HICP_and_ECB_Rates.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "responsible-steel",
   "metadata": {},
   "source": [
    "# Eurozone consumer prices inflation, ECB Deposit Facility, Market Yield on Government Bonds at 10-Year, wage inflation, and Riskless Yield Curve\n",
    "This notebook jaxteposes the evolution of Eurozone consumer prices inflation as measured by the HICP (Harmonized Index of Consumer Prices) with ECB Deposit Facility Rate and 10 year Government Bond yields. It then looks at the the relationship between riskfree rates (e.g. 10-year AAA-rated eurozone central government bonds rates) and Eurozone HICP + real GDP growth rates. HICP + GDP growth rates is known as _the intrinsic riskfree rate_. In theory the 10-year AAA-rated eurozone central government bond rate such as that for 10-Year Germany government bonds should be similar to the intrinsic riskfree rate. This notebook looks at how this played out since the 90's.\n",
    "\n",
    "I then look at Euroarea wage inflation data.\n",
    "\n",
    "Finally, I look at the evolution of the Euro riskless rate curve as defined by the yields on AAA-rated eurozone central government bonds.\n",
    "\n",
    "**NB**: Throughout this notebook in datasets with a quarterly frequency, data indexed to the start of a quarter designates the whole quarter starting on that date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "casual-border",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Uncomment if running in Google Colaboratory, otherwise the import of the curves module in the cell below will fail\n",
    "#!git clone -l -s https://github.com/ilchen/US_Economic_Data_Analysis.git cloned-repo\n",
    "#%cd cloned-repo\n",
    "\n",
    "# Install the latest version of eurostat\n",
    "# !pip install eurostat -U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "blank-cassette",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.ticker as mtick\n",
    "import pandas_datareader.data as web\n",
    "from pandas.tseries.offsets import MonthBegin, BDay, QuarterBegin\n",
    "\n",
    "import eurostat\n",
    "\n",
    "from datetime import date\n",
    "import re\n",
    "\n",
    "from dateutil.relativedelta import relativedelta\n",
    "\n",
    "from pricing import curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "former-nitrogen",
   "metadata": {},
   "outputs": [],
   "source": [
    "report_start = date.fromisoformat('1996-01-01')\n",
    "report_end = date.today()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "advanced-width",
   "metadata": {},
   "source": [
    "### Get Consumer Price Index for the Eurozone, ECB Deposit Facility Rate, 10 Year Government Bond Yields, and Real GDP\n",
    "I use the following dataseries provided by [FRED](https://fred.stlouisfed.org/):\n",
    "* `ECBDFR` &mdash; ECB Deposit Facility Rate for Euro Area (daily frequency, from 1999)\n",
    "* `ECBMLFR` &mdash; ECB Marginal Lending Facility Rate for Euro Area (daily frequency, from 1999). This is the rate at which banks can borrow money from the central bank against collateral for a period of one day (overnight). This rate is always higher than the main refinancing rate and therefore sets an upper limit for money market rates.\n",
    "\n",
    "And the following dataseries provided by the [Eurostat](https://ec.europa.eu/eurostat/web/main/data/database):\n",
    "* `irt_lt_mcby_m` &mdash; EMU convergence criterion series (monthly frequency). This series returns a dataset containing Long-Term Government Bond Yields for the Eurozone at 10-year maturity. I use it instead of the `IRLTLT01DEM156N` and `IRLTLT01ITM156N` datasets returned by FRED given that Eurostat's database tends to be updated earlier than that of FRED for Eurozone data.\n",
    "* `prc_hicp_midx` &mdash; Harmonized Index of Consumer Prices: All Items for the Eurozone (monthly frequency, 2015=100, from 1996)\n",
    "\n",
    "There's a relationship between the riskless rate as represented by AAA-rated eurozone central government bonds rates on the one hand and real GDP growth and inflation rates on the other hand. I use 10-year Germany Bond Yields as proxy for riskless long-term rates in the Eurozone given Germany's AAA credit rating. At the end of this section I look at real GDP developments in conjunction with the inflation of consumer prices. To calculate GDP growth for the Euro area I make use of the following dataseries from [Eurostat](https://ec.europa.eu/eurostat/databrowser/view/NAMQ_10_GDP/default/table?lang=en):\n",
    "* `namq_10_gdp` — Real Gross Domestic Product for the Eurozone, Millions of Chained 2010 Euros (quarterly frequency, from 1996). The closest series published by the FRED is `CLVMEURSCAB1GQEA19`, however it is still based on the old configuration of the Eurozone (EA19) so I don't use it. I make use of both non seasonally adjusted as well as seasonally and calendar adjusted data. This is needed because I want to obtain both annual GDP growth (i.e. growth over four quarters) as well as quarterly GDP growth and express the latter at an annual rate. I use the following formula to translate quarterly changes into annual rates:\n",
    "\n",
    "$$\\left(\\left({\\text{level of quarter n+1} \\over \\text{level of quarter n}}\\right)^4-1\\right)\\times 100\\% $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "voluntary-maker",
   "metadata": {},
   "outputs": [],
   "source": [
    "ecbr = web.get_data_fred(['ECBDFR', 'ECBMLFR'], start=report_start, end=report_end)\n",
    "\n",
    "# Retrieving the most recent Eurozone CPI and government bond yields from Eurostat's database\n",
    "EUROSTAT_DE_COUNTRY_LABEL = 'DE'\n",
    "EUROSTAT_IT_COUNTRY_LABEL = 'IT'\n",
    "eu_irt_lt = eurostat.get_data_df('irt_lt_mcby_m',\n",
    "        filter_pars={'startPeriod': report_start, 'geo': ['DE', 'IT']}).iloc[:, 2:]\n",
    "eu_irt_lt = eu_irt_lt.set_index(eu_irt_lt.columns[0]).T\n",
    "eu_irt_lt = eu_irt_lt.set_axis(pd.DatetimeIndex(eu_irt_lt.index, 'MS'))\n",
    "\n",
    "# Using Eurozone price index 2015=100, and All-items HICP: CP00 \n",
    "eu_hicp = eurostat.get_data_df('prc_hicp_midx',\n",
    "               filter_pars={'startPeriod': report_start, 'unit': 'I15', 'coicop': 'CP00', 'geo': 'EA'}).iloc[:, 3:]\n",
    "eu_hicp = eu_hicp.set_index(eu_hicp.columns[0]).T\n",
    "eu_hicp = eu_hicp.set_axis(pd.DatetimeIndex(eu_hicp.index, 'MS'))\n",
    "# Since prc_hicp_midx is indexed to 2015=100, we need to convert it to annual percentage changes\n",
    "eu_hicp_annual = eu_hicp.pct_change(12)\n",
    "\n",
    "# Make frequencies explicit, resample to month srart\n",
    "ecbr = ecbr.asfreq('D').resample('MS').last()\n",
    "\n",
    "# Merge and truncate to start of celendar year 1999.\n",
    "cpi_ecbr_irtlt = pd.concat([eu_hicp_annual, eu_irt_lt, ecbr], axis=1).loc['1997':]\n",
    "\n",
    "cpi_ecbr_irtlt = cpi_ecbr_irtlt[['EA', 'ECBDFR', 'ECBMLFR', 'DE', 'IT']]\n",
    "\n",
    "DE_YIELD_LABEL = '10y German Government Bond Yield'\n",
    "IT_YIELD_LABEL = '10y Italian Government Bond Yield'\n",
    "ECB_DEPOSIT_RATE_LABEL = 'ECB Deposit Facility Rate'\n",
    "GRAPH_TITLE_HICP = 'Eurozone annual HICP, ECB Deposit Facility and Marginal Lending Rates, and 10y Government Bond Yields'\n",
    "GRAPH_TITLE_HICP_2 = 'Eurozone annual HICP, ECB Deposit Facility, and 10y Government Bond Yields'\n",
    "cpi_ecbr_irtlt.rename(\n",
    "    columns={'EA': 'Annual Eurozone HICP',\n",
    "             'ECBDFR': ECB_DEPOSIT_RATE_LABEL, 'ECBMLFR': 'ECB Marginal Lending Facility Rate',\n",
    "             EUROSTAT_DE_COUNTRY_LABEL: DE_YIELD_LABEL,\n",
    "             EUROSTAT_IT_COUNTRY_LABEL: IT_YIELD_LABEL},\n",
    "    inplace=True)\n",
    "\n",
    "# Querying for non seasonally adjusted, seasonally and calendar adjusted all-items Eurozone GDP data\n",
    "# in chained linked volumes of 2010\n",
    "real_gdp = eurostat.get_data_df('namq_10_gdp', filter_pars={\n",
    "    'startPeriod': report_start, 'unit': 'CLV10_MEUR', 's_adj': ['NSA', 'SCA'], 'na_item': 'B1GQ', 'geo': 'EA'}).iloc[:, 4:]\n",
    "real_gdp = real_gdp.set_index(real_gdp.columns[0]).T\n",
    "real_gdp = real_gdp.set_axis(pd.DatetimeIndex(real_gdp.index, 'QS'))\n",
    "\n",
    "# Seasonally adjusted data is in the second column, it is more suitable for extrapolating GDP quarterly growth\n",
    "# at an annual rate\n",
    "real_gdp_quarterly = ((real_gdp.iloc[:,1]/real_gdp.iloc[:,1].shift(1)).pow(4)-1)\n",
    "real_gdp = real_gdp.iloc[:,:1]\n",
    "real_gdp.rename(columns={'EA': 'Real GDP'}, inplace=True)\n",
    "\n",
    "# To calculate the annual rate of GDP growth I sum up the non-seasonally adjusted GDP over the last 4 quarters.\n",
    "# If Eurostat were publishing seasonally adjusted GDP data at annual volumes (as is the case in the US),\n",
    "# I could calculate the mean over the past 4 quarters and use it as the actual annual GDP. \n",
    "real_gdp = real_gdp.rolling(4).sum().pct_change(4, fill_method='bfill')\n",
    "real_gdp['Real GDP over quarter at annual rate'] = real_gdp_quarterly\n",
    "real_gdp = real_gdp.loc['1997':]\n",
    "real_gdp.columns.names = [None]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "smooth-forestry",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the mean rate for the current month and, if needed, for the one before too\n",
    "rmth_start = cpi_ecbr_irtlt.index[-2 if pd.isna(cpi_ecbr_irtlt.iloc[-2, -1]) else -1].date()\n",
    "\n",
    "eu_irt_lt_cur_mth = eurostat.get_data_df('irt_lt_mcby_d',\n",
    "        filter_pars={'startPeriod': rmth_start, 'geo': ['DE', 'IT']}).iloc[:, 2:]\n",
    "eu_irt_lt_cur_mth = eu_irt_lt_cur_mth.set_index(eu_irt_lt_cur_mth.columns[0]).T\n",
    "eu_irt_lt_cur_mth = eu_irt_lt_cur_mth.set_axis(pd.DatetimeIndex(eu_irt_lt_cur_mth.index, 'B'))\n",
