examples/use-cases/risk-and-performance/Backtesting with LUSID derived portfolios.ipynb

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   "source": [
    "from lusidtools.jupyter_tools import toggle_code\n",
    "\n",
    "\"\"\"Backtesting with derived portfolios\n",
    "\n",
    "Shows how to use a derived portfolio to test different trading strategies.\n",
    "\n",
    "Attributes\n",
    "----------\n",
    "cocoon\n",
    "instruments\n",
    "holdings\n",
    "quotes\n",
    "aggregation\n",
    "derived portfolios\n",
    "\"\"\"\n",
    "\n",
    "toggle_code(\"Toggle Docstring\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Backtesting strategy selection on PnL \n",
    "\n",
    "The aim of this notebook is to show strategy backtesting using LUSID's derived portfolio functionality. In this notebook we will compare the performance of a US technology sector equity portfolio under two seperate scenarios. In the first scenario, the portfolio will be weighted towards \"Google\". In the second scenario, the portfolio will be weighted towards \"Netflix\". We will then compare PnL results. \n",
    "\n",
    "From a LUSID perspective, we will complete the following:\n",
    "\n",
    "(1) Setup the LUSID environment. <br>\n",
    "\n",
    "(2) Create our first portfolio. <br>\n",
    "\n",
    "(3) Load our FANG (Facebook, Apple, Netflix, Google) instrument master. <br>\n",
    "\n",
    "(4) Upsert initial holdings - the portfolio will have a 55% of NAV weighting to \"Google\". <br>\n",
    "\n",
    "(5) Upsert quotes to cover a 9 month period (1 Jan 2019 to 30 Sep 2019). <br>\n",
    "\n",
    "(6) Run aggregration on Google heavy portfolio. <br>\n",
    "\n",
    "(7) Plot the results of this portfolio on a graph. <br>\n",
    "\n",
    "(8) Did we make the correct allocation decision? By using LUSID's derived portfolios, we can wind back time and check performance of the portfolio if we allocated 55% to Netflix instead of Google. <br>\n",
    "\n",
    "(9) Plot and compare time series. <br>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 1: Import packages and initialize LUSID environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LUSID Environment Initialised\n",
      "LUSID SDK Version:  0.6.10069.0\n"
     ]
    }
   ],
   "source": [
    "# Import LUSID\n",
    "import lusid\n",
    "import lusid.models as models\n",
    "\n",
    "# import lusid_sample_data as import_data\n",
    "from lusidtools.cocoon import cocoon\n",
    "from lusidtools.cocoon import instruments as cocoon_instruments\n",
    "from lusidjam import RefreshingToken\n",
    "\n",
    "# Import Libraries\n",
    "import pprint\n",
    "from datetime import datetime, timedelta, time, date\n",
    "import pytz\n",
    "import uuid\n",
    "import os\n",
    "import printer as prettyprint\n",
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import lusid_sample_data as import_data\n",
    "import json\n",
    "\n",
    "# Authenticate our user and create our API client\n",
    "secrets_path = os.getenv(\"FBN_SECRETS_PATH\")\n",
    "\n",
    "api_factory = lusid.utilities.ApiClientFactory(\n",
    "    token=RefreshingToken(),\n",
    "    api_secrets_filename=secrets_path,\n",
    "    app_name=\"LusidJupyterNotebook\",\n",
    ")\n",
    "\n",
    "print(\"LUSID Environment Initialised\")\n",
    "print(\n",
    "    \"LUSID SDK Version: \",\n",
    "    api_factory.build(lusid.api.ApplicationMetadataApi)\n",
    "    .get_lusid_versions()\n",
    "    .build_version,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import ploting libraries and configuration\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Use line magic function to enable matplotlib to work interactively with iPython\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# Set style to fivethirtyeight to create clean and clear looking graphs\n",
    "\n",
    "plt.style.use(\"fivethirtyeight\")\n",
    "\n",
    "# Define a dictionary containing default plotting configurations\n",
    "\n",
    "params = {\n",
    "    \"legend.fontsize\": \"small\",\n",
    "    \"figure.figsize\": (12, 4.5),\n",
    "    \"axes.labelsize\": \"small\",\n",
    "    \"axes.titlesize\": \"medium\",\n",
    "    \"xtick.labelsize\": \"small\",\n",
    "    \"ytick.labelsize\": \"small\",\n",
    "}\n",
    "\n",
    "plt.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define two portfolios:<br>\n",
    "\n",
    "(1) portfolioA will be used to test performance when 55% of the portfolio is weighted to Google. <br>\n",
    "\n",
    "(2) portfolioB will be used to test performance when 55% of the portfolio is weighted to Netflix. <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "portfolioA = \"US_TECH1\"\n",
    "portfolioB = \"US_TECH2\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define a scope.\n",
    "\n",
    "A scope in LUSID is a partioning of data. See our support page for [Scopes](https://support.lusid.com/what-is-a-scope-in-lusid-and-how-is-it-used) for more details:\n",
    "\n",
    "\n",
    "\n",
    "In this notebook, we will use the scope to partition portfolios, instruments, quotes and holdings data.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "scope = \"techStrategy\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 2: Create the first portfolio\n",
    "\n",
    "To get started, we first need to load a portfolio. The portfolio will be used to store holdings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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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>portfolio_ticker</th>\n",
       "      <th>portfolio_name</th>\n",
