \n",
" 71.685997 | \n",
" 323.749991 | \n",
" 325.509991 | \n",
" 165.528999 | \n",
" 155.119995 | \n",
" 286.537009 | \n",
" 879.536011 | \n",
" 143.327997 | \n",
"
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" \n",
" 99% | \n",
" 441.468004 | \n",
" 3589.468743 | \n",
" 97.592703 | \n",
" 370.564304 | \n",
" 407.781591 | \n",
" 175.211599 | \n",
" 168.477704 | \n",
" 336.495103 | \n",
" 1548.547510 | \n",
" 150.232899 | \n",
"
\n",
" \n",
" max | \n",
" 506.089996 | \n",
" 3731.409912 | \n",
" 107.500000 | \n",
" 382.179993 | \n",
" 416.179993 | \n",
" 179.589996 | \n",
" 171.779999 | \n",
" 343.109985 | \n",
" 2238.750000 | \n",
" 152.789993 | \n",
"
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"metadata": {},
"execution_count": 53
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "oEBw_JyP11y7"
},
"source": [
"Let's first look at how the price of each stock has evolved within give time frame."
]
},
{
"cell_type": "code",
"metadata": {
"id": "RQD270Mc11y8",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 441
},
"outputId": "138109d8-cd39-48f2-af0c-2d61a50c189b"
},
"source": [
"plt.figure(figsize=(14, 7))\n",
"for c in table.columns.values:\n",
" plt.plot(table.index, table[c], lw=3, alpha=0.8,label=c)\n",
"plt.legend(loc='upper left', fontsize=12)\n",
"plt.ylabel('price in $')"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0, 0.5, 'price in $')"
]
},
"metadata": {},
"execution_count": 45
},
{
"output_type": "display_data",
"data": {
"text/plain": [
""
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\n"
},
"metadata": {
"image/png": {
"width": 936,
"height": 407
},
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "SAy6T54Y11y8"
},
"source": [
"Another way to plot this is plotting daily returns (percent change compared to the day before). By plotting daily returns instead of actual prices, we can see the stocks' volatility."
]
},
{
"cell_type": "code",
"metadata": {
"id": "VosK88Ly11y9",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 441
},
"outputId": "9fb55b50-efda-4ce6-8e0d-bf8938e63dae"
},
"source": [
"returns = table.pct_change()\n",
"\n",
"plt.figure(figsize=(14, 7))\n",
"for c in returns.columns.values:\n",
" plt.plot(returns.index, returns[c], lw=3, alpha=0.8,label=c)\n",
"plt.legend(loc='upper right', fontsize=12)\n",
"plt.ylabel('daily returns')"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0, 0.5, 'daily returns')"
]
},
"metadata": {},
"execution_count": 46
},
{
"output_type": "display_data",
"data": {
"text/plain": [
""
],
"image/png": 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},
"metadata": {
"image/png": {
"width": 935,
"height": 407
},
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 300
},
"id": "cn3QMAw3IHMO",
"outputId": "928b2ddf-3da7-4a56-eadc-9432501b042b"
},
"source": [
"returns.describe()"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" AAPL AMZN COP FB HD \\\n",
"count 1571.000000 1571.000000 1571.000000 1571.000000 1571.000000 \n",
"mean 0.000895 0.001234 0.000838 0.000753 0.000672 \n",
"std 0.026354 0.019121 0.026353 0.021755 0.015812 \n",
"min -0.741522 -0.079221 -0.248401 -0.263901 -0.197938 \n",
