Current_Riskfree_Rates.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "caroline-doctor",
   "metadata": {},
   "source": [
    "# Analysis of US Past, Present, and Future Riskless rates as represented by Fed Funds Rates and 10-Year Treasury Yields\n",
    "The Federal Funds Rate and 10-year Treasury Securities yield are used as short-term and long-term riskfree rates respectively. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. When a depository institution has surplus balances in its reserve account, it lends to other banks in need of larger balances.10-Year Treasury Yield indicates the rate at which U.S. Department of the Treasury can presently borrow from the public. \n",
    "\n",
    "There's a relationship between riskfree rates (e.g. 10-year Treasury rates) and CPI + real GDP growth rates. CPI + GDP growth rates is known as _the intrinsic riskfree rate_. In theory the 10-year Treasury rate should be similar to the intrinsic riskfree rate.\n",
    "\n",
    "In this notebook I first construct the current riskfree curve (based on the most recent US Treasury Yields of different maturities) as well as current real rates curve based on the most recent Treasury inflation protected security (TIPS) yields of different maturities. This allows to infer forward 10-year Treasury Yields later in this notebook.\n",
    "\n",
    "Unlike the [US CPI, Fed Funds Effective Rate, Market Yield on US Treasury Securities at 10-Year... notebook](https://github.com/ilchen/US_Economic_Data_Analysis/blob/main/CPI_and_Fed_Funds_Rates.ipynb) where I look at monthly changes in riskfree rates, expected inflation, and riskless curves, in this notebook I then concentrate on inferring future Fed Funds rates and 10-year Treasury Yields from the futures contracts traded on CME and depict the past, present, and future riskfree rates in one graph. For 10-year Treasury Yields I also use forward yields inferred from the earlier constructed  US Treasury Yield curve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "solved-groove",
   "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 pandas-datareader and yfinance\n",
    "# !pip install pandas-datareader -U\n",
    "# !pip install yfinance -U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "authentic-kernel",
   "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 BDay, MonthBegin, MonthEnd\n",
    "from dateutil.relativedelta import relativedelta\n",
    "from datetime import date\n",
    "import yfinance as yfin\n",
    "\n",
    "from pricing import curves, futures_rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "brief-agreement",
   "metadata": {},
   "outputs": [],
   "source": [
    "report_end = date.today()\n",
    "report_start = report_end - relativedelta(months=+28)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "institutional-template",
   "metadata": {},
   "outputs": [],
   "source": [
    "dff_tr10 = web.get_data_fred(['DFF', 'DGS10'], start=report_start, end=report_end) / 100."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "interstate-wells",
   "metadata": {},
   "source": [
    "## Current US Treasury and US Real Rates Curves\n",
    "In this part of the notebook I construct the US Treasury Yield curve based on the most recent market yields on U.S. Treasury Securities at different maturities published by [FRED](https://fred.stlouisfed.org). I also use this curve in the second half of the notebook to infer forward treasury yields. I use the Fed Funds effective rate as proxy for instantaneous riskless rate.\n",
    "\n",
    "\n",
    "I also constuct the most recent US Real Treasury yield curve. Real rates are yields on Treasury inflation protected security (TIPS). The reason they are called _real_ is because an investor in a TIPS security is automatically compensated for CPI inflation. That is the current yield on a TIPS security is the rate of return the investor is guaranteed to get when inflation is accounted for.\n",
    "\n",