       "      <th>base_currency</th>\n",
       "      <th>created</th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>US_TECH1</td>\n",
       "      <td>Portfolio for tech FANG strategy</td>\n",
       "      <td>USD</td>\n",
       "      <td>2018-01-01T14:39:32Z</td>\n",
       "      <td>UK</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  portfolio_ticker                    portfolio_name base_currency  \\\n",
       "0         US_TECH1  Portfolio for tech FANG strategy           USD   \n",
       "\n",
       "                created location  \n",
       "0  2018-01-01T14:39:32Z       UK  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load a CSV file of portfolio data into a pandas DataFrame\n",
    "\n",
    "portfolio_csv = r\"data/backtesting/backtesting_portfolios.csv\"\n",
    "df_portfolios_csv = pd.read_csv(portfolio_csv)\n",
    "df_portfolios_csv[\"portfolio_ticker\"] = portfolioA\n",
    "df_portfolios_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a dictionary of mappings\n",
    "# The dictionary keys are the names for values in LUSID\n",
    "# The dictionary values are the names in our CSV column headers\n",
    "\n",
    "mapping_required = {\n",
    "    \"display_name\": \"portfolio_name\",\n",
    "    \"code\": \"portfolio_ticker\",\n",
    "    \"base_currency\": \"base_currency\",\n",
    "}\n",
    "\n",
    "\n",
    "mapping_optional = {\"description\": \"portfolio_name\", \"created\": \"created\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the load_from_data_frame method from LUSID's Python cocoon package to upload the portfolio\n",
    "\n",
    "response = cocoon.load_from_data_frame(\n",
    "    api_factory=api_factory,\n",
    "    scope=scope,\n",
    "    data_frame=df_portfolios_csv,\n",
    "    property_columns=[\"location\"],\n",
    "    mapping_required=mapping_required,\n",
    "    mapping_optional=mapping_optional,\n",
    "    file_type=\"portfolios\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 3: Upsert our instrument master\n",
    "\n",
    "Next we upsert some instruments into LUSID. Simliar to the above, the instruments will be created from a CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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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>name</th>\n",
       "      <th>Ticker</th>\n",
       "      <th>ClientInternal</th>\n",
       "      <th>QuotePermId</th>\n",
       "      <th>MarketSector</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alphabet</td>\n",
       "      <td>GOOG</td>\n",
       "      <td>EQ38475943</td>\n",
       "      <td>1-8590928320</td>\n",
       "      <td>Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Facebook</td>\n",
       "      <td>FB</td>\n",
       "      <td>EQ26845198</td>\n",
       "      <td>1-8590932301</td>\n",
       "      <td>Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Netflix</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>EQ36852475</td>\n",
       "      <td>1-8590930194</td>\n",
       "      <td>Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>EQ38451369</td>\n",
       "      <td>1-4295989835</td>\n",
       "      <td>Equity</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       name Ticker ClientInternal   QuotePermId MarketSector\n",
       "0  Alphabet   GOOG     EQ38475943  1-8590928320       Equity\n",
       "1  Facebook     FB     EQ26845198  1-8590932301       Equity\n",
       "2   Netflix   NFLX     EQ36852475  1-8590930194       Equity\n",
       "3     Apple   AAPL     EQ38451369  1-4295989835       Equity"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load an instruments file from CSV\n",
    "# The details will be stored in a Pandas DataFrame\n",
    "\n",
    "instruments_csv = r\"data/backtesting/backtesting_instruments.csv\"\n",
    "df_instruments = pd.read_csv(instruments_csv)\n",
    "df_instruments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create dictionaries of mappings\n",
    "\n",
    "mapping_required = {\n",
    "    \"name\": \"name\",\n",
    "}\n",
    "\n",
    "# This time, we also need to tell LUSID about our unique identifiers\n",
    "# All instruments in LUSID need a unique identifier\n",
    "\n",
    "identifiers = {\"ClientInternal\": \"ClientInternal\", \"Ticker\": \"Ticker\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Call cocoon again\n",
    "# But this time we use a file_type of \"instruments\" to call the instruments endpoint\n",
    "\n",
    "response = cocoon.load_from_data_frame(\n",
    "    api_factory=api_factory,\n",
    "    scope=scope,\n",
    "    data_frame=df_instruments,\n",
    "    mapping_required=mapping_required,\n",
    "    mapping_optional={},\n",
    "    file_type=\"instruments\",\n",
    "    identifier_mapping=identifiers,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 4: Create initial holdings for 1 Jan 2019\n",
    "\n",
    "Now that we have a portfolio and some instruments, we want to create holdings in that portfolio using those instruments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>portfolio_code</th>\n",
       "      <th>instrument_name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>price</th>\n",
       "      <th>currency</th>\n",
       "      <th>QuotePermId</th>\n",
       "      <th>ClientInternal</th>\n",
       "      <th>effective_at</th>\n",
       "      <th>market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>US_TECH1</td>\n",
       "      <td>Alphabet</td>\n",
       "      <td>52632</td>\n",
       "      <td>1045.00</td>\n",
       "      <td>USD</td>\n",