"25% -0.006677 -0.007519 -0.011754 -0.008322 -0.005609 \n",
"50% 0.000988 0.001390 0.000000 0.001050 0.001029 \n",
"75% 0.010258 0.010611 0.013214 0.011577 0.007966 \n",
"max 0.119808 0.135359 0.252139 0.155214 0.137508 \n",
"\n",
" JNJ JPM MSFT TSLA WMT \n",
"count 1571.000000 1571.000000 1571.000000 1571.000000 1571.000000 \n",
"mean 0.000442 0.000675 0.001256 0.002125 0.000658 \n",
"std 0.012041 0.018497 0.017024 0.041273 0.013474 \n",
"min -0.100379 -0.149649 -0.147390 -0.774862 -0.101832 \n",
"25% -0.004644 -0.007231 -0.005906 -0.014911 -0.005556 \n",
"50% 0.000371 0.000259 0.001036 0.001367 0.000526 \n",
"75% 0.005927 0.008627 0.009669 0.019257 0.006585 \n",
"max 0.079977 0.180125 0.142169 0.198949 0.117085 "
],
"text/html": [
"\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" AAPL | \n",
" AMZN | \n",
" COP | \n",
" FB | \n",
" HD | \n",
" JNJ | \n",
" JPM | \n",
" MSFT | \n",
" TSLA | \n",
" WMT | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
" 1571.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 0.000895 | \n",
" 0.001234 | \n",
" 0.000838 | \n",
" 0.000753 | \n",
" 0.000672 | \n",
" 0.000442 | \n",
" 0.000675 | \n",
" 0.001256 | \n",
" 0.002125 | \n",
" 0.000658 | \n",
"
\n",
" \n",
" std | \n",
" 0.026354 | \n",
" 0.019121 | \n",
" 0.026353 | \n",
" 0.021755 | \n",
" 0.015812 | \n",
" 0.012041 | \n",
" 0.018497 | \n",
" 0.017024 | \n",
" 0.041273 | \n",
" 0.013474 | \n",
"
\n",
" \n",
" min | \n",
" -0.741522 | \n",
" -0.079221 | \n",
" -0.248401 | \n",
" -0.263901 | \n",
" -0.197938 | \n",
" -0.100379 | \n",
" -0.149649 | \n",
" -0.147390 | \n",
" -0.774862 | \n",
" -0.101832 | \n",
"
\n",
" \n",
" 25% | \n",
" -0.006677 | \n",
" -0.007519 | \n",
" -0.011754 | \n",
" -0.008322 | \n",
" -0.005609 | \n",
" -0.004644 | \n",
" -0.007231 | \n",
" -0.005906 | \n",
" -0.014911 | \n",
" -0.005556 | \n",
"
\n",
" \n",
" 50% | \n",
" 0.000988 | \n",
" 0.001390 | \n",
" 0.000000 | \n",
" 0.001050 | \n",
" 0.001029 | \n",
" 0.000371 | \n",
" 0.000259 | \n",
" 0.001036 | \n",
" 0.001367 | \n",
" 0.000526 | \n",
"
\n",
" \n",
" 75% | \n",
" 0.010258 | \n",
" 0.010611 | \n",
" 0.013214 | \n",
" 0.011577 | \n",
" 0.007966 | \n",
" 0.005927 | \n",
" 0.008627 | \n",
" 0.009669 | \n",
" 0.019257 | \n",
" 0.006585 | \n",
"
\n",
" \n",
" max | \n",
" 0.119808 | \n",
" 0.135359 | \n",
" 0.252139 | \n",
" 0.155214 | \n",
" 0.137508 | \n",
" 0.079977 | \n",
" 0.180125 | \n",
" 0.142169 | \n",
" 0.198949 | \n",
" 0.117085 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"
\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"
\n",
" "
]
},
"metadata": {},
"execution_count": 47
}
]
},
{
"cell_type": "markdown",
"source": [
"### Source: https://www.fredasongdrechsler.com/intro-to-python-for-fnce/sp500-constituents"
],
"metadata": {
"id": "Y3Xq4W9Y5-_S"
}
},
{
"cell_type": "markdown",
"source": [
"Reference: Drechsler, Qingyi (Freda) S., 2022, Python Programs for Empirical Finance, https://www.fredasongdrechsler.com"
],
"metadata": {
"id": "MIRjJqjw5-7u"
}
},
{
"cell_type": "markdown",
"source": [
"##### Extending her code, I modified ....."