    "eu_irt_lt_cur_mth.rename(\n",
    "    columns={EUROSTAT_DE_COUNTRY_LABEL: DE_YIELD_LABEL,\n",
    "             EUROSTAT_IT_COUNTRY_LABEL: IT_YIELD_LABEL},\n",
    "    inplace=True)\n",
    "eu_irt_lt_cur_mth = eu_irt_lt_cur_mth.asfreq('D').resample('MS').mean()\n",
    "cpi_ecbr_irtlt.loc['2022':, [DE_YIELD_LABEL, IT_YIELD_LABEL]].update(eu_irt_lt_cur_mth)\n",
    "cpi_ecbr_irtlt.update(eu_irt_lt_cur_mth)\n",
    "\n",
    "# Convert to percentage points\n",
    "cpi_ecbr_irtlt.iloc[:,[1,2,3,4]] /= 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "blond-shaft",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>Annual Eurozone HICP</th>\n",
       "      <th>ECB Deposit Facility Rate</th>\n",
       "      <th>ECB Marginal Lending Facility Rate</th>\n",
       "      <th>10y German Government Bond Yield</th>\n",
       "      <th>10y Italian Government Bond Yield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1999-01-01</th>\n",
       "      <td>0.7650%</td>\n",
       "      <td>2.0000%</td>\n",
       "      <td>4.5000%</td>\n",
       "      <td>3.7000%</td>\n",
       "      <td>3.9200%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-02-01</th>\n",
       "      <td>0.7357%</td>\n",
       "      <td>2.0000%</td>\n",
       "      <td>4.5000%</td>\n",
       "      <td>3.8500%</td>\n",
       "      <td>4.0500%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-03-01</th>\n",
       "      <td>0.9393%</td>\n",
       "      <td>2.0000%</td>\n",
       "      <td>4.5000%</td>\n",
       "      <td>4.0400%</td>\n",
       "      <td>4.2700%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-04-01</th>\n",
       "      <td>1.0732%</td>\n",
       "      <td>1.5000%</td>\n",
       "      <td>3.5000%</td>\n",
       "      <td>3.8500%</td>\n",
       "      <td>4.1100%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-05-01</th>\n",
       "      <td>0.9355%</td>\n",
       "      <td>1.5000%</td>\n",
       "      <td>3.5000%</td>\n",
       "      <td>4.0100%</td>\n",
       "      <td>4.2800%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-04-01</th>\n",
       "      <td>2.3717%</td>\n",
       "      <td>4.0000%</td>\n",
       "      <td>4.7500%</td>\n",
       "      <td>2.4500%</td>\n",
       "      <td>3.8600%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-01</th>\n",
       "      <td>2.5660%</td>\n",
       "      <td>4.0000%</td>\n",
       "      <td>4.7500%</td>\n",
       "      <td>2.5200%</td>\n",
       "      <td>3.8400%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-01</th>\n",
       "      <td>2.5188%</td>\n",
       "      <td>3.7500%</td>\n",
       "      <td>4.5000%</td>\n",
       "      <td>2.4800%</td>\n",
       "      <td>3.9400%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-01</th>\n",
       "      <td>2.5778%</td>\n",
       "      <td>3.7500%</td>\n",
       "      <td>4.5000%</td>\n",
       "      <td>2.4600%</td>\n",
       "      <td>3.8300%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.7500%</td>\n",
       "      <td>4.5000%</td>\n",
       "      <td>2.1971%</td>\n",
       "      <td>3.6815%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>308 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Annual Eurozone HICP  ECB Deposit Facility Rate  \\\n",
       "1999-01-01               0.7650%                    2.0000%   \n",
       "1999-02-01               0.7357%                    2.0000%   \n",
       "1999-03-01               0.9393%                    2.0000%   \n",
       "1999-04-01               1.0732%                    1.5000%   \n",
       "1999-05-01               0.9355%                    1.5000%   \n",
       "...                          ...                        ...   \n",
       "2024-04-01               2.3717%                    4.0000%   \n",
       "2024-05-01               2.5660%                    4.0000%   \n",
       "2024-06-01               2.5188%                    3.7500%   \n",
       "2024-07-01               2.5778%                    3.7500%   \n",
       "2024-08-01                   NaN                    3.7500%   \n",
       "\n",
       "            ECB Marginal Lending Facility Rate  \\\n",
       "1999-01-01                             4.5000%   \n",
       "1999-02-01                             4.5000%   \n",
       "1999-03-01                             4.5000%   \n",
       "1999-04-01                             3.5000%   \n",
       "1999-05-01                             3.5000%   \n",
       "...                                        ...   \n",
       "2024-04-01                             4.7500%   \n",
       "2024-05-01                             4.7500%   \n",
       "2024-06-01                             4.5000%   \n",
       "2024-07-01                             4.5000%   \n",
       "2024-08-01                             4.5000%   \n",
       "\n",
       "            10y German Government Bond Yield  \\\n",
       "1999-01-01                           3.7000%   \n",
       "1999-02-01                           3.8500%   \n",
       "1999-03-01                           4.0400%   \n",
       "1999-04-01                           3.8500%   \n",
       "1999-05-01                           4.0100%   \n",
       "...                                      ...   \n",
       "2024-04-01                           2.4500%   \n",
       "2024-05-01                           2.5200%   \n",
       "2024-06-01                           2.4800%   \n",
       "2024-07-01                           2.4600%   \n",
       "2024-08-01                           2.1971%   \n",
       "\n",
       "            10y Italian Government Bond Yield  \n",
       "1999-01-01                            3.9200%  \n",
       "1999-02-01                            4.0500%  \n",
       "1999-03-01                            4.2700%  \n",
       "1999-04-01                            4.1100%  \n",
       "1999-05-01                            4.2800%  \n",
       "...                                       ...  \n",
       "2024-04-01                            3.8600%  \n",
       "2024-05-01                            3.8400%  \n",
       "2024-06-01                            3.9400%  \n",
       "2024-07-01                            3.8300%  \n",
       "2024-08-01                            3.6815%  \n",
       "\n",
       "[308 rows x 5 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.float_format = '{:.4%}'.format\n",
    "cpi_ecbr_irtlt.dropna(subset=[ECB_DEPOSIT_RATE_LABEL, DE_YIELD_LABEL, IT_YIELD_LABEL])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "affecting-national",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = cpi_ecbr_irtlt.iloc[:,:2].plot(figsize=(20,10), grid=True,\n",
    "                        title=GRAPH_TITLE_HICP_2,\n",
    "                        xticks=cpi_ecbr_irtlt.index[::12], xlabel='', rot=45, yticks=np.arange(0, .13, .02))\n",
    "cpi_ecbr_irtlt.iloc[:,3:].plot(ax=ax, linestyle='--', grid=True,\n",
    "                        xticks=cpi_ecbr_irtlt.index[::12], xlabel='', rot=45, yticks=np.arange(0, .13, .02))\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, cpi_ecbr_irtlt.index[::12])))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "direct-system",
   "metadata": {},
   "source": [
    "#### Eurozone HICP  based on monthly and quarterly changes\n",
    "In the previous part of this notebook I looked at HICP based on changes compared to 12 months ago. This is the standard way of determining annual percentage cahnges. Below I look at monthly changes in HICP and then translate them into annual percentage changes using the following simple formula for translating monthly HICP changes into annual percentage changes:\n",
    "\n",
    "$$\\left(\\left({\\text{level of month n+1} \\over \\text{level of month n}}\\right)^{12}-1\\right)\\times 100\\% $$\n",
    "\n",
    "And then the same for translating quarterly changes into annual rates:\n",
    "\n",
    "$$\\left(\\left({\\text{level of month n+1} \\over \\text{level of month n-2}}\\right)^4-1\\right)\\times 100\\% $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "hazardous-tablet",
   "metadata": {},
   "outputs": [],
   "source": [
    "from_date = date(2020, 1, 1)\n",
    "eu_hicp_monthly = eu_hicp.pct_change(fill_method='bfill').loc[from_date:, 'EA']\n",
    "eu_hicp_monthly.rename('Eurozone HICP Change over Prev Month', inplace=True)\n",
    "eu_hicp_annual = ((eu_hicp/eu_hicp.shift(1)).pow(12)-1).loc[from_date:, 'EA'].rename('Eurozone HICP Change over Prev Month at Annual Rate')\n",
    "eu_hicp_quarterly = ((eu_hicp/eu_hicp.shift(3)).pow(4)-1).loc[from_date:, 'EA'].rename('Eurozone HICP Change over Prev 3 Months at Annual Rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "refined-interface",
   "metadata": {},
   "outputs": [],
   "source": [
    "eu_hicp_df = pd.concat([cpi_ecbr_irtlt.loc[from_date:, cpi_ecbr_irtlt.columns[0]], eu_hicp_quarterly, eu_hicp_annual], axis=1).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "nutritional-slide",
   "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>Annual Eurozone HICP</th>\n",
       "      <th>Eurozone HICP Change over Prev 3 Months at Annual Rate</th>\n",
       "      <th>Eurozone HICP Change over Prev Month at Annual Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-08-01</th>\n",
       "      <td>5.2440%</td>\n",
       "      <td>2.8891%</td>\n",
       "      <td>6.7158%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-01</th>\n",
       "      <td>4.3351%</td>\n",
       "      <td>3.1465%</td>\n",
       "      <td>3.9394%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-01</th>\n",
       "      <td>2.9001%</td>\n",
       "      <td>3.8814%</td>\n",
       "      <td>1.0660%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-01</th>\n",