       "      <td>1-8590928320</td>\n",
       "      <td>EQ38475943</td>\n",
       "      <td>2019-01-01T00:00:00Z</td>\n",
       "      <td>55000440.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>US_TECH1</td>\n",
       "      <td>Apple</td>\n",
       "      <td>94985</td>\n",
       "      <td>157.92</td>\n",
       "      <td>USD</td>\n",
       "      <td>1-4295989835</td>\n",
       "      <td>EQ38451369</td>\n",
       "      <td>2019-01-01T00:00:00Z</td>\n",
       "      <td>15000031.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>US_TECH1</td>\n",
       "      <td>Netflix</td>\n",
       "      <td>56041</td>\n",
       "      <td>267.66</td>\n",
       "      <td>USD</td>\n",
       "      <td>1-8590930194</td>\n",
       "      <td>EQ36852475</td>\n",
       "      <td>2019-01-01T00:00:00Z</td>\n",
       "      <td>14999934.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>US_TECH1</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>110554</td>\n",
       "      <td>135.68</td>\n",
       "      <td>USD</td>\n",
       "      <td>1-8590932301</td>\n",
       "      <td>EQ26845198</td>\n",
       "      <td>2019-01-01T00:00:00Z</td>\n",
       "      <td>14999966.72</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  portfolio_code instrument_name  quantity   price currency   QuotePermId  \\\n",
       "0       US_TECH1        Alphabet     52632 1045.00      USD  1-8590928320   \n",
       "1       US_TECH1           Apple     94985  157.92      USD  1-4295989835   \n",
       "2       US_TECH1         Netflix     56041  267.66      USD  1-8590930194   \n",
       "3       US_TECH1        Facebook    110554  135.68      USD  1-8590932301   \n",
       "\n",
       "  ClientInternal          effective_at  market_value  \n",
       "0     EQ38475943  2019-01-01T00:00:00Z   55000440.00  \n",
       "1     EQ38451369  2019-01-01T00:00:00Z   15000031.20  \n",
       "2     EQ36852475  2019-01-01T00:00:00Z   14999934.06  \n",
       "3     EQ26845198  2019-01-01T00:00:00Z   14999966.72  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load holdings into DataFrame\n",
    "\n",
    "holdings_csv = r\"data/backtesting/backtesting_holdings.csv\"\n",
    "df_holdings = pd.read_csv(holdings_csv)\n",
    "df_holdings[\"effective_at\"] = \"2019-01-01T00:00:00Z\"\n",
    "df_holdings[\"portfolio_code\"] = portfolioA\n",
    "df_holdings[\"market_value\"] = df_holdings[\"quantity\"] * df_holdings[\"price\"]\n",
    "df_holdings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pie_plot():\n",
    "    plt.style.use(\"fivethirtyeight\")\n",
    "    pie_plot = df_holdings.plot.pie(\n",
    "        y=\"market_value\",\n",
    "        labels=df_holdings[\"instrument_name\"].values,\n",
    "        figsize=(11, 11),\n",
    "        title=f\"Allocation of portfolio {portfolioA} to FANG stocks by % of NAV\",\n",
    "        explode=(0.025, 0, 0, 0),\n",
    "        startangle=140,\n",
    "        autopct=\"%1.1f%%\",\n",
    "        textprops={\"fontsize\": 16},\n",
    "    )\n",
    "\n",
    "    pie_plot.set_ylabel(\"\")\n",
    "    pie_plot.legend(loc=4, prop={\"size\": 14})\n",
    "    pie_plot.set_title(\n",
    "        f\"Allocation of portfolio {portfolioA} to FANG stocks by % of NAV\", fontsize=20\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x1100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pie_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Provide mappings (as above)\n",
    "# Adding a $ prefix to the dict value will hardcode that value into the LUSID call\n",
    "# In the example below, we only want to set holdings, we are not concerned about the cash impact.\n",
    "# Therefore we set the portfolio_cost and cost.amount to 0\n",
    "\n",
    "mapping_required = {\n",
    "    \"name\": \"instrument_name\",\n",
    "    \"effective_at\": \"effective_at\",\n",
    "    \"code\": \"portfolio_code\",\n",
    "    \"tax_lots.units\": \"quantity\",\n",
    "    \"tax_lots.price\": \"price\",\n",
    "    \"tax_lots.portfolio_cost\": \"market_value\",\n",
    "    \"tax_lots.cost.currency\": \"currency\",\n",
    "    \"tax_lots.cost.amount\": \"market_value\",\n",
    "}\n",
    "\n",
    "identifiers = {\n",
    "    \"ClientInternal\": \"ClientInternal\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run the load_from_data_frame cocoon method again\n",
    "# This time we upload holdings\n",
    "\n",
    "response = cocoon.load_from_data_frame(\n",
    "    api_factory=api_factory,\n",
    "    scope=scope,\n",
    "    data_frame=df_holdings,\n",
    "    mapping_required=mapping_required,\n",
    "    mapping_optional={},\n",
    "    file_type=\"holdings\",\n",
    "    identifier_mapping=identifiers,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 5: Upload quotes\n",
    "\n",
    "Next we need some quotes, to produce our valuations. In this example, the quotes will be loaded from an external CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>quote_date</th>\n",
       "      <th>client_internal</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-02T00:00:00Z</td>\n",
       "      <td>EQ38475943</td>\n",
       "      <td>1045.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-03T00:00:00Z</td>\n",
       "      <td>EQ38475943</td>\n",
       "      <td>1016.06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             quote_date client_internal   price\n",
       "0  2019-01-02T00:00:00Z      EQ38475943 1045.85\n",
       "1  2019-01-03T00:00:00Z      EQ38475943 1016.06"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quotes_csv = r\"data/backtesting/backtesting_quotes.csv\"\n",