    "Unfortunately the Fed only publishes TIPS yields for a limited set of constant maturities: 5 years, 7 years, 10 years, 20 years, and 30 years. In the following part of the notebook I constract the missing maturities for 1 and 2 years by subtracting the most recent expected inflation for 1 and 2 years from treasury yields of the same maturities. For the instant real rate I subtract the most recent CPI from the most recent Fed Funds rate.\n",
    "\n",
    "I use the following dataseries from [FRED](https://fred.stlouisfed.org) to accomplish the task for  Treasury Yield Curve construction:\n",
    "* DFF &mdash; Federal Funds Effective Rate (daily frequency)\n",
    "* DGS1MO &mdash;  Market Yield on U.S. Treasury Securities at 1-Month Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS3MO &mdash;  Market Yield on U.S. Treasury Securities at 3-Month Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS6MO &mdash; Market Yield on U.S. Treasury Securities at 6-Month Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS1 &mdash; Market Yield on U.S. Treasury Securities at 1-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* ...\n",
    "* DGS20 &mdash; Market Yield on U.S. Treasury Securities at 20-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS30 &mdash; Market Yield on U.S. Treasury Securities at 30-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "\n",
    "and additionally these series to construct the TIPS Real Yield curve:\n",
    "* CPIAUCSL &mdash; Consumer Price Index for All Urban Consumers, seasonally adjusted (monthly frequency)\n",
    "* EXPINF1YR &mdash; 1-Year Expected Inflation (monthly frequency)\n",
    "* EXPINF2YR &mdash; 2-Year Expected Inflation (monthly frequency)\n",
    "* DFII5 &mdash; Market Yield on U.S. Treasury Securities at 5-Year Constant Maturity, Quoted on an Investment Basis, Inflation-Indexed (daily frequency)\n",
    "* ...\n",
    "* DFII30 &mdash; Market Yield on U.S. Treasury Securities at 30-Year Constant Maturity, Quoted on an Investment Basis, Inflation-Indexed (daily frequency)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "alike-destruction",
   "metadata": {},
   "outputs": [],
   "source": [
    "today = date.today()\n",
    "\n",
    "# Constructing the riskless yield curve based on the current fed funds rate and treasury yields\n",
    "data = web.get_data_fred(\n",
    "    ['DFF', 'DGS1MO', 'DGS3MO', 'DGS6MO', 'DGS1', 'DGS2', 'DGS3', 'DGS5', 'DGS7', 'DGS10', 'DGS20', 'DGS30'],\n",
    "    today - relativedelta(weeks=+6) - BDay(2), today)\n",
    "data.dropna(inplace=True)\n",
    "\n",
    "cur_date_curve = data.index[-1].date()\n",
    "\n",
    "# Please choose an appropritate date in the past for comparison\n",
    "# delta = relativedelta(weeks=+1)\n",
    "delta = relativedelta(months=+1)\n",
    "# past_label = '1 week prior'\n",
    "past_label = '1 month prior'\n",
    "\n",
    "# Ensuring we go back to the last business day a week ago\n",
    "past_date = BDay(0).rollback(cur_date_curve - delta)\n",
    "\n",
    "# Convert to percentage points\n",
    "data /= 100.\n",
    "\n",
    "# Some adjustments are required to bring FED Funds rate to the same day count convention and compounding frequency\n",
    "# as treasury yields (actual/actual with semi-annual compounding):\n",
    "# 1. https://www.federalreserve.gov/releases/h15/default.htm -> day count convention for Fed Funds Rate needs\n",
    "# to be changed to actual/actual\n",
    "# 2. Conversion from annual to semi-annual compounding: https://home.treasury.gov/policy-issues/financing-the-government/interest-rate-statistics/interest-rates-frequently-asked-questions\n",
    "data.DFF *= (366 if curves.YieldCurve.is_leap_year(cur_date_curve.year) else 365) / 360 # to x/actual\n",
    "data.DFF = 2 * (np.sqrt(data.DFF + 1) - 1)\n",
    "\n",
    "offsets = [relativedelta(), relativedelta(months=+1), relativedelta(months=+3), relativedelta(months=+6),\n",
    "           relativedelta(years=+1), relativedelta(years=+2), relativedelta(years=+3), relativedelta(years=+5),\n",
    "           relativedelta(years=+7), relativedelta(years=+10), relativedelta(years=+20),\n",
    "           relativedelta(years=+30)]\n",
    "\n",
    "# Define the riskless yield curve\n",
    "curve = curves.YieldCurve(today, offsets, data[cur_date_curve:cur_date_curve + BDay()].to_numpy()[0, :],\n",