],
"metadata": {
"id": "iM-B4pDc5-47"
}
},
{
"cell_type": "code",
"source": [
"sp500 = conn.raw_sql(\"\"\"\n",
" select a.*, b.date, b.ret\n",
" from crsp.msp500list as a,\n",
" crsp.msf as b\n",
" where a.permno=b.permno\n",
" and b.date >= a.start and b.date<= a.ending\n",
" and b.date>='01/01/2000'\n",
" order by date;\n",
" \"\"\", date_cols=['start', 'ending', 'date'])"
],
"metadata": {
"id": "4OyBdH5M5_bX"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Add Other Descriptive Variables\n",
"\n",
"mse = conn.raw_sql(\"\"\"\n",
" select comnam, ncusip, namedt, nameendt, \n",
" permno, shrcd, exchcd, hsiccd, ticker\n",
" from crsp.msenames\n",
" \"\"\", date_cols=['namedt', 'nameendt'])\n",
"\n",
"# if nameendt is missing then set to today date\n",
"mse['nameendt']=mse['nameendt'].fillna(pd.to_datetime('today'))\n",
"\n",
"# Merge with SP500 data\n",
"sp500_full = pd.merge(sp500, mse, how = 'left', on = 'permno')\n",
"\n",
"# Impose the date range restrictions\n",
"sp500_full = sp500_full.loc[(sp500_full.date>=sp500_full.namedt) \\\n",
" & (sp500_full.date<=sp500_full.nameendt)]"
],
"metadata": {
"id": "Bl-x7DxL6ccW"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Linking with Compustat through CCM\n",
"\n",
"ccm=conn.raw_sql(\"\"\"\n",
" select gvkey, liid as iid, lpermno as permno, linktype, linkprim, \n",
" linkdt, linkenddt\n",
" from crsp.ccmxpf_linktable\n",
" where substr(linktype,1,1)='L'\n",
" and (linkprim ='C' or linkprim='P')\n",
" \"\"\", date_cols=['linkdt', 'linkenddt'])\n",
"\n",
"# if linkenddt is missing then set to today date\n",
"ccm['linkenddt']=ccm['linkenddt'].fillna(pd.to_datetime('today'))\n",
"\n",
"# Merge the CCM data with S&P500 data\n",
"# First just link by matching PERMNO\n",
"sp500ccm = pd.merge(sp500_full, ccm, how='left', on=['permno'])\n",
"\n",
"# Then set link date bounds\n",
"sp500ccm = sp500ccm.loc[(sp500ccm['date']>=sp500ccm['linkdt'])\\\n",
" &(sp500ccm['date']<=sp500ccm['linkenddt'])]\n",
"\n",
"# Rearrange columns for final output\n",
"\n",
"sp500ccm = sp500ccm.drop(columns=['namedt', 'nameendt', \\\n",
" 'linktype', 'linkprim', 'linkdt', 'linkenddt'])\n",
"sp500ccm = sp500ccm[['date', 'permno', 'comnam', 'ncusip', 'shrcd', 'exchcd', 'hsiccd', 'ticker', \\\n",
" 'gvkey', 'iid', 'start', 'ending', 'ret']]"
],
"metadata": {
"id": "Gd6nuQ826cZO"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"sp500ccm"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 641
},
"id": "WIBGj_Fk6cWr",
"outputId": "34858f77-2cef-4b4b-cbe6-edd950ac8bec"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" date permno comnam ncusip shrcd \\\n",
"0 2000-01-31 40416.0 AVON PRODUCTS INC 05430310 11.0 \n",
"1 2000-01-31 44062.0 SPRINGS INDUSTRIES INC 85178310 11.0 \n",
"2 2000-01-31 26403.0 DISNEY WALT CO 25468710 11.0 \n",
"3 2000-01-31 60628.0 FEDEX CORP 31428X10 11.0 \n",
"4 2000-01-31 69032.0 MORGAN STANLEY DEAN WITTER & CO 61744644 11.0 \n",
"... ... ... ... ... ... \n",