    "df_quotes = pd.read_csv(quotes_csv)\n",
    "df_quotes.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>quote_date</th>\n",
       "      <th>client_internal</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-02T00:00:00Z</td>\n",
       "      <td>EQ38475943</td>\n",
       "      <td>1045.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>2019-01-02T00:00:00Z</td>\n",
       "      <td>EQ38451369</td>\n",
       "      <td>155.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>2019-01-02T00:00:00Z</td>\n",
       "      <td>EQ36852475</td>\n",
       "      <td>267.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>2019-01-02T00:00:00Z</td>\n",
       "      <td>EQ26845198</td>\n",
       "      <td>135.68</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               quote_date client_internal   price\n",
       "0    2019-01-02T00:00:00Z      EQ38475943 1045.85\n",
       "187  2019-01-02T00:00:00Z      EQ38451369  155.58\n",
       "374  2019-01-02T00:00:00Z      EQ36852475  267.66\n",
       "561  2019-01-02T00:00:00Z      EQ26845198  135.68"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_quotes.loc[df_quotes[\"quote_date\"] == \"2019-01-02T00:00:00Z\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now have the quotes in a DataFrame, which is great. However we also want to provide the LUID. To resolve this problem, we take our client_internal ID and search the APIs for a LUID which is appended to each row in the DataFrame. <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_luid_id(data_frame):\n",
    "\n",
    "    client_ids = pd.DataFrame(\n",
    "        list(df_holdings[\"ClientInternal\"].unique()), columns=[\"client_internal\"]\n",
    "    )\n",
    "    client_ids[\"LUID\"] = client_ids[\"client_internal\"].apply(\n",
    "        lambda x: api_factory.build(lusid.api.InstrumentsApi)\n",
    "        .get_instrument(identifier_type=\"ClientInternal\", identifier=x)\n",
    "        .lusid_instrument_id\n",
    "    )\n",
    "\n",
    "    client_ids = client_ids.set_index(\"client_internal\")\n",
    "\n",
    "    data_frame[\"LUID\"] = data_frame[\"client_internal\"].apply(\n",
    "        lambda x: client_ids.loc[x][\"LUID\"]\n",
    "    )\n",
    "\n",
    "    return data_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_quotes = add_luid_id(df_quotes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define our mapping dictionaries\n",
    "\n",
    "mapping_required = {\n",
    "    \"quote_id.quote_series_id.instrument_id_type\": \"$LusidInstrumentId\",\n",
    "    \"quote_id.effective_at\": \"quote_date\",\n",
    "    \"quote_id.quote_series_id.provider\": \"$DataScope\",\n",
    "    \"quote_id.quote_series_id.field\": \"$mid\",\n",
    "    \"quote_id.quote_series_id.quote_type\": \"$Price\",\n",
    "    \"quote_id.quote_series_id.instrument_id\": \"LUID\",\n",
    "    \"metric_value.unit\": \"$USD\",\n",
    "    \"metric_value.value\": \"price\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\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>local_vars_configuration</th>\n",
       "      <th>_lineage</th>\n",
       "      <th>_cut_label</th>\n",
       "      <th>_uploaded_by</th>\n",
       "      <th>_as_at</th>\n",
       "      <th>_scale_factor</th>\n",
       "      <th>discriminator</th>\n",
       "      <th>_provider</th>\n",
       "      <th>_price_source</th>\n",
       "      <th>_instrument_id</th>\n",
       "      <th>_instrument_id_type</th>\n",
       "      <th>_quote_type</th>\n",
       "      <th>_field</th>\n",
       "      <th>_value</th>\n",
       "      <th>_unit</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1045.85</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1016.06</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1070.71</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1068.39</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1076.28</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1074.66</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1070.33</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1057.19</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1044.69</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>&lt;lusid.configuration.Configuration object at 0...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>00ubsbczibzRxZJzM2p7</td>\n",
       "      <td>2022-10-03 10:52:12.723909+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>DataScope</td>\n",
       "      <td>None</td>\n",
       "      <td>LUID_UE5CSCAY</td>\n",
       "      <td>LusidInstrumentId</td>\n",
       "      <td>Price</td>\n",
       "      <td>mid</td>\n",
       "      <td>1077.15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Success</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            local_vars_configuration _lineage _cut_label  \\\n",
       "0  <lusid.configuration.Configuration object at 0...                       \n",
       "1  <lusid.configuration.Configuration object at 0...                       \n",
       "2  <lusid.configuration.Configuration object at 0...                       \n",
       "3  <lusid.configuration.Configuration object at 0...                       \n",
       "4  <lusid.configuration.Configuration object at 0...                       \n",
       "5  <lusid.configuration.Configuration object at 0...                       \n",
       "6  <lusid.configuration.Configuration object at 0...                       \n",
       "7  <lusid.configuration.Configuration object at 0...                       \n",
       "8  <lusid.configuration.Configuration object at 0...                       \n",