    "                          compounding_freq=2)\n",
    "past_curve = curves.YieldCurve(past_date, offsets,\n",
    "                               data[past_date:past_date+BDay()].to_numpy()[0,:], compounding_freq=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "outdoor-support",
   "metadata": {},
   "outputs": [],
   "source": [
    "real_rates = web.get_data_fred(['DFII5', 'DFII7', 'DFII10', 'DFII20', 'DFII30'],\n",
    "                               today - relativedelta(weeks=+6) - BDay(2), today) / 100.\n",
    "real_rates.dropna(inplace=True)\n",
    "\n",
    "# Infer real rates from the most recent expected inflation and current treasury yields\n",
    "expected_infl = web.get_data_fred(['EXPINF1YR', 'EXPINF2YR'], today - MonthBegin(2), today) / 100.\n",
    "\n",
    "# We need to convert expected inflation from annual to semi-annual compounding\n",
    "expected_infl = 2 * (np.sqrt(expected_infl + 1) - 1)\n",
    "\n",
    "real_rates_1y_2y = data.iloc[-1,[4,5]].set_axis(expected_infl.iloc[-1,:].index) - expected_infl.iloc[-1,:]\n",
    "real_rates.insert(0, 'DFII2', real_rates_1y_2y[1])\n",
    "real_rates.insert(0, 'DFII1', real_rates_1y_2y[0])\n",
    "\n",
    "# Infer the current real rate from the difference between most recent Fed Funds Rate and CPI\n",
    "cpi = web.get_data_fred('CPIAUCSL', today - MonthBegin(14), today).pct_change(12)\n",
    "\n",
    "# We need to convert cpi from annual to semi-annual compounding, as we did earlier for the fedfunds rate\n",
    "cpi = 2 * (np.sqrt(cpi + 1) - 1)\n",
    "\n",
    "real_rates.insert(0, 'INST', dff_tr10.iloc[-1,0]-cpi.iloc[-1,0])\n",
    "\n",
    "# Unfortunately fewer curve points for TIPS\n",
    "offsets_tips = [relativedelta(), relativedelta(years=+1), relativedelta(years=+2), relativedelta(years=+5),\n",
    "                relativedelta(years=+7), relativedelta(years=+10), relativedelta(years=+20), relativedelta(years=+30)]\n",
    "curve_real_rates = curves.YieldCurve(today, offsets_tips, real_rates[cur_date_curve:cur_date_curve + BDay()].to_numpy()[0, :],\n",
    "                                     compounding_freq=2)\n",
    "past_curve_real_rates = curves.YieldCurve(\n",
    "    today, offsets_tips, real_rates[past_date:past_date + BDay()].to_numpy()[0, :], compounding_freq=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "adverse-confidentiality",
   "metadata": {},
   "outputs": [],
   "source": [
    "curve_points = curve.get_curve_points(120)\n",
    "curve_points_past = past_curve.get_curve_points(120)\n",
    "curve_points.rename('US Treasury Yield', inplace=True)\n",
    "curve_points_past.rename(curve_points.name + f' ({past_label})', inplace=True)\n",
    "\n",
    "curve_points_real = curve_real_rates.get_curve_points(120)\n",
    "curve_points_real_past = past_curve_real_rates.get_curve_points(120)\n",
    "curve_points_real.rename('US TIPS (Real) Yield', inplace=True)\n",
    "curve_points_real_past.rename(curve_points_real.name + f' ({past_label})', inplace=True)\n",
    "\n",
    "# Replacing indices for sake of better visualization\n",
    "df = pd.concat([curve_points, curve_points_real, curve_points_past.set_axis(curve_points.index),\n",
    "                curve_points_real_past.set_axis(curve_points_real.index)], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "local-porter",
   "metadata": {},
   "outputs": [
    {
     "data": {
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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[:,:2].plot(figsize=(20,10), grid=True, title=f'US Treasury Yield Curve on {cur_date_curve:%Y-%m-%d}',\n",
    "                        xlim=(curve_points.index[0], curve_points.index[-1]),\n",
    "                        xticks=curve_points.index[::4], xlabel='', rot=45, ylim=(.01, .056))\n",
    "df.iloc[:,2:].plot(ax=ax, grid=True, xticks=df.index[::4], rot=45, linestyle='--', color=['#1f77b4', '#ff7f0e'])\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, curve_points.index[::4])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "rapid-savings",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Yield Curve on 2024-05-17 changed by an average of -14.99bps compared to 1 month prior\n",
