{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](../images/logo.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Deposits and FRAs "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-05-03T11:41:34.601266Z",
     "start_time": "2020-05-03T11:41:28.386153Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\GunnarSalentin\\OneDrive - RIVACON GmbH\\Dokumente\\git\\RiVaPy\\rivapy\\__init__.py:11: UserWarning: The pyvacon module is not available. You may not use all functionality without this module. Consider installing pyvacon.\n",
      "  warnings.warn('The pyvacon module is not available. You may not use all functionality without this module. Consider installing pyvacon.')\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import math\n",
    "from dateutil.relativedelta import relativedelta\n",
    "import datetime as dt\n",
    "from rivapy.tools._validators import print_member_values\n",
    "\n",
    "from rivapy.marketdata import DiscountCurve\n",
    "from rivapy.instruments import DepositSpecification, ForwardRateAgreementSpecification\n",
    "from rivapy.pricing import price\n",
    "\n",
    "from rivapy.tools.enums import DayCounterType, InterpolationType, ExtrapolationType\n",
    "\n",
    "from rivapy.pricing.pricing_data import DepositPricingData, ForwardRateAgreementPricingData\n",
    "from rivapy.pricing.pricing_request import  ForwardRateAgreementPricingRequest\n",
    "from rivapy.pricing.pricing_request import DepositPricingRequest\n",
    "from rivapy.pricing.bond_pricing import DeterministicCashflowPricer\n",
    "from rivapy.pricing.deposit_pricing import DepositPricer\n",
    "from rivapy.pricing.fra_pricing import ForwardRateAgreementPricer\n",
    "from rivapy.tools.datetools import _term_to_period, DayCounter, roll_day\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from matplotlib.dates import date2num, DateFormatter\n",
    "from rivapy.tools.visualization import plot_deposit, plot_fra\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Definition of a deposit\n",
    "\n",
    "A deposit is simply a short-term bond where at the start date the lender pays the nominal amount $N$ to the borrower, and at maturity plus settlement days (i.e. the payment date) the borrower pays back the nominal amount plus the accrued interest. Interest is usually expressed using simple compounding, i.e. the amount paid back at the payment date is $N \\cdot (1 + r \\cdot \\tau)$ where $r$ is the interest rate and $\\tau$ is the year fraction between start and end date. \\\n",
    "Deposits can be setup in RIVAPY by providing start and end dates directly or by providing a start date and a term. Other instrument specific dates, e.g. fixing date, end date, or maturity date can be passed explicitly when setting up the instrument or will be derived from default values, e.g. spot_days of 2 days, and business day convention.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Number of annual payments is not a whole number but a decimal.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inspecting instance of DepositSpecification:\n",
      "\n",
      "accrual_dates: [datetime.datetime(2023, 1, 2, 0, 0), datetime.datetime(2024, 1, 26, 0, 0)]\n",
      "adjust_accruals: True\n",
      "adjust_end_date: False\n",
      "adjust_schedule: True\n",
      "adjust_start_date: True\n",
      "backwards: True\n",
      "business_day_convention: ModifiedFollowing\n",