       "9  <lusid.configuration.Configuration object at 0...                       \n",
       "\n",
       "           _uploaded_by                           _as_at _scale_factor  \\\n",
       "0  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "1  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "2  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "3  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "4  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "5  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "6  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "7  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "8  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "9  00ubsbczibzRxZJzM2p7 2022-10-03 10:52:12.723909+00:00          None   \n",
       "\n",
       "  discriminator  _provider _price_source _instrument_id _instrument_id_type  \\\n",
       "0          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "1          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "2          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "3          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "4          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "5          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "6          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "7          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "8          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "9          None  DataScope          None  LUID_UE5CSCAY   LusidInstrumentId   \n",
       "\n",
       "  _quote_type _field  _value _unit   status  \n",
       "0       Price    mid 1045.85   USD  Success  \n",
       "1       Price    mid 1016.06   USD  Success  \n",
       "2       Price    mid 1070.71   USD  Success  \n",
       "3       Price    mid 1068.39   USD  Success  \n",
       "4       Price    mid 1076.28   USD  Success  \n",
       "5       Price    mid 1074.66   USD  Success  \n",
       "6       Price    mid 1070.33   USD  Success  \n",
       "7       Price    mid 1057.19   USD  Success  \n",
       "8       Price    mid 1044.69   USD  Success  \n",
       "9       Price    mid 1077.15   USD  Success  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run cocoon again, this time for quotes\n",
    "\n",
    "response = cocoon.load_from_data_frame(\n",
    "    api_factory=api_factory,\n",
    "    scope=scope,\n",
    "    data_frame=df_quotes,\n",
    "    mapping_required=mapping_required,\n",
    "    mapping_optional={},\n",
    "    file_type=\"quotes\",\n",
    ")\n",
    "\n",
    "prettyprint.upsert_quotes_response(response[\"quotes\"][\"success\"][0]).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 6: Run aggregration on portfolio\n",
    "\n",
    "Now we have all our data in LUSID to produce a valuation. Let's see how well our portfolio performed between 1 Jan and 30 Sep. Was it a good idea to allocate 55% to Google?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "recipe_code = \"market_value\"\n",
    "recipe_scope = \"backtesting\"\n",
    "\n",
    "# Create a recipe to perform a valuation\n",
    "configuration_recipe_api = api_factory.build(lusid.api.ConfigurationRecipeApi)\n",
    "\n",
    "configuration_recipe = models.ConfigurationRecipe(\n",
    "    scope=recipe_scope,\n",
    "    code=recipe_code,\n",
    "    market=models.MarketContext(\n",
    "        market_rules=[\n",
    "            models.MarketDataKeyRule(\n",
    "                key=\"Quote.LusidInstrumentId.*\",\n",
    "                supplier=\"DataScope\",\n",
    "                data_scope=scope,\n",
    "                quote_type=\"Price\",\n",
    "                field=\"mid\",\n",
    "                # quote_interval=date.strftime(\"%Y-%m-%d\") + \".0D\"\n",
    "                quote_interval=\"1W\",\n",
    "            )\n",
    "        ],\n",
    "        suppliers=models.MarketContextSuppliers(\n",
    "            commodity=\"DataScope\",\n",
    "            credit=\"DataScope\",\n",
    "            equity=\"DataScope\",\n",
    "            fx=\"DataScope\",\n",
    "            rates=\"DataScope\",\n",
    "        ),\n",
    "        options=models.MarketOptions(\n",
    "            default_supplier=\"DataScope\",\n",
    "            default_instrument_code_type=\"LusidInstrumentId\",\n",
    "            default_scope=scope,\n",
    "        ),\n",
    "    ),\n",
    ")\n",
    "\n",
    "upsert_configuration_recipe_response = (\n",
    "    configuration_recipe_api.upsert_configuration_recipe(\n",
    "        upsert_recipe_request=models.UpsertRecipeRequest(\n",
    "            configuration_recipe=configuration_recipe\n",
    "        )\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an aggregration function\n",
    "# This function takes two parameters of data and portfolio_code\n",
    "# It returns a valuation of the portfolio for the date\n",
    "# The return is a list of format [portfolio, date, valuation]\n",
    "# Example [TECH_PORTFOLIO, 2019-10-10, 10000000]\n",
    "\n",
    "\n",
    "def run_agg(start_date, end_date, portfolio_code):\n",
    "\n",
    "    # Create the valuation request\n",
    "    valuation_request = models.ValuationRequest(\n",
    "        recipe_id=models.ResourceId(scope=recipe_scope, code=recipe_code),\n",
    "        metrics=[\n",
    "            models.AggregateSpec(key=\"Analytic/default/ValuationDate\", op=\"Value\"),\n",
    "            models.AggregateSpec(key=\"Valuation/PvInReportCcy\", op=\"Sum\"),\n",
    "        ],\n",
    "        group_by=[\n",
    "            \"Analytic/default/ValuationDate\",\n",