      "The TIPS (Real) Curve on 2024-05-17 changed by an average of -9.54bps compared to 1 month prior\n"
     ]
    }
   ],
   "source": [
    "print('The Yield Curve on {:%Y-%m-%d} changed by an average of {:+.2f}bps compared to {:s}'\n",
    "      .format(data.index[-1].date(), 10000 * (df.iloc[:,0].mean() - df.iloc[:,2].mean()), past_label))\n",
    "print('The TIPS (Real) Curve on {:%Y-%m-%d} changed by an average of {:+.2f}bps compared to {:s}'\n",
    "      .format(data.index[-1].date(), 10000 * (df.iloc[:,1].mean() - df.iloc[:,3].mean()), past_label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "biblical-messaging",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For up till 10y the Yield Curve on 2024-05-17 changed by an average of -14.30bps compared to 1 month prior\n",
      "For up till 10y the TIPS (Real) Curve on 2024-05-17 changed by an average of -3.61bps compared 1 month prior\n"
     ]
    }
   ],
   "source": [
    "till = cur_date_curve + relativedelta(years=+10)\n",
    "print('For up till 10y the Yield Curve on {:%Y-%m-%d} changed by an average of {:.2f}bps compared to {:s}'\n",
    "      .format(data.index[-1].date(),\n",
    "              10000 * (df.loc[:till,df.columns[0]].mean() - df.loc[:till,df.columns[2]].mean()), past_label))\n",
    "print('For up till 10y the TIPS (Real) Curve on {:%Y-%m-%d} changed by an average of {:.2f}bps compared {:s}'\n",
    "      .format(data.index[-1].date(),\n",
    "              10000 * (df.loc[:till,df.columns[1]].mean() - df.loc[:till,df.columns[3]].mean()), past_label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "loving-somerset",
   "metadata": {},
   "outputs": [],
   "source": [
    "offset_in_years = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "widespread-conditioning",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average long-term (>3y) treasury yield: 4.56%\n"
     ]
    }
   ],
   "source": [
    "print('Average long-term (>{:d}y) treasury yield: {:.2%}'.format(offset_in_years,\n",
    "    df.loc[(data.index[-1].date()+relativedelta(years=+3)):,df.columns[0]].mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "blank-family",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Long-term (>3y) treasury yield: 4.42%-4.73%\n"
     ]
    }
   ],
   "source": [
    "print('Long-term (>{:d}y) treasury yield: {:.2%}-{:.2%}'.format(offset_in_years,\n",
    "    curve_points.loc[(data.index[-1].date()+relativedelta(years=+offset_in_years)):].min(),\n",
    "    curve_points.loc[(data.index[-1].date()+relativedelta(years=+offset_in_years)):].max()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "thick-relief",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average long-term (>3y) real yield: 2.15%\n"
     ]
    }
   ],
   "source": [
    "print('Average long-term (>3y) real yield: {:.2%}'.format(\n",
    "    df.loc[(data.index[-1].date()+relativedelta(years=+3)):,df.columns[1]].mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "assumed-treasurer",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Long-term (>3y) real yield: 2.07%-2.23%\n"
     ]
    }
   ],
   "source": [
    "print('Long-term (>{:d}y) real yield: {:.2%}-{:.2%}'.format(offset_in_years,\n",
    "    curve_points_real.loc[(data.index[-1].date()+relativedelta(years=+offset_in_years)):].min(),\n",
    "    curve_points_real.loc[(data.index[-1].date()+relativedelta(years=+offset_in_years)):].max()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pressed-rings",
   "metadata": {},
   "source": [
    "## Past, Present, and Future: Fed Funds Rates and 10-year Treasury Yields\n",
    "I obtain future Fed Funds Rates and 10-year Treasury Yields from the following futures contracts traded on CME:\n",
    "* [30 Day Federal Funds](https://www.cmegroup.com/markets/interest-rates/stirs/30-day-federal-fund.html) futures contracts, and\n",
    "* [10 Year T-Note](https://www.cmegroup.com/markets/interest-rates/us-treasury/10-year-us-treasury-note.html) futures contracts<sup>1</sup>.\n",
    "I use helper classes `CMEFedFundsFuturesRates` and `CME10YearTNoteFuturesYields` from the `pricing.futures_rates` package to do the heavy lifting.\n",
    "\n",
