Aula_6.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "import bql\n",
    "bq = bql.Service()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>PX_LAST(dates=RANGE(-5D,-3D))</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2020-08-12</td>\n",
       "      <td>USD</td>\n",
       "      <td>1554.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2020-08-13</td>\n",
       "      <td>USD</td>\n",
       "      <td>1621.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2020-08-14</td>\n",
       "      <td>USD</td>\n",
       "      <td>1650.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX US Equity</th>\n",
       "      <td>2020-08-12</td>\n",
       "      <td>USD</td>\n",
       "      <td>475.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX US Equity</th>\n",
       "      <td>2020-08-13</td>\n",
       "      <td>USD</td>\n",
       "      <td>481.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX US Equity</th>\n",
       "      <td>2020-08-14</td>\n",
       "      <td>USD</td>\n",
       "      <td>482.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBER US Equity</th>\n",
       "      <td>2020-08-12</td>\n",
       "      <td>USD</td>\n",
       "      <td>30.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBER US Equity</th>\n",
       "      <td>2020-08-13</td>\n",
       "      <td>USD</td>\n",
       "      <td>30.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBER US Equity</th>\n",
       "      <td>2020-08-14</td>\n",
       "      <td>USD</td>\n",
       "      <td>29.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     DATE CURRENCY  PX_LAST(dates=RANGE(-5D,-3D))\n",
       "ID                                                               \n",
       "TSLA US Equity 2020-08-12      USD                        1554.76\n",
       "TSLA US Equity 2020-08-13      USD                        1621.00\n",
       "TSLA US Equity 2020-08-14      USD                        1650.71\n",
       "NFLX US Equity 2020-08-12      USD                         475.47\n",
       "NFLX US Equity 2020-08-13      USD                         481.33\n",
       "NFLX US Equity 2020-08-14      USD                         482.68\n",
       "UBER US Equity 2020-08-12      USD                          30.84\n",
       "UBER US Equity 2020-08-13      USD                          30.46\n",
       "UBER US Equity 2020-08-14      USD                          29.99"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#------------#\n",
    "#  Grouping  #\n",
    "#------------#\n",
    "\n",
    "# Example 1: \n",
    "# Average + Last Price + Date range\n",
    "\n",
    "# BQL String:\n",
    "# get(avg(PX_LAST(dates=range(-10D, 0D)))) \n",
    "# for(['TSLA US Equity', 'NFLX US Equity', 'UBER US Equity'])\n",
    "\n",
    "# BQL Object Model:\n",
    "bql_item = (bq.data.px_last(dates=bq.func.range('-5D', '-3D')))\n",
    "bql_universe = ['TSLA US Equity', 'NFLX US Equity', 'UBER US Equity']\n",
    "bql_request = bql.Request(bql_universe, bql_item)\n",
    "bql_response = bq.execute(bql_request)\n",
    "df = bql_response[0].df()\n",
    "df"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "- By default, each security, country or other entity in a universe is surrounded by a container that isolates the entity's data from the data of other universe members.\n",
    "\n",
    "- This container is known as the identifier boundary.\n",
    "\n",
    "- Because you spcified a date range of three days, each security returns a \"stack\" of three prices. You can visualize each stack as a separate boundary that belongs to each security.\n",
    "\n",
    "- Calculating one average value for each set of three prices ... "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>AVG(PX_LAST(dates=RANGE(-5D,-2D)))</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2020-08-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>1608.823333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX US Equity</th>\n",
       "      <td>2020-08-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>479.826667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBER US Equity</th>\n",
       "      <td>2020-08-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>30.430000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     DATE CURRENCY  AVG(PX_LAST(dates=RANGE(-5D,-2D)))\n",
       "ID                                                                    \n",
       "TSLA US Equity 2020-08-15      USD                         1608.823333\n",
       "NFLX US Equity 2020-08-15      USD                          479.826667\n",
       "UBER US Equity 2020-08-15      USD                           30.430000"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example 1: \n",
    "# Average + Last Price + Date range\n",
    "\n",
    "# BQL String:\n",
    "# get(avg(PX_LAST(dates=range(-10D, 0D)))) \n",
    "# for(['TSLA US Equity', 'NFLX US Equity', 'UBER US Equity'])\n",
    "\n",
    "# BQL Object Model:\n",
    "bql_item = bq.func.avg(bq.data.px_last(dates=bq.func.range('-5D', '-2D')))\n",
    "bql_universe = ['TSLA US Equity', 'NFLX US Equity', 'UBER US Equity']\n",
    "bql_request = bql.Request(bql_universe, bql_item)\n",
    "bql_response = bq.execute(bql_request)\n",
    "df = bql_response[0].df()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>REVISION_DATE</th>\n",
       "      <th>PERIOD_END_DATE</th>\n",
       "      <th>AS_OF_DATE</th>\n",
       "      <th>ORIG_IDS</th>\n",
       "      <th>COUNTRY_FULL_NAME()</th>\n",
       "      <th>MEDIAN(GROUP(PROF_MARGIN(),by=COUNTRY_FULL_NAME()))</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AUSTRALIA</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>2020-08-17</td>\n",
       "      <td>BHP LN Equity</td>\n",
       "      <td>AUSTRALIA</td>\n",
       "      <td>20.527923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUSTRIA</th>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>2020-08-17</td>\n",
       "      <td>None</td>\n",
       "      <td>AUSTRIA</td>\n",