      "calendar: {datetime.date(2023, 1, 1): \"New Year's Day\", datetime.date(2023, 4, 7): 'Good Friday', datetime.date(2023, 4, 10): 'Easter Monday', datetime.date(2023, 5, 1): 'Labour Day', datetime.date(2023, 12, 25): 'Christmas Day', datetime.date(2023, 12, 26): 'Christmas Holiday', datetime.date(2024, 1, 1): \"New Year's Day\", datetime.date(2024, 3, 29): 'Good Friday', datetime.date(2024, 4, 1): 'Easter Monday', datetime.date(2024, 5, 1): 'Labour Day', datetime.date(2024, 12, 25): 'Christmas Day', datetime.date(2024, 12, 26): 'Christmas Holiday'}\n",
      "coupon: 0.03\n",
      "coupon_type: fix\n",
      "currency: EUR\n",
      "dates: [datetime.datetime(2023, 1, 2, 0, 0), datetime.datetime(2024, 1, 26, 0, 0)]\n",
      "day_count_convention: Act360\n",
      "end_date: 2024-01-26 00:00:00\n",
      "frequency: 389D\n",
      "index: None\n",
      "ir_index: None\n",
      "issue_date: 2023-01-02 00:00:00\n",
      "issue_price: None\n",
      "issuer: \n",
      "last_fixing: None\n",
      "maturity_date: 2024-01-26 00:00:00\n",
      "notional: <rivapy.instruments.components.ConstNotionalStructure object at 0x000001A23C0E75F0>\n",
      "notional_exchange: True\n",
      "nr_annual_payments: 0.9383033419023136\n",
      "obj_id: dummy_id\n",
      "payment_days: 5\n",
      "pays_in_arrears: True\n",
      "rate: 0.03\n",
      "rating: NONE\n",
      "roll_convention: NONE\n",
      "schedule: <rivapy.tools.datetools.Schedule object at 0x000001A23C2DF620>\n",
      "securitization_level: NONE\n",
      "spot_days: 5\n",
      "start_date: 2023-01-02 00:00:00\n",
      "stub_type_is_Long: True\n",
      "Schedule details:\n",
      "2023-01-02\n",
      "2024-01-26\n"
     ]
    }
   ],
   "source": [
    "# Set up deposit specification\n",
    "ccy = 'EUR'\n",
    "ref_date = dt.datetime(2023, 1, 2)\n",
    "issue_date = ref_date\n",
    "maturity_date = dt.datetime(2024, 1, 26)\n",
    "dcc = 'Act360'\n",
    "rate = .03\n",
    "notional = 100.\n",
    "deposit_spec = DepositSpecification(\n",
    "    obj_id='dummy_id',\n",
    "    issuer=\"\",\n",
    "    currency=ccy,\n",
    "    issue_date=issue_date,\n",
    "    maturity_date=maturity_date,\n",
    "    notional=notional,\n",
    "    rate=rate,\n",
    "    day_count_convention=dcc,\n",
    "    roll_convention='NONE', \n",
    "    payment_days = 5,\n",
    "    spot_days = 5\n",
    ")\n",
    "print_member_values(deposit_spec)\n",
    "\n",
    "schedule = deposit_spec.get_schedule()\n",
    "print(\"Schedule details:\")\n",
    "dates = schedule._roll_out(\n",
    "    from_=schedule.start_day,\n",
    "    to_=schedule.end_day,\n",
    "    term=schedule.time_period,\n",
    "    ref_date=ref_date\n",
    ")\n",
    "for date in dates:\n",
    "    print(date.strftime(\"%Y-%m-%d\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "End dates of notional structure are not set.\n",
      "End dates of notional structure are not set.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cashflows: [(datetime.datetime(2023, 1, 2, 0, 0), -100.0), (datetime.datetime(2024, 1, 31, 0, 0), 3.2416666666666663), (datetime.datetime(2024, 1, 31, 0, 0), 100.0)]\n",
      "\n",
      "Pricing deposit:\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cf = DepositPricer.get_expected_cashflows(deposit_spec)\n",
    "print(f\"Cashflows: {cf}\")\n",
    "print(\"\\nPricing deposit:\")\n",
    "# add timeline plot\n",
    "fig = plot_deposit(deposit_spec, ref_date)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inspecting instance of DepositSpecification:\n",
      "\n",
      "accrual_dates: [datetime.datetime(2023, 1, 2, 0, 0), datetime.datetime(2023, 4, 3, 0, 0)]\n",