    "CME allows for a variety of maturities of Treasury notes to be delivered during a 10-Year Treasury Note futures contract's final settlement. In particular Treasury notes with maturities starting from 6.5 years can be delivered. Therefore future yields deduced from these contracts are but a rough approximation of future 10-year Treasury Yields. Therefore in below I use them only for reference. As the main representation of future 10-year Treasury Yields, I use forward treasury yields obtained from the Treasury Yield curve I've constructed in the first half of this notebook. I calculate forward treasury yield for each future month based on the first business day from the month's middle.\n",
    "\n",
    "I retrieve the past and current riskfree rates from the following dataseries provided by [FRED](https://fred.stlouisfed.org):\n",
    "* DFF &mdash; Federal Funds Effective Rate (daily frequency)\n",
    "* DGS10 &mdash; Market Yield on U.S. Treasury Securities at 10-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "\n",
    "[1] Unfortunately only the contracts for the next two quarters are actively traded for [this instrument](https://www.cmegroup.com/markets/interest-rates/us-treasury/10-year-us-treasury-note.quotes.html) on CME. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "smaller-certificate",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Resampling to monthly frequencies by taking the average for each month,\n",
    "# but using the last price for the current month\n",
    "ff_tr10 = pd.concat([dff_tr10.loc[:report_end - MonthEnd(2)].resample('MS').mean(),\n",
    "                     dff_tr10.loc[report_end - MonthEnd(2) + BDay():].resample('MS').last()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "dramatic-bankruptcy",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  16 of 16 completed\n",
      "[*********************100%%**********************]  3 of 3 completed\n",
      "[**********************69%%*******               ]  11 of 16 completed"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Objective function: -0.00048 after 18 iterations\n",
      "Objective function: -0.00134 after 19 iterations\n",
      "Objective function: -0.00011 after 18 iterations\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  16 of 16 completed\n",
      "[*********************100%%**********************]  3 of 3 completed"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Objective function: -0.00061 after 16 iterations\n",
      "Objective function: -0.00079 after 15 iterations\n",
      "Objective function: -0.00083 after 15 iterations\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# A kludge for pandas-datareader not being able to cope with latest Yahoo-Finance changes\n",
    "yfin.pdr_override()\n",
    "\n",
    "# Inferring future Fed Funds and 10 Year Treasury Note yields for the futures contracts traded on CME\n",
    "inferrer_ff_rates = futures_rates.CMEFedFundsFuturesRates(cur_date_curve)\n",
    "inferrer_tnote_yields = futures_rates.CME10YearTNoteFuturesYields(cur_date_curve)\n",
    "ff_rates = inferrer_ff_rates.get_rates_for_next_n_months(16)\n",
    "tr10_yields = inferrer_tnote_yields.get_yields_for_next_n_quarters(3)\n",
    "\n",
    "ff_rates_past = inferrer_ff_rates.get_rates_for_next_n_months(16, past_date)\n",
    "tr10_yields_past = inferrer_tnote_yields.get_yields_for_next_n_quarters(3, past_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "developmental-communist",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating forward treasury yields from the earlier constructed Treasury Yield Curves\n",
    "term = relativedelta(years=+10)\n",
    "\n",
    "def to_forward_yield(forward_date, fn):\n",
    "    forward_date = forward_date + relativedelta(weeks=+2) + BDay(0)\n",
    "    return fn(forward_date, forward_date + term)[0]\n",
    "\n",
    "from functools import partial\n",
    "\n",
    "forward_tr10_yields = ff_rates.index.to_series().apply(\n",
    "    partial(to_forward_yield, fn=curve.get_forward_yield_for_maturity_date))\n",
    "forward_tr10_yields_past = ff_rates.index.to_series().apply(\n",