"169638 2022-03-31 17478.0 S & P GLOBAL INC 78409V10 11.0 \n",
"169639 2022-03-31 91152.0 TRANSDIGM GROUP INC 89364110 11.0 \n",
"169641 2022-03-31 24985.0 AMEREN CORP 02360810 11.0 \n",
"169642 2022-03-31 29946.0 BROWN FORMAN CORP 11563720 11.0 \n",
"169643 2022-03-31 17700.0 CERIDIAN H C M HOLDING INC 15677J10 11.0 \n",
"\n",
" exchcd hsiccd ticker gvkey iid start ending ret \n",
"0 1.0 2844.0 AVP 001920 01 1967-05-18 2015-03-20 -0.035985 \n",
"1 1.0 2221.0 SMI 009963 01 1967-06-29 2000-12-11 -0.089202 \n",
"2 1.0 4833.0 DIS 003980 01 1976-07-01 2022-03-31 0.241453 \n",
"3 1.0 4513.0 FDX 004598 01 1980-11-06 2022-03-31 -0.033588 \n",
"4 1.0 6282.0 MWD 012124 01 1995-09-22 2022-03-31 -0.069002 \n",
"... ... ... ... ... .. ... ... ... \n",
"169638 1.0 6282.0 SPGI 007163 01 1957-03-01 2022-03-31 0.091775 \n",
"169639 1.0 3728.0 TDG 148349 01 2016-06-03 2022-03-31 -0.022578 \n",
"169641 1.0 4911.0 AEE 010860 01 1991-09-20 2022-03-31 0.097731 \n",
"169642 1.0 2085.0 BF 002435 01 1982-10-14 2022-03-31 0.030331 \n",
"169643 1.0 7372.0 CDAY 023546 01 2021-09-20 2022-03-31 -0.062406 \n",
"\n",
"[133640 rows x 13 columns]"
],
"text/html": [
"\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" date | \n",
" permno | \n",
" comnam | \n",
" ncusip | \n",
" shrcd | \n",
" exchcd | \n",
" hsiccd | \n",
" ticker | \n",
" gvkey | \n",
" iid | \n",
" start | \n",
" ending | \n",
" ret | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 2000-01-31 | \n",
" 40416.0 | \n",
" AVON PRODUCTS INC | \n",
" 05430310 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 2844.0 | \n",
" AVP | \n",
" 001920 | \n",
" 01 | \n",
" 1967-05-18 | \n",
" 2015-03-20 | \n",
" -0.035985 | \n",
"
\n",
" \n",
" 1 | \n",
" 2000-01-31 | \n",
" 44062.0 | \n",
" SPRINGS INDUSTRIES INC | \n",
" 85178310 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 2221.0 | \n",
" SMI | \n",
" 009963 | \n",
" 01 | \n",
" 1967-06-29 | \n",
" 2000-12-11 | \n",
" -0.089202 | \n",
"
\n",
" \n",
" 2 | \n",
" 2000-01-31 | \n",
" 26403.0 | \n",
" DISNEY WALT CO | \n",
" 25468710 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 4833.0 | \n",
" DIS | \n",
" 003980 | \n",
" 01 | \n",
" 1976-07-01 | \n",
" 2022-03-31 | \n",
" 0.241453 | \n",
"
\n",
" \n",
" 3 | \n",
" 2000-01-31 | \n",
" 60628.0 | \n",
" FEDEX CORP | \n",
" 31428X10 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 4513.0 | \n",
" FDX | \n",
" 004598 | \n",
" 01 | \n",
" 1980-11-06 | \n",
" 2022-03-31 | \n",
" -0.033588 | \n",
"
\n",
" \n",
" 4 | \n",
" 2000-01-31 | \n",
" 69032.0 | \n",
" MORGAN STANLEY DEAN WITTER & CO | \n",
" 61744644 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 6282.0 | \n",
" MWD | \n",
" 012124 | \n",
" 01 | \n",
" 1995-09-22 | \n",
" 2022-03-31 | \n",
" -0.069002 | \n",
"
\n",
" \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
"
\n",
" \n",
" 169638 | \n",
" 2022-03-31 | \n",
" 17478.0 | \n",
" S & P GLOBAL INC | \n",
" 78409V10 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 6282.0 | \n",