       "      <td>2.3977%</td>\n",
       "      <td>-0.5792%</td>\n",
       "      <td>-6.4496%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-01</th>\n",
       "      <td>2.9290%</td>\n",
       "      <td>-1.2160%</td>\n",
       "      <td>1.9551%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-01-01</th>\n",
       "      <td>2.7688%</td>\n",
       "      <td>-2.9851%</td>\n",
       "      <td>-4.2673%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-02-01</th>\n",
       "      <td>2.5817%</td>\n",
       "      <td>1.6901%</td>\n",
       "      <td>7.7373%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-01</th>\n",
       "      <td>2.4277%</td>\n",
       "      <td>4.1252%</td>\n",
       "      <td>9.4564%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-04-01</th>\n",
       "      <td>2.3717%</td>\n",
       "      <td>8.1334%</td>\n",
       "      <td>7.2191%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-01</th>\n",
       "      <td>2.5660%</td>\n",
       "      <td>6.3870%</td>\n",
       "      <td>2.6011%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-01</th>\n",
       "      <td>2.5188%</td>\n",
       "      <td>4.1160%</td>\n",
       "      <td>2.5955%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-01</th>\n",
       "      <td>2.5778%</td>\n",
       "      <td>1.5963%</td>\n",
       "      <td>-0.3785%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Annual Eurozone HICP  \\\n",
       "2023-08-01               5.2440%   \n",
       "2023-09-01               4.3351%   \n",
       "2023-10-01               2.9001%   \n",
       "2023-11-01               2.3977%   \n",
       "2023-12-01               2.9290%   \n",
       "2024-01-01               2.7688%   \n",
       "2024-02-01               2.5817%   \n",
       "2024-03-01               2.4277%   \n",
       "2024-04-01               2.3717%   \n",
       "2024-05-01               2.5660%   \n",
       "2024-06-01               2.5188%   \n",
       "2024-07-01               2.5778%   \n",
       "\n",
       "            Eurozone HICP Change over Prev 3 Months at Annual Rate  \\\n",
       "2023-08-01                                            2.8891%        \n",
       "2023-09-01                                            3.1465%        \n",
       "2023-10-01                                            3.8814%        \n",
       "2023-11-01                                           -0.5792%        \n",
       "2023-12-01                                           -1.2160%        \n",
       "2024-01-01                                           -2.9851%        \n",
       "2024-02-01                                            1.6901%        \n",
       "2024-03-01                                            4.1252%        \n",
       "2024-04-01                                            8.1334%        \n",
       "2024-05-01                                            6.3870%        \n",
       "2024-06-01                                            4.1160%        \n",
       "2024-07-01                                            1.5963%        \n",
       "\n",
       "            Eurozone HICP Change over Prev Month at Annual Rate  \n",
       "2023-08-01                                            6.7158%    \n",
       "2023-09-01                                            3.9394%    \n",
       "2023-10-01                                            1.0660%    \n",
       "2023-11-01                                           -6.4496%    \n",
       "2023-12-01                                            1.9551%    \n",
       "2024-01-01                                           -4.2673%    \n",
       "2024-02-01                                            7.7373%    \n",
       "2024-03-01                                            9.4564%    \n",
       "2024-04-01                                            7.2191%    \n",
       "2024-05-01                                            2.6011%    \n",
       "2024-06-01                                            2.5955%    \n",
       "2024-07-01                                           -0.3785%    "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eu_hicp_df.tail(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "impressed-greene",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "cm = sns.color_palette('Blues', as_cmap=True)\n",
    "IDX_FORMAT = '{:%Y-%m}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "requested-resort",
   "metadata": {},
   "outputs": [
    {
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       "  width: 200px;\n",
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       "#T_c2a65_row12_col0, #T_c2a65_row15_col0, #T_c2a65_row17_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #f1f7fd;\n",
       "  color: #000000;\n",
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       "#T_c2a65_row12_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #a1cbe2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c2a65_row13_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #f5fafe;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c2a65_row13_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #58a1cf;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c2a65_row14_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #09529d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c2a65_row15_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #2575b7;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c2a65_row16_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #f2f8fd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c2a65_row16_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #5aa2cf;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c2a65_row17_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #a4cce3;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_c2a65\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_c2a65_level0_col0\" class=\"col_heading level0 col0\" >Annual Eurozone HICP</th>\n",
       "      <th id=\"T_c2a65_level0_col1\" class=\"col_heading level0 col1\" >Eurozone HICP Change over Prev 3 Months at Annual Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row0\" class=\"row_heading level0 row0\" >2023-02</th>\n",
       "      <td id=\"T_c2a65_row0_col0\" class=\"data row0 col0\" >8.50%</td>\n",
       "      <td id=\"T_c2a65_row0_col1\" class=\"data row0 col1\" >0.96%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row1\" class=\"row_heading level0 row1\" >2023-03</th>\n",
       "      <td id=\"T_c2a65_row1_col0\" class=\"data row1 col0\" >6.88%</td>\n",
       "      <td id=\"T_c2a65_row1_col1\" class=\"data row1 col1\" >6.18%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row2\" class=\"row_heading level0 row2\" >2023-04</th>\n",
       "      <td id=\"T_c2a65_row2_col0\" class=\"data row2 col0\" >6.96%</td>\n",
       "      <td id=\"T_c2a65_row2_col1\" class=\"data row2 col1\" >9.82%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row3\" class=\"row_heading level0 row3\" >2023-05</th>\n",
       "      <td id=\"T_c2a65_row3_col0\" class=\"data row3 col0\" >6.10%</td>\n",
       "      <td id=\"T_c2a65_row3_col1\" class=\"data row3 col1\" >6.45%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row4\" class=\"row_heading level0 row4\" >2023-06</th>\n",
       "      <td id=\"T_c2a65_row4_col0\" class=\"data row4 col0\" >5.52%</td>\n",
       "      <td id=\"T_c2a65_row4_col1\" class=\"data row4 col1\" >3.75%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row5\" class=\"row_heading level0 row5\" >2023-07</th>\n",
       "      <td id=\"T_c2a65_row5_col0\" class=\"data row5 col0\" >5.31%</td>\n",
       "      <td id=\"T_c2a65_row5_col1\" class=\"data row5 col1\" >0.78%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row6\" class=\"row_heading level0 row6\" >2023-08</th>\n",
       "      <td id=\"T_c2a65_row6_col0\" class=\"data row6 col0\" >5.24%</td>\n",
       "      <td id=\"T_c2a65_row6_col1\" class=\"data row6 col1\" >2.89%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row7\" class=\"row_heading level0 row7\" >2023-09</th>\n",
       "      <td id=\"T_c2a65_row7_col0\" class=\"data row7 col0\" >4.34%</td>\n",
       "      <td id=\"T_c2a65_row7_col1\" class=\"data row7 col1\" >3.15%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row8\" class=\"row_heading level0 row8\" >2023-10</th>\n",
       "      <td id=\"T_c2a65_row8_col0\" class=\"data row8 col0\" >2.90%</td>\n",
       "      <td id=\"T_c2a65_row8_col1\" class=\"data row8 col1\" >3.88%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row9\" class=\"row_heading level0 row9\" >2023-11</th>\n",
       "      <td id=\"T_c2a65_row9_col0\" class=\"data row9 col0\" >2.40%</td>\n",
       "      <td id=\"T_c2a65_row9_col1\" class=\"data row9 col1\" >-0.58%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row10\" class=\"row_heading level0 row10\" >2023-12</th>\n",
       "      <td id=\"T_c2a65_row10_col0\" class=\"data row10 col0\" >2.93%</td>\n",
       "      <td id=\"T_c2a65_row10_col1\" class=\"data row10 col1\" >-1.22%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row11\" class=\"row_heading level0 row11\" >2024-01</th>\n",
       "      <td id=\"T_c2a65_row11_col0\" class=\"data row11 col0\" >2.77%</td>\n",
       "      <td id=\"T_c2a65_row11_col1\" class=\"data row11 col1\" >-2.99%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row12\" class=\"row_heading level0 row12\" >2024-02</th>\n",
       "      <td id=\"T_c2a65_row12_col0\" class=\"data row12 col0\" >2.58%</td>\n",
       "      <td id=\"T_c2a65_row12_col1\" class=\"data row12 col1\" >1.69%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row13\" class=\"row_heading level0 row13\" >2024-03</th>\n",