    "        ],\n",
    "        portfolio_entity_ids=[\n",
    "            models.PortfolioEntityId(scope=scope, code=portfolio_code)\n",
    "        ],\n",
    "        valuation_schedule=models.ValuationSchedule(\n",
    "            effective_from=start_date, effective_at=end_date.isoformat()\n",
    "        ),\n",
    "    )\n",
    "\n",
    "    # Perform a valuation\n",
    "    valuation = api_factory.build(lusid.api.AggregationApi).get_valuation(\n",
    "        valuation_request=valuation_request\n",
    "    )\n",
    "\n",
    "    return valuation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_agg_df(agg_data):\n",
    "\n",
    "    agg_df = (\n",
    "        pd.DataFrame(agg_data)\n",
    "        .rename(\n",
    "            columns={\n",
    "                \"Sum(Valuation/PvInReportCcy)\": \"MarketValue\",\n",
    "                \"Analytic/default/ValuationDate\": \"Date\",\n",
    "            }\n",
    "        )\n",
    "        .sort_values(\"Date\", axis=0)\n",
    "    )\n",
    "    agg_df[\"MarketValue\"] = agg_df[\"MarketValue\"] / 1000000\n",
    "    agg_df[\"Portfolio\"] = portfolioA\n",
    "    agg_df[\"Date\"] = pd.to_datetime(agg_df[\"Date\"])\n",
    "    agg_df.set_index(\"Date\", inplace=True)\n",
    "\n",
    "    return agg_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_date = datetime(year=2019, month=1, day=2, tzinfo=pytz.UTC)\n",
    "end_date = datetime(year=2019, month=9, day=30, tzinfo=pytz.UTC)\n",
    "\n",
    "agg = run_agg(start_date, end_date, portfolioA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>MarketValue</th>\n",
       "      <th>Portfolio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-02 00:00:00+00:00</th>\n",
       "      <td>99.82</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-03 00:00:00+00:00</th>\n",
       "      <td>96.55</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-04 00:00:00+00:00</th>\n",
       "      <td>102.15</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-07 00:00:00+00:00</th>\n",
       "      <td>103.01</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-08 00:00:00+00:00</th>\n",
       "      <td>104.46</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           MarketValue Portfolio\n",
       "Date                                            \n",
       "2019-01-02 00:00:00+00:00        99.82  US_TECH1\n",
       "2019-01-03 00:00:00+00:00        96.55  US_TECH1\n",
       "2019-01-04 00:00:00+00:00       102.15  US_TECH1\n",
       "2019-01-07 00:00:00+00:00       103.01  US_TECH1\n",
       "2019-01-08 00:00:00+00:00       104.46  US_TECH1"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolioA_df = get_agg_df(agg.data)\n",
    "portfolioA_df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 7: Plot results of portfolio \n",
    "\n",
    "Plot the results of the DataFrame in a nice time-series. We can see our performance was good. The NAV of the portfolio when from 100 million USD on 1 Jan to just under 120 million USD on 30 Sep."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_series_performance():\n",
    "    ts_performance = portfolioA_df.plot(y=[\"MarketValue\"], figsize=(12, 9))\n",
    "    ts_performance.set_title(\n",
    "        f\"NAV of portfolio {portfolioA} from 01-01-2019 to 30-09-2019\", fontsize=\"large\"\n",
    "    )\n",
    "    ts_performance.set_ylabel(\"NAV in millions of $\", fontsize=\"large\")\n",
    "    ts_performance.set_xlabel(\"Time: Jan to Sep 2019\", fontsize=\"large\")\n",
    "    ts_performance.legend(prop={\"size\": 12})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_series_performance()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 8: Did we make the right allocation choice?\n",
    "\n",
    "What would have happened is we allocated 55% of portfolio NAV to Netflix instead of Google. How would that have impacted our portfolio's performance? Fortunately, we can check that easily using LUSID's derived portfolios functionality.<br>\n",
    "\n",
    "First lets create a derived portfolio from the parent portfolio which is portfolioA above. The derived portfolio will inherit all the holdings of the parent portfolio. See our page on [derived portfolios](https://support.lusid.com/what-is-a-derived-portfolio) to learn more about this portfolio type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_derived_portfolio(new_port, parent_port):\n",
    "\n",
    "    derived_api = api_factory.build(lusid.api.DerivedTransactionPortfoliosApi)\n",
    "\n",
    "    derived_request = lusid.models.CreateDerivedTransactionPortfolioRequest(\n",
    "        display_name=f\"Derived Portfolio of {parent_port}\",\n",
    "        code=new_port,\n",
    "        parent_portfolio_id=lusid.models.ResourceId(scope=scope, code=parent_port),\n",
    "        description=\"US Tech Strategy\",\n",
    "        created=\"2018-06-01T00:00:00Z\",\n",
    "    )\n",
    "\n",
    "    try:\n",
    "\n",
    "        response = derived_api.create_derived_portfolio(\n",
    "            scope=scope, create_derived_transaction_portfolio_request=derived_request\n",
    "        )\n",
    "\n",
    "        print(response)\n",
    "\n",
    "    except lusid.exceptions.ApiException as e:\n",
    "        if e.status == 400 and json.loads(e.body)[\"code\"] == 112:\n",
    "            print(json.loads(e.body)[\"title\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Could not create a portfolio with id 'US_TECH2' because it already exists in scope 'techStrategy'.\n"
     ]
    }
   ],
   "source": [