" SPGI | \n",
" 007163 | \n",
" 01 | \n",
" 1957-03-01 | \n",
" 2022-03-31 | \n",
" 0.091775 | \n",
"
\n",
" \n",
" 169639 | \n",
" 2022-03-31 | \n",
" 91152.0 | \n",
" TRANSDIGM GROUP INC | \n",
" 89364110 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 3728.0 | \n",
" TDG | \n",
" 148349 | \n",
" 01 | \n",
" 2016-06-03 | \n",
" 2022-03-31 | \n",
" -0.022578 | \n",
"
\n",
" \n",
" 169641 | \n",
" 2022-03-31 | \n",
" 24985.0 | \n",
" AMEREN CORP | \n",
" 02360810 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 4911.0 | \n",
" AEE | \n",
" 010860 | \n",
" 01 | \n",
" 1991-09-20 | \n",
" 2022-03-31 | \n",
" 0.097731 | \n",
"
\n",
" \n",
" 169642 | \n",
" 2022-03-31 | \n",
" 29946.0 | \n",
" BROWN FORMAN CORP | \n",
" 11563720 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 2085.0 | \n",
" BF | \n",
" 002435 | \n",
" 01 | \n",
" 1982-10-14 | \n",
" 2022-03-31 | \n",
" 0.030331 | \n",
"
\n",
" \n",
" 169643 | \n",
" 2022-03-31 | \n",
" 17700.0 | \n",
" CERIDIAN H C M HOLDING INC | \n",
" 15677J10 | \n",
" 11.0 | \n",
" 1.0 | \n",
" 7372.0 | \n",
" CDAY | \n",
" 023546 | \n",
" 01 | \n",
" 2021-09-20 | \n",
" 2022-03-31 | \n",
" -0.062406 | \n",
"
\n",
" \n",
"
\n",
"
133640 rows × 13 columns
\n",
"
\n",
"
\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"
\n",
" "
]
},
"metadata": {},
"execution_count": 52
}
]
},
{
"cell_type": "code",
"source": [
"conn.describe_table('crsp','msi')"
],
"metadata": {
"id": "9sVIZMoF6cUD",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 412
},
"outputId": "290bc21b-a8da-4499-9930-3b205c7a403f"
},
"execution_count": 30,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Approximately 1156 rows in crsp.msi.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" name nullable type\n",
"0 date True DATE\n",
"1 vwretd True DOUBLE_PRECISION\n",
"2 vwretx True DOUBLE_PRECISION\n",
"3 ewretd True DOUBLE_PRECISION\n",
"4 ewretx True DOUBLE_PRECISION\n",
"5 sprtrn True DOUBLE_PRECISION\n",
"6 spindx True DOUBLE_PRECISION\n",
"7 totval True DOUBLE_PRECISION\n",
"8 totcnt True DOUBLE_PRECISION\n",
"9 usdval True DOUBLE_PRECISION\n",
"10 usdcnt True DOUBLE_PRECISION"
],
"text/html": [
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},
"metadata": {},
"execution_count": 30
}
]
},
{
"cell_type": "code",
"source": [
"crsp_msi = conn.raw_sql(\"\"\"\n",
" SELECT *\n",
" FROM crsp.msi \n",
" WHERE date BETWEEN '01/01/2020' AND '12/31/2021'\n",
" \"\"\", date_cols = ['date']) \n",
"\n",
"crsp_msi"
],
"metadata": {
"id": "gjdlLD0A6cRY",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 802
},
"outputId": "bc8f0d5a-f3c2-4fa8-ac05-5b58a2ab6a55"
},
"execution_count": 32,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" date vwretd vwretx ewretd ewretx sprtrn spindx \\\n",
"0 2020-01-31 -0.001728 -0.002849 -0.013334 -0.014200 -0.001628 3225.52 \n",
"1 2020-02-28 -0.077918 -0.079868 -0.069814 -0.071321 -0.084110 2954.22 \n",