       "      <td id=\"T_c2a65_row13_col0\" class=\"data row13 col0\" >2.43%</td>\n",
       "      <td id=\"T_c2a65_row13_col1\" class=\"data row13 col1\" >4.13%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row14\" class=\"row_heading level0 row14\" >2024-04</th>\n",
       "      <td id=\"T_c2a65_row14_col0\" class=\"data row14 col0\" >2.37%</td>\n",
       "      <td id=\"T_c2a65_row14_col1\" class=\"data row14 col1\" >8.13%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row15\" class=\"row_heading level0 row15\" >2024-05</th>\n",
       "      <td id=\"T_c2a65_row15_col0\" class=\"data row15 col0\" >2.57%</td>\n",
       "      <td id=\"T_c2a65_row15_col1\" class=\"data row15 col1\" >6.39%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row16\" class=\"row_heading level0 row16\" >2024-06</th>\n",
       "      <td id=\"T_c2a65_row16_col0\" class=\"data row16 col0\" >2.52%</td>\n",
       "      <td id=\"T_c2a65_row16_col1\" class=\"data row16 col1\" >4.12%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c2a65_level0_row17\" class=\"row_heading level0 row17\" >2024-07</th>\n",
       "      <td id=\"T_c2a65_row17_col0\" class=\"data row17 col0\" >2.58%</td>\n",
       "      <td id=\"T_c2a65_row17_col1\" class=\"data row17 col1\" >1.60%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x12a22dfa0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eu_hicp_df = eu_hicp_df.loc[from_date:, eu_hicp_df.columns[0:2]]\n",
    "eu_hicp_df.tail(18).style.format_index(IDX_FORMAT).format('{:.2%}')\\\n",
    "    .set_properties(subset=eu_hicp_df.columns, **{'width': '200px'})\\\n",
    "    .set_table_styles([{'selector': 'th', 'props': 'text-align: right; width: 100px'}])\\\n",
    "    .background_gradient(cmap=cm)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "played-barcelona",
   "metadata": {},
   "source": [
    "#### Eurozone Real GDP growth\n",
    "I present both growth over the last 4 quarters as well as growth over one quarter, both expressed as annual percentage rates. For growth over one quarter (the 2<sup>nd</sup> column) I use seasonally and calendar adjusted data (Eurostat code `SCA`). For growth over the last 4 quarters (which provides the official annual growth) I use unadjusted data (Eurostat code `NSA`). Unfortunately Eurostat tends to delay publishing unadujusted data, as a result you might occasionally see a NaN value in the last row for it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "consistent-saying",
   "metadata": {},
   "outputs": [
    {
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       "<table id=\"T_374f3\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_374f3_level0_col0\" class=\"col_heading level0 col0\" >Real GDP</th>\n",
       "      <th id=\"T_374f3_level0_col1\" class=\"col_heading level0 col1\" >Real GDP over quarter at annual rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row0\" class=\"row_heading level0 row0\" >2020-01</th>\n",
       "      <td id=\"T_374f3_row0_col0\" class=\"data row0 col0\" >0.53%</td>\n",
       "      <td id=\"T_374f3_row0_col1\" class=\"data row0 col1\" >-12.75%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row1\" class=\"row_heading level0 row1\" >2020-04</th>\n",
       "      <td id=\"T_374f3_row1_col0\" class=\"data row1 col0\" >-3.37%</td>\n",
       "      <td id=\"T_374f3_row1_col1\" class=\"data row1 col1\" >-37.58%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row2\" class=\"row_heading level0 row2\" >2020-07</th>\n",
       "      <td id=\"T_374f3_row2_col0\" class=\"data row2 col0\" >-4.88%</td>\n",
       "      <td id=\"T_374f3_row2_col1\" class=\"data row2 col1\" >55.71%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row3\" class=\"row_heading level0 row3\" >2020-10</th>\n",
       "      <td id=\"T_374f3_row3_col0\" class=\"data row3 col0\" >-6.01%</td>\n",
       "      <td id=\"T_374f3_row3_col1\" class=\"data row3 col1\" >0.48%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row4\" class=\"row_heading level0 row4\" >2021-01</th>\n",
       "      <td id=\"T_374f3_row4_col0\" class=\"data row4 col0\" >-5.43%</td>\n",
       "      <td id=\"T_374f3_row4_col1\" class=\"data row4 col1\" >1.58%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row5\" class=\"row_heading level0 row5\" >2021-04</th>\n",
       "      <td id=\"T_374f3_row5_col0\" class=\"data row5 col0\" >1.41%</td>\n",
       "      <td id=\"T_374f3_row5_col1\" class=\"data row5 col1\" >9.54%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row6\" class=\"row_heading level0 row6\" >2021-07</th>\n",
       "      <td id=\"T_374f3_row6_col0\" class=\"data row6 col0\" >3.71%</td>\n",
       "      <td id=\"T_374f3_row6_col1\" class=\"data row6 col1\" >8.32%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row7\" class=\"row_heading level0 row7\" >2021-10</th>\n",
       "      <td id=\"T_374f3_row7_col0\" class=\"data row7 col0\" >6.04%</td>\n",
       "      <td id=\"T_374f3_row7_col1\" class=\"data row7 col1\" >2.30%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row8\" class=\"row_heading level0 row8\" >2022-01</th>\n",
       "      <td id=\"T_374f3_row8_col0\" class=\"data row8 col0\" >7.54%</td>\n",
       "      <td id=\"T_374f3_row8_col1\" class=\"data row8 col1\" >2.37%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row9\" class=\"row_heading level0 row9\" >2022-04</th>\n",
       "      <td id=\"T_374f3_row9_col0\" class=\"data row9 col0\" >5.01%</td>\n",
       "      <td id=\"T_374f3_row9_col1\" class=\"data row9 col1\" >3.60%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row10\" class=\"row_heading level0 row10\" >2022-07</th>\n",
       "      <td id=\"T_374f3_row10_col0\" class=\"data row10 col0\" >4.40%</td>\n",
       "      <td id=\"T_374f3_row10_col1\" class=\"data row10 col1\" >1.81%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row11\" class=\"row_heading level0 row11\" >2022-10</th>\n",
       "      <td id=\"T_374f3_row11_col0\" class=\"data row11 col0\" >3.44%</td>\n",
       "      <td id=\"T_374f3_row11_col1\" class=\"data row11 col1\" >-0.28%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row12\" class=\"row_heading level0 row12\" >2023-01</th>\n",
       "      <td id=\"T_374f3_row12_col0\" class=\"data row12 col0\" >2.54%</td>\n",
       "      <td id=\"T_374f3_row12_col1\" class=\"data row12 col1\" >2.12%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row13\" class=\"row_heading level0 row13\" >2023-04</th>\n",
       "      <td id=\"T_374f3_row13_col0\" class=\"data row13 col0\" >1.70%</td>\n",
       "      <td id=\"T_374f3_row13_col1\" class=\"data row13 col1\" >0.54%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row14\" class=\"row_heading level0 row14\" >2023-07</th>\n",
       "      <td id=\"T_374f3_row14_col0\" class=\"data row14 col0\" >1.18%</td>\n",
       "      <td id=\"T_374f3_row14_col1\" class=\"data row14 col1\" >0.16%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row15\" class=\"row_heading level0 row15\" >2023-10</th>\n",
       "      <td id=\"T_374f3_row15_col0\" class=\"data row15 col0\" >0.93%</td>\n",
       "      <td id=\"T_374f3_row15_col1\" class=\"data row15 col1\" >0.02%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row16\" class=\"row_heading level0 row16\" >2024-01</th>\n",
       "      <td id=\"T_374f3_row16_col0\" class=\"data row16 col0\" >0.49%</td>\n",
       "      <td id=\"T_374f3_row16_col1\" class=\"data row16 col1\" >1.13%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_374f3_level0_row17\" class=\"row_heading level0 row17\" >2024-04</th>\n",
       "      <td id=\"T_374f3_row17_col0\" class=\"data row17 col0\" >nan%</td>\n",
       "      <td id=\"T_374f3_row17_col1\" class=\"data row17 col1\" >1.21%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x12a22d8e0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# real_gdp.loc['2020':]\n",
    "real_gdp.tail(18).style.format_index(IDX_FORMAT).format('{:.2%}')\\\n",
    "    .set_properties(subset=real_gdp.columns, **{'width': '200px'})\\\n",
    "    .set_table_styles([{'selector': 'th', 'props': 'text-align: right; width: 100px'}])\\\n",
    "    .background_gradient(cmap=cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "psychological-trout",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = real_gdp.iloc[:,0].plot(figsize=(20,10), grid=True, title='Eurozone Real GDP growth (annual rate)',\n",
    "                   xticks=real_gdp.index[::4], xlabel='', rot=45)#, yticks=np.arange(-.15, .2, 0.025))\n",
    "ax.axhline(y=0, lw=2, c='k')\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "ax2 = ax.twiny()\n",
    "real_gdp.iloc[:,0].plot.bar(ax=ax2, xlabel='', legend=False)\n",
    "ax.axhline(y=real_gdp.iloc[:,0].mean(), ls='--', c='#1f77b4', label='Mean level of Real GDP growth')\n",
    "ax.legend()\n",
    "ax2.xaxis.set_major_locator(mtick.NullLocator())\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, real_gdp.index[::4])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "formal-compound",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean level of annual rate of real GDP growth in the Euro area since 1997-01-01: 1.63%\n"
     ]
    }
   ],
   "source": [
    "print(f'Mean level of annual rate of real GDP growth in the Euro area since {real_gdp.index[0]:%Y-%m-%d}: '\n",
    "      f'{real_gdp.iloc[:,0].mean():.2%}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "graduate-torture",
   "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>Real GDP</th>\n",
       "      <th>Annual Eurozone HICP</th>\n",
       "      <th>10y German Government Bond Yield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>0.5280%</td>\n",
       "      <td>1.1090%</td>\n",
       "      <td>-0.4400%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-01</th>\n",