       "      <td>13.556570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BELGIUM</th>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>2020-08-17</td>\n",
       "      <td>None</td>\n",
       "      <td>BELGIUM</td>\n",
       "      <td>10.363741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BERMUDA</th>\n",
       "      <td>2020-08-03</td>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>2020-08-17</td>\n",
       "      <td>HSX LN Equity</td>\n",
       "      <td>BERMUDA</td>\n",
       "      <td>-7.809186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRITAIN</th>\n",
       "      <td>2020-06-15</td>\n",
       "      <td>2020-03-31</td>\n",
       "      <td>2020-08-17</td>\n",
       "      <td>None</td>\n",
       "      <td>BRITAIN</td>\n",
       "      <td>8.364807</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          REVISION_DATE PERIOD_END_DATE AS_OF_DATE       ORIG_IDS  \\\n",
       "ID                                                                  \n",
       "AUSTRALIA    2020-02-25      2019-12-31 2020-08-17  BHP LN Equity   \n",
       "AUSTRIA      2020-07-29      2020-06-30 2020-08-17           None   \n",
       "BELGIUM      2020-07-29      2020-06-30 2020-08-17           None   \n",
       "BERMUDA      2020-08-03      2020-06-30 2020-08-17  HSX LN Equity   \n",
       "BRITAIN      2020-06-15      2020-03-31 2020-08-17           None   \n",
       "\n",
       "          COUNTRY_FULL_NAME()  \\\n",
       "ID                              \n",
       "AUSTRALIA           AUSTRALIA   \n",
       "AUSTRIA               AUSTRIA   \n",
       "BELGIUM               BELGIUM   \n",
       "BERMUDA               BERMUDA   \n",
       "BRITAIN               BRITAIN   \n",
       "\n",
       "           MEDIAN(GROUP(PROF_MARGIN(),by=COUNTRY_FULL_NAME()))  \n",
       "ID                                                              \n",
       "AUSTRALIA                                          20.527923    \n",
       "AUSTRIA                                            13.556570    \n",
       "BELGIUM                                            10.363741    \n",
       "BERMUDA                                            -7.809186    \n",
       "BRITAIN                                             8.364807    "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example 2: Grouping methods ... \n",
    "# Group members of the Euro Stoxx 50 by country and find the median profit margin per country:\n",
    "\n",
    "# BQL String:\n",
    "# get(median(group(PROF_MARGIN(), by=COUNTRY_FULL_NAME()))) \n",
    "# for(members('SXXP Index'))\n",
    "\n",
    "# BQL Object Model:\n",
    "bql_item = bq.func.median(bq.func.group(bq.data.prof_margin(), by=bq.data.country_full_name()))\n",
    "bql_universe = bq.univ.members('SXXP Index')\n",
    "bql_request = bql.Request(bql_universe, bql_item)\n",
    "bql_response = bq.execute(bql_request)\n",
    "df = bql_response[0].df()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAY_TO_DAY_TOT_RETURN_GROSS_DVDS(dates=RANGE(-5D,-3D))/GROUPAVG(DAY_TO_DAY_TOT_RETURN_GROSS_DVDS(dates=RANGE(-5D,-3D)))</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ENBR3 BS Equity</th>\n",
       "      <td>2020-08-12</td>\n",
       "      <td>1.089128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENBR3 BS Equity</th>\n",
       "      <td>2020-08-13</td>\n",
       "      <td>2.919133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENBR3 BS Equity</th>\n",
       "      <td>2020-08-14</td>\n",
       "      <td>-1.972885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HGTX3 BS Equity</th>\n",
       "      <td>2020-08-12</td>\n",
       "      <td>12.794549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HGTX3 BS Equity</th>\n",
       "      <td>2020-08-13</td>\n",
       "      <td>-0.723640</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      DATE  \\\n",
       "ID                           \n",
       "ENBR3 BS Equity 2020-08-12   \n",
       "ENBR3 BS Equity 2020-08-13   \n",
       "ENBR3 BS Equity 2020-08-14   \n",
       "HGTX3 BS Equity 2020-08-12   \n",
       "HGTX3 BS Equity 2020-08-13   \n",
       "\n",
       "                 DAY_TO_DAY_TOT_RETURN_GROSS_DVDS(dates=RANGE(-5D,-3D))/GROUPAVG(DAY_TO_DAY_TOT_RETURN_GROSS_DVDS(dates=RANGE(-5D,-3D)))  \n",
       "ID                                                                                                                                        \n",
       "ENBR3 BS Equity                                           1.089128                                                                        \n",
       "ENBR3 BS Equity                                           2.919133                                                                        \n",
       "ENBR3 BS Equity                                          -1.972885                                                                        \n",
       "HGTX3 BS Equity                                          12.794549                                                                        \n",
       "HGTX3 BS Equity                                          -0.723640                                                                        "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example 3:\n",
    "# Create a ratio that compares today’s total return from each member of the Euro Stoxx 50 Index to the average total return across all members:\n",
    "\n",
    "# BQL String:\n",
    "# get((DAY_TO_DAY_TOT_RETURN_GROSS_DVDS(dates=range(-6D, -3D))/GROUPAVG(DAY_TO_DAY_TOT_RETURN_GROSS_DVDS(dates=range(-6D, 0D))))) \n",
    "# for(members('IBOV Index'))\n",
    "\n",
    "# BQL Object Model:\n",
    "bql_item = (bq.data.day_to_day_tot_return_gross_dvds(dates=bq.func.range('-5D', '-3D')) / bq.func.groupavg(bq.data.day_to_day_tot_return_gross_dvds(dates=bq.func.range('-5D', '-3D'))))\n",
    "bql_universe = bq.univ.members('IBOV Index')\n",
    "bql_request = bql.Request(bql_universe, bql_item)\n",
    "bql_response = bq.execute(bql_request)\n",
    "df = bql_response[0].df()\n",
    "df.head()"
   ]
  }
 ],
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