"2 2020-03-31 -0.141733 -0.143685 -0.207501 -0.209773 -0.125119 2584.59 \n",
"3 2020-04-30 0.129674 0.128408 0.153867 0.152519 0.126844 2912.43 \n",
"4 2020-05-29 0.053739 0.051688 0.064070 0.062277 0.045282 3044.31 \n",
"5 2020-06-30 0.025299 0.023522 0.057391 0.054855 0.018388 3100.29 \n",
"6 2020-07-31 0.055529 0.054408 0.040737 0.039671 0.055101 3271.12 \n",
"7 2020-08-31 0.068442 0.066798 0.038884 0.037315 0.070065 3500.31 \n",
"8 2020-09-30 -0.035056 -0.036515 -0.027356 -0.029264 -0.039228 3363.00 \n",
"9 2020-10-30 -0.020178 -0.021218 0.000584 -0.000483 -0.027666 3269.96 \n",
"10 2020-11-30 0.123707 0.122019 0.174412 0.172530 0.107546 3621.63 \n",
"11 2020-12-31 0.045048 0.043244 0.072853 0.069761 0.037121 3756.07 \n",
"12 2021-01-29 -0.000631 -0.001611 0.073192 0.072453 -0.011137 3714.24 \n",
"13 2021-02-26 0.029196 0.027888 0.067528 0.066370 0.026091 3811.15 \n",
"14 2021-03-31 0.030573 0.029086 0.012449 0.010736 0.042439 3972.89 \n",
"15 2021-04-30 0.048190 0.047301 0.016612 0.015805 0.052425 4181.17 \n",
"16 2021-05-28 0.007092 0.005786 0.013179 0.011995 0.005487 4204.11 \n",
"17 2021-06-30 0.023422 0.022021 0.021482 0.019631 0.022214 4297.50 \n",
"18 2021-07-30 0.011828 0.010952 -0.033644 -0.034465 0.022748 4395.26 \n",
"19 2021-08-31 0.027147 0.025842 0.018892 0.017615 0.028990 4522.68 \n",
"20 2021-09-30 -0.042243 -0.043531 -0.028472 -0.030084 -0.047569 4307.54 \n",
"21 2021-10-29 0.064657 0.063766 0.026557 0.025517 0.069144 4605.38 \n",
"22 2021-11-30 -0.018347 -0.019703 -0.046540 -0.047915 -0.008334 4567.00 \n",
"23 2021-12-31 0.033345 0.031577 -0.001760 -0.004799 0.043613 4766.18 \n",
"\n",
" totval totcnt usdval usdcnt \n",
"0 4.105976e+10 7267.0 4.111595e+10 7225.0 \n",
"1 3.777752e+10 7253.0 4.104252e+10 7213.0 \n",
"2 3.233352e+10 7226.0 3.774818e+10 7209.0 \n",
"3 3.650329e+10 7224.0 3.223454e+10 7195.0 \n",
"4 3.838482e+10 7217.0 3.642426e+10 7187.0 \n",
"5 3.943612e+10 7244.0 3.836352e+10 7177.0 \n",
"6 4.171822e+10 7273.0 3.941430e+10 7212.0 \n",
"7 4.460940e+10 7286.0 4.170614e+10 7230.0 \n",
"8 4.312178e+10 7336.0 4.460255e+10 7249.0 \n",
"9 4.229818e+10 7397.0 4.302700e+10 7289.0 \n",
"10 4.754201e+10 7457.0 4.219016e+10 7363.0 \n",
"11 4.983956e+10 7525.0 4.750443e+10 7418.0 \n",
"12 4.993087e+10 7606.0 4.977916e+10 7505.0 \n",
"13 5.154680e+10 7692.0 4.991748e+10 7587.0 \n",
"14 5.347375e+10 7838.0 5.151550e+10 7643.0 \n",
"15 5.625838e+10 7978.0 5.340985e+10 7798.0 \n",
"16 5.674877e+10 8085.0 5.622996e+10 7957.0 \n",
"17 5.826003e+10 8186.0 5.670801e+10 8053.0 \n",
"18 5.904011e+10 8310.0 5.816022e+10 8161.0 \n",
"19 6.067961e+10 8367.0 5.899042e+10 8280.0 \n",
"20 5.823152e+10 8473.0 6.065855e+10 8337.0 \n",
"21 6.209768e+10 8548.0 5.818295e+10 8419.0 \n",
"22 6.104353e+10 8644.0 6.204864e+10 8513.0 \n",
"23 6.314345e+10 8750.0 6.095814e+10 8598.0 "
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" totcnt | \n",
" usdval | \n",
" usdcnt | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 2020-01-31 | \n",