    "    partial(to_forward_yield, fn=past_curve.get_forward_yield_for_maturity_date))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "improved-connectivity",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Renaming the future Fed Funds and T-Note series to have the same name as those retrieved earlier\n",
    "ff_rates.rename(ff_tr10.columns[0], inplace=True)\n",
    "#tr10_yields.rename(ff_tr10.columns[1], inplace=True)\n",
    "forward_tr10_yields.rename(ff_tr10.columns[1], inplace=True)\n",
    "\n",
    "# Concatenating future rates and yields into a DataFrame\n",
    "future_rates = pd.concat([ff_rates, forward_tr10_yields], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "continental-printer",
   "metadata": {},
   "outputs": [],
   "source": [
    "# And now merging the past, current, and future rates/yields \n",
    "ext_ff_tr10 = pd.concat([ff_tr10, future_rates])\n",
    "ext_ff_tr10.rename(\n",
    "    columns={'DFF': 'Federal Funds Effective Rate',\n",
    "             'DGS10': '10y Treasury Yield'},\n",
    "    inplace=True)\n",
    "\n",
    "PAST_DATE = f' ({past_label})'\n",
    "FROM_FUTURES = ' (inferred from futures)'\n",
    "FROM_FUTURES_PAST_DATE = f' (inferred from futures, {past_label})'\n",
    "\n",
    "ff_rates.rename(ext_ff_tr10.columns[0] + FROM_FUTURES, inplace=True)\n",
    "ff_rates_past = pd.concat([ff_rates_past, ff_tr10.DFF.iloc[-1:]]).sort_index()\n",
    "ff_rates_past.rename(ext_ff_tr10.columns[0] + FROM_FUTURES_PAST_DATE, inplace=True)\n",
    "forward_tr10_yields.rename('Forward 10y Treasury Yield', inplace=True)\n",
    "forward_tr10_yields_past = pd.concat([forward_tr10_yields_past, ff_tr10.DGS10.iloc[-1:]]).sort_index()\n",
    "forward_tr10_yields_past.rename(forward_tr10_yields.name + PAST_DATE, inplace=True)\n",
    "#tr10_yields_ = pd.concat([tr10_yields, ff_tr10.DGS10.iloc[-1:]]).sort_index()\n",
    "tr10_yields.rename(ext_ff_tr10.columns[1] + FROM_FUTURES, inplace=True)\n",
    "tr10_yields_past.rename(ext_ff_tr10.columns[1] + FROM_FUTURES_PAST_DATE, inplace=True)\n",
    "\n",
    "ext2_ff_tr10 = pd.concat([ff_rates, forward_tr10_yields, ff_rates_past, forward_tr10_yields_past], axis=1)\n",
    "\n",
    "ext2_tr10 = pd.concat([tr10_yields, tr10_yields_past], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "pressing-zambia",
   "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 = ext_ff_tr10.plot(figsize=(20,10), grid=True,\n",
    "                      title=f'US Past, Current, and Future (as of {cur_date_curve:%Y-%m-%d}) Fed Funds Rate and 10y Treasury Yield',\n",
    "                      xticks=ext_ff_tr10.index, xlabel='', rot=45)\n",
    "ext2_ff_tr10.iloc[:,:2].plot(ax=ax, grid=True, marker='o', xticks=ext_ff_tr10.index, xlabel='',\n",
    "              rot=45, yticks=np.arange(0, .06, 0.01), color=['#1f77b4','#ff7f0e'])\n",
    "ext2_ff_tr10.iloc[:,2:].plot(ax=ax, grid=True, marker='.', linestyle='--', xticks=ext_ff_tr10.index, xlabel='',\n",
    "              rot=45, yticks=np.arange(0, .06, 0.005), color=['#1f77b4','#ff7f0e'])\n",
    "# ext2_tr10.iloc[:,:1].plot(ax=ax, grid=True, marker='v', linestyle='none', xticks=ext_ff_tr10.index, xlabel='',\n",
    "#               rot=45, yticks=np.arange(0, .06, 0.01), color='#ff7f0e')\n",
    "# ext2_tr10.iloc[:,1:].plot(ax=ax, grid=True, marker='^', linestyle='none', xticks=ext_ff_tr10.index, xlabel='',\n",
    "#               rot=45, yticks=np.arange(0, .06, 0.005), color='#ff7f0e')\n",
    "ax.legend()\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, ext_ff_tr10.index)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "incomplete-exchange",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forward 10y treasury yield in 2025-09: 4.36%\n"
     ]
    }
   ],
   "source": [
    "print('Forward 10y treasury yield in {:%Y-%m}: {:.2%}'.format(ext2_ff_tr10.index[-1], ext2_ff_tr10.iloc[-1, 1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "proof-peeing",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forward 10y treasury yield in 2025-09 changed by -17.77bps compared to 1 month prior\n"
     ]
    }
   ],
   "source": [
    "print('Forward 10y treasury yield in {:%Y-%m} changed by {:+.2f}bps compared to {:s}'.format(\n",