       "      <td>-3.3654%</td>\n",
       "      <td>0.2217%</td>\n",
       "      <td>-0.4667%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-01</th>\n",
       "      <td>-4.8798%</td>\n",
       "      <td>-0.0313%</td>\n",
       "      <td>-0.5200%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-01</th>\n",
       "      <td>-6.0110%</td>\n",
       "      <td>-0.2754%</td>\n",
       "      <td>-0.6133%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>-5.4265%</td>\n",
       "      <td>1.0597%</td>\n",
       "      <td>-0.4633%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-01</th>\n",
       "      <td>1.4116%</td>\n",
       "      <td>1.8360%</td>\n",
       "      <td>-0.2800%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-01</th>\n",
       "      <td>3.7060%</td>\n",
       "      <td>2.8279%</td>\n",
       "      <td>-0.4500%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-01</th>\n",
       "      <td>6.0418%</td>\n",
       "      <td>4.6274%</td>\n",
       "      <td>-0.3000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-01</th>\n",
       "      <td>7.5422%</td>\n",
       "      <td>6.1422%</td>\n",
       "      <td>0.1033%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-01</th>\n",
       "      <td>5.0114%</td>\n",
       "      <td>8.0453%</td>\n",
       "      <td>1.0500%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-01</th>\n",
       "      <td>4.3964%</td>\n",
       "      <td>9.3113%</td>\n",
       "      <td>1.3033%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-01</th>\n",
       "      <td>3.4370%</td>\n",
       "      <td>9.9572%</td>\n",
       "      <td>2.1167%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01</th>\n",
       "      <td>2.5385%</td>\n",
       "      <td>8.0105%</td>\n",
       "      <td>2.3133%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-01</th>\n",
       "      <td>1.6988%</td>\n",
       "      <td>6.1931%</td>\n",
       "      <td>2.3600%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-01</th>\n",
       "      <td>1.1785%</td>\n",
       "      <td>4.9630%</td>\n",
       "      <td>2.5567%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-01</th>\n",
       "      <td>0.9306%</td>\n",
       "      <td>2.7423%</td>\n",
       "      <td>2.5067%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-01-01</th>\n",
       "      <td>0.4862%</td>\n",
       "      <td>2.5927%</td>\n",
       "      <td>2.2867%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-04-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.4855%</td>\n",
       "      <td>2.4833%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Real GDP  Annual Eurozone HICP  10y German Government Bond Yield\n",
       "2020-01-01   0.5280%               1.1090%                          -0.4400%\n",
       "2020-04-01  -3.3654%               0.2217%                          -0.4667%\n",
       "2020-07-01  -4.8798%              -0.0313%                          -0.5200%\n",
       "2020-10-01  -6.0110%              -0.2754%                          -0.6133%\n",
       "2021-01-01  -5.4265%               1.0597%                          -0.4633%\n",
       "2021-04-01   1.4116%               1.8360%                          -0.2800%\n",
       "2021-07-01   3.7060%               2.8279%                          -0.4500%\n",
       "2021-10-01   6.0418%               4.6274%                          -0.3000%\n",
       "2022-01-01   7.5422%               6.1422%                           0.1033%\n",
       "2022-04-01   5.0114%               8.0453%                           1.0500%\n",
       "2022-07-01   4.3964%               9.3113%                           1.3033%\n",
       "2022-10-01   3.4370%               9.9572%                           2.1167%\n",
       "2023-01-01   2.5385%               8.0105%                           2.3133%\n",
       "2023-04-01   1.6988%               6.1931%                           2.3600%\n",
       "2023-07-01   1.1785%               4.9630%                           2.5567%\n",
       "2023-10-01   0.9306%               2.7423%                           2.5067%\n",
       "2024-01-01   0.4862%               2.5927%                           2.2867%\n",
       "2024-04-01       NaN               2.4855%                           2.4833%"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Including only the yield on German government bonds as those of Italy are not AAA rated and cannot be regarded\n",
    "# as riskfree\n",
    "df = pd.concat([real_gdp.iloc[:,0], cpi_ecbr_irtlt.iloc[:,[0,3]].resample('qs').mean()], axis=1)\\\n",
    "    .loc[:real_gdp.last_valid_index()] # Truncate based on last valid GDP value\n",
    "df.loc['2020':]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "suspected-requirement",
   "metadata": {},
   "source": [
    "### Visualizing the relationship between 10y German Bund Yield and the Intrinsic Riskfree rate (real GDP growth + inflation rates)\n",
    "I use Germany 10-year government bond yield as a representative of a Eurozone central government bond with an AAA credit rating in the below graph. It is a proxy for the actual long-term riskfree rate in the Eurozone. I compare it with the intrinsic riskfree rate as defined by the sum of real GDP growth and inflation rates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "median-particle",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.iloc[:, -1].plot(figsize=(20,10), grid=True,\n",
    "                         title='Annual HICP and Real GDP vs ' + DE_YIELD_LABEL,\n",
    "                         xticks=df.index[::2], xlabel='', rot=45,\n",
    "                         yticks=np.arange(-.15, .2, 0.025), linestyle='--', color='k')\n",
    "ax2 = ax.twiny()\n",
    "df.iloc[:,[0,1]].plot.bar(ax=ax2, xlabel='', stacked=True)\n",
    "ax.legend(loc='upper center')\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "ax2.xaxis.set_major_locator(mtick.NullLocator())\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, df.index[::2])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "polyphonic-import",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gap between intrinsic (GDP+HICP) and actual (10-y German Bund) riskfree rates: nan%\n",
      "Compared with: 0.79% one quarter earlier\n"
     ]
    }
   ],
   "source": [
    "print('Gap between intrinsic (GDP+HICP) and actual (10-y German Bund) riskfree rates: {:.2%}\\n'\n",
    "      'Compared with: {:.2%} one quarter earlier'.format(\n",
    "    df.iloc[-1,0] + df.iloc[-1,1] - df.iloc[-1,2], df.iloc[-2,0] + df.iloc[-2,1] - df.iloc[-2,2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cheap-washington",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average gap between intrinsic (GDP+HICP) and actual (10-y German Bund) riskfree rates since 1997-01: 1.11%\n"
     ]
    }
   ],
   "source": [
    "print('Average gap between intrinsic (GDP+HICP) and actual (10-y German Bund) riskfree rates since {:%Y-%m}: {:.2%}'\n",
    "      .format(df.index[0], df.iloc[:,0].mean() + df.iloc[:,1].mean() - df.iloc[:,2].mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "located-envelope",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average gap between intrinsic (GDP+HICP) and actual (10-y German Bund) riskfree rates since 2009-01: 1.89%\n"
     ]
    }
   ],
   "source": [
    "from_dt = date(2009, 1, 1)\n",
    "means = df.loc[from_dt:].mean()\n",
    "print('Average gap between intrinsic (GDP+HICP) and actual (10-y German Bund) riskfree rates since {:%Y-%m}: {:.2%}'\n",
    "      .format(from_dt, means.iloc[0] + means.iloc[1] - means.iloc[2]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "rotary-complement",
   "metadata": {},
   "source": [
    "## A quick look at wage inflation in the Eurozone\n",
    "In contrast to U.S. Bureau of Labor Statistics, unfortunately Eurostat typically lags by one quarter in publishing data on wage inflation and publishes them only with quarterly frequencies.\n",
    "\n",
    "I use the following dataseries provided by [Eurostat](https://ec.europa.eu/eurostat/web/main/data/database):\n",
    "* `lc_lci_r2_q` &mdash; Labour cost index by NACE Rev. 2 activity - nominal value, quarterly data. This series returns a MultiIndexed dataset containing different views on this data for the Eurozone as a whole as whell as for each individual country in the EU."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "objective-humidity",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Seasonally and calendar-adjusted, 2020=100\n",
    "# NACE Rev 2. Sections B to S from 2009Q1 onward\n",
    "# Labour cost for LCI (compensation of employees plus taxes minus subsidies): D1_D4_MD5\n",
    "eu_wagei = eurostat.get_data_df('lc_lci_r2_q',\n",
    "        filter_pars={'startPeriod': report_start, 's_adj': 'SCA', 'unit': 'I20',\n",
    "                     'nace_r2': 'B-S', 'lcstruct': 'D1_D4_MD5', 'geo': 'EA'}).iloc[:, 5:]\n",
    "eu_wagei = eu_wagei.set_index(eu_wagei.columns[0]).T\n",
    "eu_wagei = eu_wagei.set_axis(pd.DatetimeIndex(eu_wagei.index, 'QS'))\n",
    "eu_wagei.dropna(inplace=True)\n",
    "eu_wagei_quarterly = (eu_wagei/eu_wagei.shift()).pow(4) - 1\n",
    "eu_wagei_quarterly.rename(columns={'EA': 'Hourly Earnings Change Over Last Quarter at Annual Rate'}, inplace=True)\n",
    "eu_wagei = eu_wagei.pct_change(4, fill_method='bfill').dropna()\n",
    "eu_wagei.rename(columns={'EA': 'Hourly Earnings Annual Percentage Change'}, inplace=True)\n",
    "\n",
    "cpi_and_wagei = pd.concat([cpi_ecbr_irtlt.iloc[:,0].resample('qs').last().loc[eu_wagei.index[0]:], eu_wagei], axis=1)\\\n",
    "     .loc[:date.today()-relativedelta(months=+3)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "becoming-burner",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Mean level of Wage Inflation, and HICP\n",