" -0.001728 | \n",
" -0.002849 | \n",
" -0.013334 | \n",
" -0.014200 | \n",
" -0.001628 | \n",
" 3225.52 | \n",
" 4.105976e+10 | \n",
" 7267.0 | \n",
" 4.111595e+10 | \n",
" 7225.0 | \n",
"
\n",
" \n",
" 1 | \n",
" 2020-02-28 | \n",
" -0.077918 | \n",
" -0.079868 | \n",
" -0.069814 | \n",
" -0.071321 | \n",
" -0.084110 | \n",
" 2954.22 | \n",
" 3.777752e+10 | \n",
" 7253.0 | \n",
" 4.104252e+10 | \n",
" 7213.0 | \n",
"
\n",
" \n",
" 2 | \n",
" 2020-03-31 | \n",
" -0.141733 | \n",
" -0.143685 | \n",
" -0.207501 | \n",
" -0.209773 | \n",
" -0.125119 | \n",
" 2584.59 | \n",
" 3.233352e+10 | \n",
" 7226.0 | \n",
" 3.774818e+10 | \n",
" 7209.0 | \n",
"
\n",
" \n",
" 3 | \n",
" 2020-04-30 | \n",
" 0.129674 | \n",
" 0.128408 | \n",
" 0.153867 | \n",
" 0.152519 | \n",
" 0.126844 | \n",
" 2912.43 | \n",
" 3.650329e+10 | \n",
" 7224.0 | \n",
" 3.223454e+10 | \n",
" 7195.0 | \n",
"
\n",
" \n",
" 4 | \n",
" 2020-05-29 | \n",
" 0.053739 | \n",
" 0.051688 | \n",
" 0.064070 | \n",
" 0.062277 | \n",
" 0.045282 | \n",
" 3044.31 | \n",
" 3.838482e+10 | \n",
" 7217.0 | \n",
" 3.642426e+10 | \n",
" 7187.0 | \n",
"
\n",
" \n",
" 5 | \n",
" 2020-06-30 | \n",
" 0.025299 | \n",
" 0.023522 | \n",
" 0.057391 | \n",
" 0.054855 | \n",
" 0.018388 | \n",
" 3100.29 | \n",
" 3.943612e+10 | \n",
" 7244.0 | \n",
" 3.836352e+10 | \n",
" 7177.0 | \n",
"
\n",
" \n",
" 6 | \n",
" 2020-07-31 | \n",
" 0.055529 | \n",
" 0.054408 | \n",
" 0.040737 | \n",
" 0.039671 | \n",
" 0.055101 | \n",
" 3271.12 | \n",
" 4.171822e+10 | \n",
" 7273.0 | \n",
" 3.941430e+10 | \n",
" 7212.0 | \n",
"
\n",
" \n",
" 7 | \n",
" 2020-08-31 | \n",
" 0.068442 | \n",
" 0.066798 | \n",
" 0.038884 | \n",
" 0.037315 | \n",
" 0.070065 | \n",
" 3500.31 | \n",
" 4.460940e+10 | \n",
" 7286.0 | \n",
" 4.170614e+10 | \n",
" 7230.0 | \n",
"
\n",
" \n",
" 8 | \n",
" 2020-09-30 | \n",
" -0.035056 | \n",
" -0.036515 | \n",
" -0.027356 | \n",
" -0.029264 | \n",
" -0.039228 | \n",
" 3363.00 | \n",
" 4.312178e+10 | \n",
" 7336.0 | \n",
" 4.460255e+10 | \n",
" 7249.0 | \n",
"
\n",
" \n",
" 9 | \n",
" 2020-10-30 | \n",
" -0.020178 | \n",
" -0.021218 | \n",
" 0.000584 | \n",
" -0.000483 | \n",
" -0.027666 | \n",
" 3269.96 | \n",
" 4.229818e+10 | \n",
" 7397.0 | \n",
" 4.302700e+10 | \n",
" 7289.0 | \n",
"
\n",
" \n",
" 10 | \n",
" 2020-11-30 | \n",
" 0.123707 | \n",
" 0.122019 | \n",
" 0.174412 | \n",
" 0.172530 | \n",
" 0.107546 | \n",
" 3621.63 | \n",
" 4.754201e+10 | \n",
" 7457.0 | \n",
" 4.219016e+10 | \n",
" 7363.0 | \n",
"
\n",
" \n",
" 11 | \n",
" 2020-12-31 | \n",
" 0.045048 | \n",
" 0.043244 | \n",
" 0.072853 | \n",
" 0.069761 | \n",
" 0.037121 | \n",
" 3756.07 | \n",
" 4.983956e+10 | \n",
" 7525.0 | \n",
" 4.750443e+10 | \n",
" 7418.0 | \n",
"
\n",
" \n",
" 12 | \n",
" 2021-01-29 | \n",
" -0.000631 | \n",
" -0.001611 | \n",
" 0.073192 | \n",
" 0.072453 | \n",
" -0.011137 | \n",
" 3714.24 | \n",
" 4.993087e+10 | \n",
" 7606.0 | \n",
" 4.977916e+10 | \n",
" 7505.0 | \n",
"
\n",
" \n",
" 13 | \n",