    "    ext2_ff_tr10.index[-1], (ext2_ff_tr10.iloc[-1, 1] - ext2_ff_tr10.iloc[-1, 3]) * 10000, past_label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cheap-barbados",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forward 10y treasury yield for maturities up to 2025-09 changed by an average of -16.65bps\n"
     ]
    }
   ],
   "source": [
    "print('Forward 10y treasury yield for maturities up to {:%Y-%m} changed by an average of {:+.2f}bps'.format(\n",
    "    ext2_ff_tr10.index[-1],\n",
    "    (ext2_ff_tr10.iloc[:, 1].mean() - ext2_ff_tr10.iloc[:, 3].mean()) * 10000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "listed-behalf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Futures markets are expecting the Fed Funds rate to be at 4.28% in 2025-09\n"
     ]
    }
   ],
   "source": [
    "print('Futures markets are expecting the Fed Funds rate to be at {:.2%} in {:%Y-%m}'\n",
    "      .format(ext2_ff_tr10.iloc[-1,0], ext2_ff_tr10.index[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "soviet-chart",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Markets are expecting Fed Funds rate to be -18.9995bps in 2025-09 compared to 1 month prior\n"
     ]
    }
   ],
   "source": [
    "print('Markets are expecting Fed Funds rate to be {:+.4f}bps in {:%Y-%m} compared to {:s}'.\n",
    "      format((ext2_ff_tr10.iloc[-1,0]-ext2_ff_tr10.iloc[-1,2])*10000, ext2_ff_tr10.index[-1].date(), past_label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "sharing-balance",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Future 10y treasury yield for 2024-12 changed by -26.60bps\n"
     ]
    }
   ],
   "source": [
    "print('Future 10y treasury yield for {:%Y-%m} changed by {:.2f}bps'.format(\n",
    "    ext2_tr10.index[-1].date(), (ext2_tr10.iloc[-1, 0] - ext2_tr10.iloc[-1, 1]) * 10000))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "martial-berlin",
   "metadata": {},
   "source": [
    "## Past, Present, and Future: Fed Funds Rates and 3-month Treasury Yields\n",
    "In his 30<sup>th</sup> January, 2023 [blog post](https://aswathdamodaran.blogspot.com/2023/01/data-update-3-for-2023-inflation-and.html) Aswath Damodaran made a point about the putative powers of the Fed that it may well not have:\n",
    "> There is no \"interest rate room\" in the Fed, where the Fed chair or FOMC committee, move the levers to set treasury or mortgage rates. The only rate that the Fed does set is the Fed Funds rate, and it is true that you have seen that rate jump from close to zero to just above 4% in 2022. Before you feel the urge to say \"I told you so\", take a look at US treasury rates (3-month and 10-year) on this graph, in relation to the Fed Funds rate, and make your own judgment on whether the rates climb after the Fed hikes the Fed Funds rate (which would you be your working hypothesis if the Fed sets rates) or if the Fed hikes rates in response to market rates going up.\n",
    "\n",
    "In this part of the notebook I extend the analysis to future Fed Funds Rates and forward 3-month Treasury yields.\n",
    "\n",
    "I obtain future Fed Funds Rates and 10-year Treasury Yields from the following futures contracts traded on CME:\n",
    "* [30 Day Federal Funds](https://www.cmegroup.com/markets/interest-rates/stirs/30-day-federal-fund.html) futures contracts, and\n",
    "I use the helper class `CMEFedFundsFuturesRates` from the `pricing.futures_rates` package to do the heavy lifting.\n",
    "\n",
    "I retrieve the past and current riskfree rates from the following dataseries provided by [FRED](https://fred.stlouisfed.org):\n",
    "* DFF &mdash; Federal Funds Effective Rate (daily frequency)\n",
    "* DGS3MO &mdash; Market Yield on U.S. Treasury Securities at 3-Month Constant Maturity, Quoted on an Investment Basis (daily frequency)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "worth-ottawa",
   "metadata": {},
   "outputs": [],
   "source": [
    "tr3m = web.get_data_fred('DGS3MO', start=report_start, end=report_end) / 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "beautiful-optimum",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Resampling to monthly frequencies by taking the average for each month,\n",