    "mean_level_wagei = eu_wagei.iloc[:,0].mean()\n",
    "mean_level_cpi = cpi_ecbr_irtlt.iloc[:,0].mean()\n",
    "\n",
    "LABEL_MEAN_WAGEI = 'Mean Level of Annual Changes in Labour Costs'\n",
    "LABEL_MEAN_CPI = 'Mean Level of Annual Changes in HICP'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "divine-marble",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = cpi_and_wagei.plot(figsize=(20,10), grid=True,\n",
    "                        title='Eurozone Annual HICP and Hourly Earnings',\n",
    "                        xticks=cpi_and_wagei.index[::2], xlabel='', rot=45, yticks=np.arange(0, .13, .02))\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "#ax.axhline(y=mean_level_cpi, lw=2, ls='--', c='#1f77b4', label=LABEL_MEAN_CPI)\n",
    "ax.axhline(y=mean_level_wagei, lw=2, ls='--', c='#ff7f0e', label=LABEL_MEAN_WAGEI)\n",
    "ax.legend()\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, cpi_and_wagei.index[::2])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "convinced-antenna",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Labour costs annual growth +2.23% above the historic mean of 2.27% in quarter starting on 2024-01-01\n"
     ]
    }
   ],
   "source": [
    "print('Labour costs annual growth {:+.2%} above the historic mean of {:.2%} in quarter starting on {:%Y-%m-%d}'\n",
    "      .format(eu_wagei.iloc[-1,0]-mean_level_wagei, mean_level_wagei, eu_wagei.index[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "wound-motorcycle",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  background-color: #66abd4;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row7_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #77b5d9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_f6c36_row8_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #206fb4;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row8_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #2d7dbb;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row9_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #08519c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row9_col1, #T_f6c36_row10_col0, #T_f6c36_row11_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #08306b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row10_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #3484bf;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row11_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #084387;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row12_col0, #T_f6c36_row15_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #2e7ebc;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row12_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #08488e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row13_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #0d57a1;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row14_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #7db8da;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_f6c36_row14_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #083e81;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row15_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #b0d2e7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_f6c36_row16_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #c1d9ed;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_f6c36_row16_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #125ea6;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_f6c36_row17_col0 {\n",
       "  width: 200px;\n",
       "  background-color: #bed8ec;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_f6c36_row17_col1 {\n",
       "  width: 200px;\n",
       "  background-color: #000000;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_f6c36\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_f6c36_level0_col0\" class=\"col_heading level0 col0\" >Annual Eurozone HICP</th>\n",
       "      <th id=\"T_f6c36_level0_col1\" class=\"col_heading level0 col1\" >Hourly Earnings Annual Percentage Change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row0\" class=\"row_heading level0 row0\" >2020-01</th>\n",
       "      <td id=\"T_f6c36_row0_col0\" class=\"data row0 col0\" >0.75%</td>\n",
       "      <td id=\"T_f6c36_row0_col1\" class=\"data row0 col1\" >3.95%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row1\" class=\"row_heading level0 row1\" >2020-04</th>\n",
       "      <td id=\"T_f6c36_row1_col0\" class=\"data row1 col0\" >0.27%</td>\n",
       "      <td id=\"T_f6c36_row1_col1\" class=\"data row1 col1\" >2.99%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row2\" class=\"row_heading level0 row2\" >2020-07</th>\n",
       "      <td id=\"T_f6c36_row2_col0\" class=\"data row2 col0\" >-0.31%</td>\n",
       "      <td id=\"T_f6c36_row2_col1\" class=\"data row2 col1\" >2.88%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row3\" class=\"row_heading level0 row3\" >2020-10</th>\n",
       "      <td id=\"T_f6c36_row3_col0\" class=\"data row3 col0\" >-0.27%</td>\n",
       "      <td id=\"T_f6c36_row3_col1\" class=\"data row3 col1\" >2.35%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row4\" class=\"row_heading level0 row4\" >2021-01</th>\n",
       "      <td id=\"T_f6c36_row4_col0\" class=\"data row4 col0\" >1.33%</td>\n",
       "      <td id=\"T_f6c36_row4_col1\" class=\"data row4 col1\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row5\" class=\"row_heading level0 row5\" >2021-04</th>\n",
       "      <td id=\"T_f6c36_row5_col0\" class=\"data row5 col0\" >1.90%</td>\n",
       "      <td id=\"T_f6c36_row5_col1\" class=\"data row5 col1\" >-0.40%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row6\" class=\"row_heading level0 row6\" >2021-07</th>\n",
       "      <td id=\"T_f6c36_row6_col0\" class=\"data row6 col0\" >3.36%</td>\n",
       "      <td id=\"T_f6c36_row6_col1\" class=\"data row6 col1\" >1.80%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row7\" class=\"row_heading level0 row7\" >2021-10</th>\n",
       "      <td id=\"T_f6c36_row7_col0\" class=\"data row7 col0\" >4.96%</td>\n",
       "      <td id=\"T_f6c36_row7_col1\" class=\"data row7 col1\" >2.40%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row8\" class=\"row_heading level0 row8\" >2022-01</th>\n",
       "      <td id=\"T_f6c36_row8_col0\" class=\"data row8 col0\" >7.44%</td>\n",
       "      <td id=\"T_f6c36_row8_col1\" class=\"data row8 col1\" >3.80%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row9\" class=\"row_heading level0 row9\" >2022-04</th>\n",
       "      <td id=\"T_f6c36_row9_col0\" class=\"data row9 col0\" >8.64%</td>\n",
       "      <td id=\"T_f6c36_row9_col1\" class=\"data row9 col1\" >5.53%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row10\" class=\"row_heading level0 row10\" >2022-07</th>\n",
       "      <td id=\"T_f6c36_row10_col0\" class=\"data row10 col0\" >9.93%</td>\n",
       "      <td id=\"T_f6c36_row10_col1\" class=\"data row10 col1\" >3.63%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row11\" class=\"row_heading level0 row11\" >2022-10</th>\n",
       "      <td id=\"T_f6c36_row11_col0\" class=\"data row11 col0\" >9.20%</td>\n",
       "      <td id=\"T_f6c36_row11_col1\" class=\"data row11 col1\" >5.56%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row12\" class=\"row_heading level0 row12\" >2023-01</th>\n",
       "      <td id=\"T_f6c36_row12_col0\" class=\"data row12 col0\" >6.88%</td>\n",
       "      <td id=\"T_f6c36_row12_col1\" class=\"data row12 col1\" >5.01%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row13\" class=\"row_heading level0 row13\" >2023-04</th>\n",
       "      <td id=\"T_f6c36_row13_col0\" class=\"data row13 col0\" >5.52%</td>\n",
       "      <td id=\"T_f6c36_row13_col1\" class=\"data row13 col1\" >4.67%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row14\" class=\"row_heading level0 row14\" >2023-07</th>\n",
       "      <td id=\"T_f6c36_row14_col0\" class=\"data row14 col0\" >4.34%</td>\n",
       "      <td id=\"T_f6c36_row14_col1\" class=\"data row14 col1\" >5.21%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row15\" class=\"row_heading level0 row15\" >2023-10</th>\n",
       "      <td id=\"T_f6c36_row15_col0\" class=\"data row15 col0\" >2.93%</td>\n",
       "      <td id=\"T_f6c36_row15_col1\" class=\"data row15 col1\" >3.79%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row16\" class=\"row_heading level0 row16\" >2024-01</th>\n",
       "      <td id=\"T_f6c36_row16_col0\" class=\"data row16 col0\" >2.43%</td>\n",
       "      <td id=\"T_f6c36_row16_col1\" class=\"data row16 col1\" >4.50%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f6c36_level0_row17\" class=\"row_heading level0 row17\" >2024-04</th>\n",
       "      <td id=\"T_f6c36_row17_col0\" class=\"data row17 col0\" >2.52%</td>\n",
       "      <td id=\"T_f6c36_row17_col1\" class=\"data row17 col1\" >nan%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x12ad696a0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cpi_and_wagei = cpi_and_wagei.loc[from_date:, cpi_and_wagei.columns[0:2]]\n",
    "cpi_and_wagei.tail(18).style.format_index(IDX_FORMAT).format('{:.2%}')\\\n",
    "    .set_properties(subset=cpi_and_wagei.columns, **{'width': '200px'})\\\n",
    "    .set_table_styles([{'selector': 'th', 'props': 'text-align: right; width: 100px'}])\\\n",
    "    .background_gradient(cmap=cm)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "confidential-routine",
   "metadata": {},
   "source": [
    "## Analyzing Euro Riskless Rate Curve\n",
    "In this analysis I make use of the spot rates (aka zero-rates) implied by AAA-rated governmental bonds in the Euro area.\n",