    "create_derived_portfolio(portfolioB, portfolioA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next let's calculate the holding adjustments required to rebalance 55% of NAV to Netflix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rebalance_port(scope, portfolioA, effective_at, adjustment):\n",
    "\n",
    "    holdings_response = (\n",
    "        api_factory.build(lusid.api.TransactionPortfoliosApi)\n",
    "        .get_holdings(scope, portfolioA, effective_at=effective_at)\n",
    "        .values\n",
    "    )\n",
    "\n",
    "    rebal_holdings = pd.DataFrame(\n",
    "        [\n",
    "            [holding.cost_portfolio_ccy.amount, holding.instrument_uid, holding.units]\n",
    "            for holding in holdings_response\n",
    "        ],\n",
    "        columns=[\"market_value\", \"LUID\", \"units\"],\n",
    "    )\n",
    "\n",
    "    rebal_holdings[\"client_internal\"] = rebal_holdings[\"LUID\"].apply(\n",
    "        lambda x: api_factory.build(lusid.api.InstrumentsApi)\n",
    "        .get_instrument(identifier_type=\"LusidInstrumentId\", identifier=x)\n",
    "        .identifiers[\"ClientInternal\"]\n",
    "    )\n",
    "\n",
    "    rebal_holdings[\"instrument_name\"] = rebal_holdings[\"LUID\"].apply(\n",
    "        lambda x: api_factory.build(lusid.api.InstrumentsApi)\n",
    "        .get_instrument(identifier_type=\"LusidInstrumentId\", identifier=x)\n",
    "        .name\n",
    "    )\n",
    "\n",
    "    rebal_holdings[\"Ticker\"] = rebal_holdings[\"LUID\"].apply(\n",
    "        lambda x: api_factory.build(lusid.api.InstrumentsApi)\n",
    "        .get_instrument(identifier_type=\"LusidInstrumentId\", identifier=x)\n",
    "        .identifiers[\"Ticker\"]\n",
    "    )\n",
    "\n",
    "    rebal_holdings[\"pct_mv\"] = rebal_holdings[\"market_value\"] / sum(\n",
    "        rebal_holdings[\"market_value\"], 0\n",
    "    )\n",
    "\n",
    "    rebal_holdings[\"target_pct_mv\"] = rebal_holdings[\"pct_mv\"]\n",
    "    for client_internal, value in adjustment:\n",
    "        rebal_holdings.loc[\n",
    "            rebal_holdings[\"client_internal\"] == client_internal, \"target_pct_mv\"\n",
    "        ] = value\n",
    "\n",
    "    rebal_holdings[\"target_units\"] = (\n",
    "        rebal_holdings[\"target_pct_mv\"]\n",
    "        / rebal_holdings[\"pct_mv\"]\n",
    "        * rebal_holdings[\"units\"]\n",
    "    )\n",
    "\n",
    "    return rebal_holdings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Running the rebalance function below, we can see the new target units for GOOG and NFLX:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>target_pct_mv</th>\n",
       "      <th>target_units</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>0.15</td>\n",
       "      <td>14354.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>0.15</td>\n",
       "      <td>94985.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>0.55</td>\n",
       "      <td>205485.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>0.15</td>\n",
       "      <td>110554.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        target_pct_mv  target_units\n",
       "Ticker                             \n",
       "GOOG             0.15      14354.12\n",
       "AAPL             0.15      94985.00\n",
       "NFLX             0.55     205485.33\n",
       "FB               0.15     110554.00"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rebalanced_portfolio = rebalance_port(\n",
    "    scope,\n",
    "    portfolioA,\n",
    "    \"2019-01-01T00:00:02Z\",\n",
    "    [(\"EQ38475943\", 0.15), (\"EQ36852475\", 0.55)],\n",
    ")\n",
    "rebalanced_portfolio[[\"Ticker\", \"target_pct_mv\", \"target_units\"]].set_index(\"Ticker\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The new % NAVs can be plotted on a pie-chart so we can visualise the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rebalanced_portfolio_pie():\n",
    "    plt.style.use(\"fivethirtyeight\")\n",
    "    rebalanced_portfolio_pie = rebalanced_portfolio.plot.pie(\n",
    "        y=\"target_pct_mv\",\n",
    "        labels=rebalanced_portfolio[\"instrument_name\"].values,\n",
    "        figsize=(11, 11),\n",
    "        title=f\"Allocation of portfolio {portfolioA} to FANG stocks by % of NAV\",\n",
    "        explode=(0.025, 0, 0, 0),\n",
    "        startangle=140,\n",
    "        autopct=\"%1.1f%%\",\n",
    "        textprops={\"fontsize\": 16},\n",
    "    )\n",
    "\n",
    "    rebalanced_portfolio_pie.set_ylabel(\"\")\n",
    "    rebalanced_portfolio_pie.legend(loc=4, prop={\"size\": 14})\n",
    "    rebalanced_portfolio_pie.set_title(\n",
    "        f\"Rebalanced allocation of portfolio {portfolioA} to FANG stocks by % of NAV\",\n",
    "        fontsize=20,\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1100x1100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rebalanced_portfolio_pie()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once we're happy with the rebalance quantities, these adjustments can be processed in LUSID using the Adjust Holdings APIs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def holding_adj_request(holdings):\n",
    "\n",
    "    holding_adj_request = []\n",
    "\n",
    "    for instrument, units in holdings:\n",
    "\n",
    "        holding_adj_request.append(\n",
    "            lusid.models.AdjustHoldingRequest(\n",
    "                instrument_identifiers={\n",
    "                    \"instrument/default/ClientInternal\": f\"{instrument}\"\n",
    "                },\n",
    "                tax_lots=[\n",
    "                    lusid.models.TargetTaxLotRequest(\n",
    "                        units=units,\n",