    "# but using the last price for the current month\n",
    "tr3m = pd.concat([tr3m.loc[:report_end - MonthEnd(2)].resample('MS').mean(),\n",
    "                  tr3m.loc[report_end - MonthEnd(2) + BDay():].resample('MS').last()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "under-praise",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating forward treasury yields from the earlier constructed Treasury Yield Curves\n",
    "term = relativedelta(months=+3)\n",
    "\n",
    "forward_tr3m_yields = ff_rates.index.to_series().apply(\n",
    "    partial(to_forward_yield, fn=curve.get_forward_yield_for_maturity_date))\n",
    "forward_tr3m_yields_past = ff_rates.index.to_series().apply(\n",
    "    partial(to_forward_yield, fn=past_curve.get_forward_yield_for_maturity_date))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "unsigned-subject",
   "metadata": {},
   "outputs": [],
   "source": [
    "forward_tr3m_yields.rename(tr3m.columns[0], inplace=True)\n",
    "# Concatenating future rates and yields into a DataFrame\n",
    "future_ff_tr3m_rates = pd.concat([ff_rates.rename(ff_tr10.DFF.name), forward_tr3m_yields], axis=1)\n",
    "ff_tr3m = pd.concat([ff_tr10.DFF, tr3m.DGS3MO], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "mature-pioneer",
   "metadata": {},
   "outputs": [],
   "source": [
    "# And now merging the past, current, and future rates/yields \n",
    "ext_ff_tr3m = pd.concat([ff_tr3m, future_ff_tr3m_rates])\n",
    "ext_ff_tr3m.rename(\n",
    "    columns={'DFF': 'Federal Funds Effective Rate',\n",
    "             'DGS3MO': '3m Treasury Yield'},\n",
    "    inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "likely-convention",
   "metadata": {},
   "outputs": [],
   "source": [
    "ff_rates.rename(ext_ff_tr10.columns[0] + FROM_FUTURES, inplace=True)\n",
    "forward_tr3m_yields.rename('Forward 3m Treasury Yield', inplace=True)\n",
    "forward_tr3m_yields_past = pd.concat([forward_tr3m_yields_past, tr3m.DGS3MO.iloc[-1:]]).sort_index()\n",
    "forward_tr3m_yields_past.rename(forward_tr3m_yields.name + PAST_DATE, inplace=True)\n",
    "\n",
    "ext2_ff_tr3m = pd.concat([ff_rates, forward_tr3m_yields, ff_rates_past, forward_tr3m_yields_past], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "floral-number",
   "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 = ext_ff_tr3m.plot(figsize=(20,10), grid=True,\n",
    "                      title=f'US Past, Current, and Future (as of {cur_date_curve:%Y-%m-%d}) Fed Funds Rate and 3m Treasury Yield',\n",
    "                      xticks=ext_ff_tr3m.index, xlabel='', rot=45)\n",
    "ext2_ff_tr3m.iloc[:,:2].plot(ax=ax, grid=True, marker='o', xticks=ext_ff_tr3m.index, xlabel='',\n",
    "              rot=45, yticks=np.arange(0, .06, 0.005), color=['#1f77b4','#ff7f0e'])\n",
    "# ext2_ff_tr3m.iloc[:,2:].plot(ax=ax, grid=True, marker='.', linestyle='--', xticks=ext_ff_tr3m.index, xlabel='',\n",
    "#               rot=45, yticks=np.arange(0, .06, 0.005), color=['#1f77b4','#ff7f0e'])\n",
    "ax.legend(loc='upper left')\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "_ = ax.set_xticklabels(list(map('{:%Y-%m}'.format, ext_ff_tr3m.index)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abroad-verse",
   "metadata": {},
   "source": [
    "Let's see in which month the divergence between future Fed Funds and 3 month trasury yield is the highest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "compatible-testing",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Markets are expecting 3m treasury yield to be 26.05bps higher than Fed Funds rate in 2025-09\n"
     ]
    }
   ],
   "source": [
    "idx = (future_ff_tr3m_rates.iloc[:, 0] - future_ff_tr3m_rates.iloc[:, 1]).abs().idxmax()\n",
    "print('Markets are expecting 3m treasury yield to be {:.2f}bps higher than Fed Funds rate in {:%Y-%m}'.\n",
    "      format((ext_ff_tr3m.loc[idx, ext_ff_tr3m.columns[1]] - ext_ff_tr3m.loc[idx, ext_ff_tr3m.columns[0]])*10000,\n",
    "             idx.date()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fabulous-uzbekistan",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}