    "\n",
    "I use the following dataseries provided by the [Eurostat](https://ec.europa.eu/eurostat/web/main/data/database):\n",
    "* `irt_euryld_m` &mdash; Euro yield curves (monthly frequency). This series returns a MultiIndexed dataset from which multiple yields can be extraced: Instantaneous forward yield curve, Par yield curve, and Spot rate yield curve. In my analysis I use the Spor rate yield curve. The returned rates are presented using Annual percentage rates/yields and represent the average over all business days in a given month. [The ECB uses continuous compounding](https://www.ecb.europa.eu/stats/financial_markets_and_interest_rates/euro_area_yield_curves/shared/pdf/technical_notes.pdf) when calculating them.\n",
    "* `irt_st_m` &mdash; Euro EURIBOR rates (monthly frequency). EURIBOR uses the actual/360 daycount convention. This series returns a MultiIndexed dataset allowing to select different maturities. I only use the 1 month rates in this notebook as the spread between government bond rates and EURIBOR tends to increase with longer maturities. Rates returned represent the average over all business days in a given month.\n",
    "\n",
    "And one dataset from [FRED](https://fred.stlouisfed.org):\n",
    "* `ECBDFR` &mdash; ECB Deposit Facility Rate for Euro Area (daily frequency). I use it as proxy for overnight rate after downsampling to monthly frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "introductory-norfolk",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The ECB provides yields for maturities ranging from 3 months till 30 years\n",
    "year_maturities = range(1, 31)\n",
    "maturities = ['Y'+str(maturity) for maturity in year_maturities]\n",
    "\n",
    "# Taking the last 3 months and converting to decimal fractions\n",
    "euro_curves = eurostat.get_data_df('irt_euryld_m', filter_pars={\n",
    "    'startPeriod': (report_end-MonthBegin(4)).date(), 'freq': 'M',\n",
    "    'yld_curv': 'SPOT_RT',\n",
    "    'maturity': maturities,\n",
    "    'bonds': 'CGB_EA_AAA', 'geo': 'EA'})\n",
    "euro_curves = euro_curves.drop(euro_curves.columns[:3].append(euro_curves.columns[4:5]), axis=1)\n",
    "euro_curves = euro_curves.set_index(euro_curves.columns[0]).T / 100.\n",
    "euro_spot_rates = euro_curves.set_axis(pd.DatetimeIndex(euro_curves.index, 'MS'))\n",
    "\n",
    "mm_rates = eurostat.get_data_df('irt_st_m', filter_pars={\n",
    "    'startPeriod': (report_end-MonthBegin(4)).date(), 'freq': 'M',\n",
    "    'int_rt': 'IRT_M1', 'geo': 'EA'}).iloc[:,2:]\n",
    "mm_rates = mm_rates.set_index(mm_rates.columns[0]).T / 100.\n",
    "mm_rates = mm_rates.set_axis(pd.DatetimeIndex(mm_rates.index, 'MS'))\n",
    "\n",
    "ecb_deposit_rate = web.get_data_fred('ECBDFR', start=report_end-MonthBegin(4)) / 100.\n",
    "\n",
    "# Resample to monthly frequency\n",
    "ecb_deposit_rate = ecb_deposit_rate.asfreq('D').resample('MS').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "auburn-prague",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting EURIBOR and ECB Deposit rates from actual/360 to actual/actual and then to continuous compounding\n",
    "leap_year_cond = lambda idx: idx.year % 4 == 0 & ((idx.year % 100 != 0) | (idx.year % 400 == 0))\n",
    "mm_rates[leap_year_cond(mm_rates.index)] *= 366. / 360\n",
    "mm_rates[np.invert(leap_year_cond(mm_rates.index))] *= 365. / 360\n",
    "ecb_deposit_rate[leap_year_cond(ecb_deposit_rate.index)] *= 366. / 360\n",
    "ecb_deposit_rate[np.invert(leap_year_cond(ecb_deposit_rate.index))] *= 365. / 360\n",
    "\n",
    "\n",
    "# From annual to continuous compounding\n",
    "ecb_deposit_rate = np.log(1 + ecb_deposit_rate)\n",
    "mm_rates = np.log(1 + mm_rates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "common-paris",
   "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>maturity</th>\n",
       "      <th>1 month</th>\n",
       "      <th>Y1</th>\n",
       "      <th>Y2</th>\n",
       "      <th>Y3</th>\n",
       "      <th>Y4</th>\n",
       "      <th>Y5</th>\n",
       "      <th>Y6</th>\n",
       "      <th>Y7</th>\n",
       "      <th>Y8</th>\n",
       "      <th>Y9</th>\n",
       "      <th>...</th>\n",
       "      <th>Y21</th>\n",
       "      <th>Y22</th>\n",
       "      <th>Y23</th>\n",
       "      <th>Y24</th>\n",
       "      <th>Y25</th>\n",
       "      <th>Y26</th>\n",
       "      <th>Y27</th>\n",
       "      <th>Y28</th>\n",
       "      <th>Y29</th>\n",
       "      <th>Y30</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-05-01</th>\n",
       "      <td>3.8079%</td>\n",
       "      <td>3.2982%</td>\n",
       "      <td>2.9508%</td>\n",
       "      <td>2.7314%</td>\n",
       "      <td>2.6017%</td>\n",
       "      <td>2.5339%</td>\n",
       "      <td>2.5080%</td>\n",
       "      <td>2.5093%</td>\n",
       "      <td>2.5276%</td>\n",
       "      <td>2.5554%</td>\n",
       "      <td>...</td>\n",
       "      <td>2.7603%</td>\n",
       "      <td>2.7531%</td>\n",
       "      <td>2.7431%</td>\n",
       "      <td>2.7306%</td>\n",
       "      <td>2.7158%</td>\n",
       "      <td>2.6992%</td>\n",
       "      <td>2.6809%</td>\n",
       "      <td>2.6612%</td>\n",
       "      <td>2.6402%</td>\n",
       "      <td>2.6183%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-01</th>\n",
       "      <td>3.6286%</td>\n",
       "      <td>3.1848%</td>\n",
       "      <td>2.8703%</td>\n",
       "      <td>2.6683%</td>\n",
       "      <td>2.5473%</td>\n",
       "      <td>2.4838%</td>\n",
       "      <td>2.4600%</td>\n",
       "      <td>2.4630%</td>\n",
       "      <td>2.4832%</td>\n",
       "      <td>2.5134%</td>\n",
       "      <td>...</td>\n",
       "      <td>2.7617%</td>\n",
       "      <td>2.7565%</td>\n",
       "      <td>2.7481%</td>\n",
       "      <td>2.7369%</td>\n",
       "      <td>2.7231%</td>\n",
       "      <td>2.7071%</td>\n",
       "      <td>2.6891%</td>\n",
       "      <td>2.6694%</td>\n",
       "      <td>2.6483%</td>\n",
       "      <td>2.6260%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-01</th>\n",
       "      <td>3.6118%</td>\n",
       "      <td>3.0876%</td>\n",
       "      <td>2.7795%</td>\n",
       "      <td>2.5816%</td>\n",
       "      <td>2.4643%</td>\n",
       "      <td>2.4050%</td>\n",
       "      <td>2.3866%</td>\n",
       "      <td>2.3960%</td>\n",
       "      <td>2.4234%</td>\n",
       "      <td>2.4615%</td>\n",
       "      <td>...</td>\n",
       "      <td>2.7785%</td>\n",
       "      <td>2.7746%</td>\n",
       "      <td>2.7668%</td>\n",
       "      <td>2.7557%</td>\n",
       "      <td>2.7414%</td>\n",
       "      <td>2.7245%</td>\n",
       "      <td>2.7052%</td>\n",
       "      <td>2.6839%</td>\n",
       "      <td>2.6609%</td>\n",
       "      <td>2.6363%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "maturity    1 month      Y1      Y2      Y3      Y4      Y5      Y6      Y7  \\\n",
       "2024-05-01  3.8079% 3.2982% 2.9508% 2.7314% 2.6017% 2.5339% 2.5080% 2.5093%   \n",
       "2024-06-01  3.6286% 3.1848% 2.8703% 2.6683% 2.5473% 2.4838% 2.4600% 2.4630%   \n",
       "2024-07-01  3.6118% 3.0876% 2.7795% 2.5816% 2.4643% 2.4050% 2.3866% 2.3960%   \n",
       "\n",
       "maturity        Y8      Y9  ...     Y21     Y22     Y23     Y24     Y25  \\\n",
       "2024-05-01 2.5276% 2.5554%  ... 2.7603% 2.7531% 2.7431% 2.7306% 2.7158%   \n",
       "2024-06-01 2.4832% 2.5134%  ... 2.7617% 2.7565% 2.7481% 2.7369% 2.7231%   \n",
       "2024-07-01 2.4234% 2.4615%  ... 2.7785% 2.7746% 2.7668% 2.7557% 2.7414%   \n",
       "\n",
       "maturity       Y26     Y27     Y28     Y29     Y30  \n",
       "2024-05-01 2.6992% 2.6809% 2.6612% 2.6402% 2.6183%  \n",
       "2024-06-01 2.7071% 2.6891% 2.6694% 2.6483% 2.6260%  \n",
       "2024-07-01 2.7245% 2.7052% 2.6839% 2.6609% 2.6363%  \n",
       "\n",
       "[3 rows x 31 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mm_rates.columns.rename(euro_spot_rates.columns.name, inplace=True)\n",
    "mm_rates.rename(columns={'EA': '1 month'}, inplace=True)\n",
    "pd.concat([mm_rates, euro_spot_rates], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "acceptable-imperial",
   "metadata": {},
   "outputs": [],
   "source": [
    "date_now = euro_spot_rates.index[-1].date()\n",
    "date_1_mth_ago = date_now + relativedelta(months=-1)\n",
    "date_2_mth_ago = date_now + relativedelta(months=-2)\n",
    "offsets = [relativedelta(years=+maturity) for maturity in year_maturities]\n",
    "monthly_offsets = [relativedelta(), relativedelta(months=+1)] #, relativedelta(months=+3), relativedelta(months=+6)]\n",
    "offsets = monthly_offsets + offsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "consistent-situation",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define Euro yield curves\n",
    "curve = curves.YieldCurve(date_now, offsets, np.append(\n",
    "            np.append(ecb_deposit_rate.loc[str(mm_rates.index[-1])].to_numpy(), mm_rates.iloc[-1].to_numpy()),\n",
    "            euro_spot_rates.iloc[-1].to_numpy()), compounding_freq=0)\n",
    "curve_1_mth_ago = curves.YieldCurve(date_1_mth_ago, offsets, np.append(\n",
    "            np.append(ecb_deposit_rate[date_1_mth_ago:date_1_mth_ago+BDay()].to_numpy()[0,:], mm_rates[date_1_mth_ago:date_1_mth_ago+BDay()].to_numpy()[0,:]),\n",
    "            euro_spot_rates[date_1_mth_ago:date_1_mth_ago+BDay()].to_numpy()[0,:]), compounding_freq=0)\n",
    "curve_2_mth_ago = curves.YieldCurve(date_2_mth_ago, offsets, np.append(\n",
    "            np.append(ecb_deposit_rate[date_2_mth_ago:date_2_mth_ago+BDay()].to_numpy()[0,:], mm_rates[date_2_mth_ago:date_2_mth_ago+BDay()].to_numpy()[0,:]),\n",