    "                        portfolio_cost=None,\n",
    "                        cost=lusid.models.CurrencyAndAmount(None, \"USD\"),\n",
    "                        price=None,\n",
    "                        purchase_date=\"2019-01-01T00:00:00Z\",\n",
    "                        settlement_date=\"2019-01-01T00:00:00Z\",\n",
    "                    )\n",
    "                ],\n",
    "            )\n",
    "        )\n",
    "\n",
    "    return holding_adj_request"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "holdings = [(\"EQ38475943\", 14390), (\"EQ36852475\", 206009)]\n",
    "\n",
    "holding_adjustment = holding_adj_request(holdings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = api_factory.build(lusid.api.TransactionPortfoliosApi).adjust_holdings(\n",
    "    scope,\n",
    "    portfolioB,\n",
    "    effective_at=\"2019-01-01T10:00:00Z\",\n",
    "    adjust_holding_request=holding_adjustment,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then rerun our aggregration functions and plot results against each other:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "derived_agg = run_agg(start_date, end_date, portfolioB)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>MarketValue</th>\n",
       "      <th>Portfolio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-02 00:00:00+00:00</th>\n",
       "      <td>99.97</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-03 00:00:00+00:00</th>\n",
       "      <td>98.36</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-04 00:00:00+00:00</th>\n",
       "      <td>105.83</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-07 00:00:00+00:00</th>\n",
       "      <td>109.44</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-08 00:00:00+00:00</th>\n",
       "      <td>111.33</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           MarketValue Portfolio\n",
       "Date                                            \n",
       "2019-01-02 00:00:00+00:00        99.97  US_TECH1\n",
       "2019-01-03 00:00:00+00:00        98.36  US_TECH1\n",
       "2019-01-04 00:00:00+00:00       105.83  US_TECH1\n",
       "2019-01-07 00:00:00+00:00       109.44  US_TECH1\n",
       "2019-01-08 00:00:00+00:00       111.33  US_TECH1"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolioB_df = get_agg_df(derived_agg.data)\n",
    "portfolioB_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Portfolio weighted 55% to Alphabet Inc</th>\n",
       "      <th>PortfolioUS_TECH1</th>\n",
       "      <th>Portfolio weighted 55% to Netflix</th>\n",
       "      <th>PortfolioUS_TECH2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-02 00:00:00+00:00</th>\n",
       "      <td>99.82</td>\n",
       "      <td>US_TECH1</td>\n",
       "      <td>99.97</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-03 00:00:00+00:00</th>\n",
       "      <td>96.55</td>\n",
       "      <td>US_TECH1</td>\n",
       "      <td>98.36</td>\n",
       "      <td>US_TECH1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Portfolio weighted 55% to Alphabet Inc  \\\n",
       "Date                                                                \n",
       "2019-01-02 00:00:00+00:00                                   99.82   \n",
       "2019-01-03 00:00:00+00:00                                   96.55   \n",
       "\n",
       "                          PortfolioUS_TECH1  \\\n",
       "Date                                          \n",
       "2019-01-02 00:00:00+00:00          US_TECH1   \n",
       "2019-01-03 00:00:00+00:00          US_TECH1   \n",
       "\n",
       "                           Portfolio weighted 55% to Netflix PortfolioUS_TECH2  \n",
       "Date                                                                            \n",
       "2019-01-02 00:00:00+00:00                              99.97          US_TECH1  \n",
       "2019-01-03 00:00:00+00:00                              98.36          US_TECH1  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "port_joined_df = portfolioA_df.join(\n",
    "    portfolioB_df, lsuffix=portfolioA, rsuffix=portfolioB\n",
    ")\n",
    "port_joined_df.rename(\n",
    "    columns={\n",
    "        \"MarketValueUS_TECH1\": \"Portfolio weighted 55% to Alphabet Inc\",\n",
    "        \"MarketValueUS_TECH2\": \"Portfolio weighted 55% to Netflix\",\n",
    "    },\n",
    "    inplace=True,\n",
    ")\n",
    "port_joined_df.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 9: Check results\n",
    "\n",
    "Looking at the time-series of results below, we can see we were correct to allocate 55% to Google versus Netflix in first 3Q of 2019."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_series_performance_all():\n",
    "    ts_performance_all = port_joined_df.plot(\n",
    "        y=[port_joined_df.columns[0], port_joined_df.columns[2]], figsize=(12, 9)\n",
    "    )\n",
    "    ts_performance_all.set_title(\n",
    "        \"NAV of portfolios from 01-01-2019 to 30-09-2019\", fontsize=\"large\"\n",
    "    )\n",
    "    ts_performance_all.set_ylabel(\"NAV in millions of $\", fontsize=\"large\")\n",
    "    ts_performance_all.set_xlabel(\"Time: Jan to Sep 2019\", fontsize=\"large\")\n",
    "    ts_performance_all.legend(prop={\"size\": 12})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_series_performance_all()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.6 ('.env': venv)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "vscode": {
   "interpreter": {
    "hash": "2631b36fd78b5e9ba2bda367fd8deaf1b7c0a55746e49610a3543f723e389a55"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}