" 2021-02-26 | \n",
" 0.029196 | \n",
" 0.027888 | \n",
" 0.067528 | \n",
" 0.066370 | \n",
" 0.026091 | \n",
" 3811.15 | \n",
" 5.154680e+10 | \n",
" 7692.0 | \n",
" 4.991748e+10 | \n",
" 7587.0 | \n",
"
\n",
" \n",
" 14 | \n",
" 2021-03-31 | \n",
" 0.030573 | \n",
" 0.029086 | \n",
" 0.012449 | \n",
" 0.010736 | \n",
" 0.042439 | \n",
" 3972.89 | \n",
" 5.347375e+10 | \n",
" 7838.0 | \n",
" 5.151550e+10 | \n",
" 7643.0 | \n",
"
\n",
" \n",
" 15 | \n",
" 2021-04-30 | \n",
" 0.048190 | \n",
" 0.047301 | \n",
" 0.016612 | \n",
" 0.015805 | \n",
" 0.052425 | \n",
" 4181.17 | \n",
" 5.625838e+10 | \n",
" 7978.0 | \n",
" 5.340985e+10 | \n",
" 7798.0 | \n",
"
\n",
" \n",
" 16 | \n",
" 2021-05-28 | \n",
" 0.007092 | \n",
" 0.005786 | \n",
" 0.013179 | \n",
" 0.011995 | \n",
" 0.005487 | \n",
" 4204.11 | \n",
" 5.674877e+10 | \n",
" 8085.0 | \n",
" 5.622996e+10 | \n",
" 7957.0 | \n",
"
\n",
" \n",
" 17 | \n",
" 2021-06-30 | \n",
" 0.023422 | \n",
" 0.022021 | \n",
" 0.021482 | \n",
" 0.019631 | \n",
" 0.022214 | \n",
" 4297.50 | \n",
" 5.826003e+10 | \n",
" 8186.0 | \n",
" 5.670801e+10 | \n",
" 8053.0 | \n",
"
\n",
" \n",
" 18 | \n",
" 2021-07-30 | \n",
" 0.011828 | \n",
" 0.010952 | \n",
" -0.033644 | \n",
" -0.034465 | \n",
" 0.022748 | \n",
" 4395.26 | \n",
" 5.904011e+10 | \n",
" 8310.0 | \n",
" 5.816022e+10 | \n",
" 8161.0 | \n",
"
\n",
" \n",
" 19 | \n",
" 2021-08-31 | \n",
" 0.027147 | \n",
" 0.025842 | \n",
" 0.018892 | \n",
" 0.017615 | \n",
" 0.028990 | \n",
" 4522.68 | \n",
" 6.067961e+10 | \n",
" 8367.0 | \n",
" 5.899042e+10 | \n",
" 8280.0 | \n",
"
\n",
" \n",
" 20 | \n",
" 2021-09-30 | \n",
" -0.042243 | \n",
" -0.043531 | \n",
" -0.028472 | \n",
" -0.030084 | \n",
" -0.047569 | \n",
" 4307.54 | \n",
" 5.823152e+10 | \n",
" 8473.0 | \n",
" 6.065855e+10 | \n",
" 8337.0 | \n",
"
\n",
" \n",
" 21 | \n",
" 2021-10-29 | \n",
" 0.064657 | \n",
" 0.063766 | \n",
" 0.026557 | \n",
" 0.025517 | \n",
" 0.069144 | \n",
" 4605.38 | \n",
" 6.209768e+10 | \n",
" 8548.0 | \n",
" 5.818295e+10 | \n",
" 8419.0 | \n",
"
\n",
" \n",
" 22 | \n",
" 2021-11-30 | \n",
" -0.018347 | \n",
" -0.019703 | \n",
" -0.046540 | \n",
" -0.047915 | \n",
" -0.008334 | \n",
" 4567.00 | \n",
" 6.104353e+10 | \n",
" 8644.0 | \n",
" 6.204864e+10 | \n",
" 8513.0 | \n",
"
\n",
" \n",
" 23 | \n",
" 2021-12-31 | \n",
" 0.033345 | \n",
" 0.031577 | \n",
" -0.001760 | \n",
" -0.004799 | \n",
" 0.043613 | \n",
" 4766.18 | \n",
" 6.314345e+10 | \n",
" 8750.0 | \n",
" 6.095814e+10 | \n",
" 8598.0 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"
\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"
\n",
" "
]
},
"metadata": {},
"execution_count": 32
}
]
},
{
"cell_type": "code",
"source": [
""
],
"metadata": {
"id": "ogljyfhn6cOu"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
""
],
"metadata": {
"id": "Y1LBTfmP6cIe"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
""
],
"metadata": {
"id": "WAlaGmJj6cC0"
},
"execution_count": null,
"outputs": []
}
]
}