    "            euro_spot_rates[date_2_mth_ago:date_2_mth_ago+BDay()].to_numpy()[0,:]), compounding_freq=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "destroyed-postage",
   "metadata": {},
   "outputs": [],
   "source": [
    "curve_points = curve.get_curve_points(120)\n",
    "curve_points_1_mth_ago = curve_1_mth_ago.get_curve_points(120)\n",
    "curve_points_2_mth_ago = curve_2_mth_ago.get_curve_points(120)\n",
    "curve_points.rename('Euro riskless rate', inplace=True)\n",
    "curve_points_1_mth_ago.rename(curve_points.name + ' (1 month prior)', inplace=True)\n",
    "curve_points_2_mth_ago.rename(curve_points.name + ' (2 months prior)', inplace=True)\n",
    "\n",
    "# Replacing indices for sake of better visualization\n",
    "curve_points_1_mth_ago = curve_points_1_mth_ago.set_axis(curve_points.index)\n",
    "curve_points_2_mth_ago = curve_points_2_mth_ago.set_axis(curve_points.index)\n",
    "df = pd.concat([curve_points, curve_points_1_mth_ago, curve_points_2_mth_ago], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "going-standard",
   "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>Euro riskless rate</th>\n",
       "      <th>Euro riskless rate (1 month prior)</th>\n",
       "      <th>Euro riskless rate (2 months prior)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-07-01</th>\n",
       "      <td>3.7416%</td>\n",
       "      <td>3.8314%</td>\n",
       "      <td>3.9862%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-01</th>\n",
       "      <td>3.4148%</td>\n",
       "      <td>3.3113%</td>\n",
       "      <td>3.5755%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025-01-01</th>\n",
       "      <td>3.2343%</td>\n",
       "      <td>3.1288%</td>\n",
       "      <td>3.3848%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025-04-03</th>\n",
       "      <td>3.1433%</td>\n",
       "      <td>3.1362%</td>\n",
       "      <td>3.3225%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025-07-04</th>\n",
       "      <td>3.0854%</td>\n",
       "      <td>3.1859%</td>\n",
       "      <td>3.2969%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2053-06-27</th>\n",
       "      <td>2.6611%</td>\n",
       "      <td>2.6486%</td>\n",
       "      <td>2.6404%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2053-09-27</th>\n",
       "      <td>2.6550%</td>\n",
       "      <td>2.6430%</td>\n",
       "      <td>2.6350%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2053-12-28</th>\n",
       "      <td>2.6489%</td>\n",
       "      <td>2.6374%</td>\n",
       "      <td>2.6295%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2054-03-31</th>\n",
       "      <td>2.6427%</td>\n",
       "      <td>2.6317%</td>\n",
       "      <td>2.6239%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2054-07-01</th>\n",
       "      <td>2.6363%</td>\n",
       "      <td>2.6260%</td>\n",
       "      <td>2.6183%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Euro riskless rate  Euro riskless rate (1 month prior)  \\\n",
       "2024-07-01             3.7416%                             3.8314%   \n",
       "2024-10-01             3.4148%                             3.3113%   \n",
       "2025-01-01             3.2343%                             3.1288%   \n",
       "2025-04-03             3.1433%                             3.1362%   \n",
       "2025-07-04             3.0854%                             3.1859%   \n",
       "...                        ...                                 ...   \n",
       "2053-06-27             2.6611%                             2.6486%   \n",
       "2053-09-27             2.6550%                             2.6430%   \n",
       "2053-12-28             2.6489%                             2.6374%   \n",
       "2054-03-31             2.6427%                             2.6317%   \n",
       "2054-07-01             2.6363%                             2.6260%   \n",
       "\n",
       "            Euro riskless rate (2 months prior)  \n",
       "2024-07-01                              3.9862%  \n",
       "2024-10-01                              3.5755%  \n",
       "2025-01-01                              3.3848%  \n",
       "2025-04-03                              3.3225%  \n",
       "2025-07-04                              3.2969%  \n",
       "...                                         ...  \n",
       "2053-06-27                              2.6404%  \n",
       "2053-09-27                              2.6350%  \n",
       "2053-12-28                              2.6295%  \n",
       "2054-03-31                              2.6239%  \n",
       "2054-07-01                              2.6183%  \n",
       "\n",
       "[120 rows x 3 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "conscious-gnome",
   "metadata": {},
   "source": [
    "#### Compounding frequency\n",
    "The rates presented throught this notebook use a continuous compounding frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "catholic-welcome",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.iloc[:,0:1].plot(figsize=(20,10), grid=True,\n",
    "             title='Euro Riskless Rate Curve over month ' + date_now.strftime('%Y-%m'),\n",
    "             xlim=(df.index[0], df.index[-1]), xticks=df.index[::4], xlabel='', rot=45)\n",
    "df.iloc[:,1:2].plot(ax=ax, grid=True, xticks=df.index[::4], rot=45, linestyle='--', color=['#1f77b4'])\n",
    "df.iloc[:,2:3].plot(ax=ax, grid=True, xticks=df.index[::4], rot=45, linestyle=':', color=['#1f77b4'])\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, df.index[::4])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "valued-baseline",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "An average shift of -1.95bps between 2024-07 and 2024-06 across maturities\n"
     ]
    }
   ],
   "source": [
    "print('An average shift of {:+.2f}bps between {:%Y-%m} and {:%Y-%m} across maturities'.format(\n",
    "    (df.iloc[:,0]-df.iloc[:,1]).mean() * 10000,\n",
    "    euro_spot_rates.index[-1].date(), euro_spot_rates.index[-2].date()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "sexual-house",
   "metadata": {},
   "outputs": [],
   "source": [
    "year_split = date(2033, 11, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "parliamentary-conflict",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "An average shift of -6.69bps between 2024-07 and 2024-06 for maturities up to 2033-11\n"
     ]
    }
   ],
   "source": [
    "print('An average shift of {:+.2f}bps between {:%Y-%m} and {:%Y-%m} for maturities up to {:%Y-%m}'.format(\n",
    "    (df.loc[:year_split,df.columns[0]]-df.loc[:year_split,df.columns[1]]).mean() * 10000,\n",
    "    euro_spot_rates.index[-1].date(), euro_spot_rates.index[-2].date(), year_split))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "fatty-crawford",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "An average shift of +0.24bp between 2024-07 and 2024-06 for maturities from 2033-11\n"
     ]
    }
   ],
   "source": [
    "print('An average shift of {:+.2f}bp between {:%Y-%m} and {:%Y-%m} for maturities from {:%Y-%m}'.format(\n",
    "    (df.loc[year_split:,df.columns[0]]-df.loc[year_split:,df.columns[1]]).mean() * 10000,\n",
    "    euro_spot_rates.index[-1].date(), euro_spot_rates.index[-2].date(), year_split))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "technological-convention",
   "metadata": {},
   "outputs": [],
   "source": [
    "offset_in_years = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "acting-mechanics",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average short-term (<3y) riskless yield: 3.02%\n"
     ]
    }
   ],
   "source": [
    "print('Average short-term (<{:d}y) riskless yield: {:.2%}'.format(offset_in_years,\n",
    "    df.loc[:(euro_spot_rates.index[-1].date()+relativedelta(years=+offset_in_years)),df.columns[0]].mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "damaged-composite",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average long-term (>3y) riskless yield: 2.64%\n"
     ]
    }
   ],
   "source": [
    "print('Average long-term (>{:d}y) riskless yield: {:.2%}'.format(offset_in_years,\n",
    "    df.loc[(euro_spot_rates.index[-1].date()+relativedelta(years=+offset_in_years)):,df.columns[0]].mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "greek-input",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Long-term (>3y) riskless yield: 2.39%-2.78%\n"
     ]
    }
   ],
   "source": [
    "print('Long-term (>{:d}y) riskless yield: {:.2%}-{:.2%}'.format(offset_in_years,\n",
    "    df.loc[(euro_spot_rates.index[-1].date()+relativedelta(years=+offset_in_years)):,df.columns[0]].min(),\n",
    "    df.loc[(euro_spot_rates.index[-1].date()+relativedelta(years=+offset_in_years)):,df.columns[0]].max()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "bizarre-mount",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Euro riskless rate   3.7416%\n",
       "dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,0:1].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "affiliated-fifth",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Euro riskless rate   2.3865%\n",
       "dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,0:1].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "loose-charles",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Euro riskless rate   2030-07-19\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,0:1].idxmin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "associate-polish",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.00018060000000000298"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[-1,0]-df.iloc[-1,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "instant-consequence",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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