      "adjust_accruals: True\n",
      "adjust_end_date: False\n",
      "adjust_schedule: True\n",
      "adjust_start_date: True\n",
      "backwards: True\n",
      "business_day_convention: ModifiedFollowing\n",
      "calendar: {datetime.date(2023, 1, 1): \"New Year's Day\", datetime.date(2023, 4, 7): 'Good Friday', datetime.date(2023, 4, 10): 'Easter Monday', datetime.date(2023, 5, 1): 'Labour Day', datetime.date(2023, 12, 25): 'Christmas Day', datetime.date(2023, 12, 26): 'Christmas Holiday', datetime.date(2024, 1, 1): \"New Year's Day\", datetime.date(2024, 3, 29): 'Good Friday', datetime.date(2024, 4, 1): 'Easter Monday', datetime.date(2024, 5, 1): 'Labour Day', datetime.date(2024, 12, 25): 'Christmas Day', datetime.date(2024, 12, 26): 'Christmas Holiday', datetime.date(2021, 1, 1): \"New Year's Day\", datetime.date(2021, 4, 2): 'Good Friday', datetime.date(2021, 4, 5): 'Easter Monday', datetime.date(2021, 5, 1): 'Labour Day', datetime.date(2021, 12, 25): 'Christmas Day', datetime.date(2021, 12, 26): 'Christmas Holiday'}\n",
      "coupon: 0.03\n",
      "coupon_type: fix\n",
      "currency: EUR\n",
      "dates: [datetime.datetime(2023, 1, 2, 0, 0), datetime.datetime(2023, 4, 3, 0, 0)]\n",
      "day_count_convention: Act360\n",
      "end_date: 2023-04-02 00:00:00\n",
      "frequency: 3M\n",
      "index: None\n",
      "ir_index: None\n",
      "issue_date: 2023-01-02 00:00:00\n",
      "issue_price: None\n",
      "issuer: \n",
      "last_fixing: None\n",
      "maturity_date: 2023-04-03 00:00:00\n",
      "notional: <rivapy.instruments.components.ConstNotionalStructure object at 0x000001A23C727B90>\n",
      "notional_exchange: True\n",
      "nr_annual_payments: 4.0\n",
      "obj_id: dummy_id\n",
      "payment_days: 0\n",
      "pays_in_arrears: True\n",
      "rate: 0.03\n",
      "rating: NONE\n",
      "roll_convention: NONE\n",
      "schedule: <rivapy.tools.datetools.Schedule object at 0x000001A23C580710>\n",
      "securitization_level: NONE\n",
      "spot_days: 2\n",
      "start_date: 2023-01-02 00:00:00\n",
      "stub_type_is_Long: True\n"
     ]
    }
   ],
   "source": [
    "term = \"3M\"\n",
    "deposit_spec_3M = DepositSpecification(\n",
    "    obj_id='dummy_id',\n",
    "    issuer=\"\",\n",
    "    currency=ccy,\n",
    "    issue_date=ref_date,\n",
    "    term=term,\n",
    "    notional=notional,\n",
    "    rate=rate,\n",
    "    day_count_convention=dcc,\n",
    "    roll_convention='NONE',  # explicitly pass as string\n",
    "    payment_days=0\n",
    ")\n",
    "print_member_values(deposit_spec_3M)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up (flat) rate curve\n",
    "object_id = \"TEST_CURVE\"\n",
    "flat_rate = 0.025\n",
    "\n",
    "days_to_maturity = [1, 180, 365, 720, 3 * 365, 4 * 365, 10 * 365]\n",
    "dates = [ref_date + dt.timedelta(days=d) for d in days_to_maturity]\n",
    "\n",
    "df = [math.exp(-d / 365.0 * flat_rate) for d in days_to_maturity]\n",
    "dc = DiscountCurve(id=object_id, refdate=ref_date, dates=dates, df=df, interpolation = InterpolationType.LINEAR, extrapolation=ExtrapolationType.LINEAR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "End dates of notional structure are not set.\n",
      "End dates of notional structure are not set.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Expected Cashflows: [(datetime.datetime(2023, 1, 2, 0, 0), -100.0), (datetime.datetime(2024, 1, 31, 0, 0), 3.2416666666666663), (datetime.datetime(2024, 1, 31, 0, 0), 100.0)]\n",
      "Price Deposit: 100.4950269333136\n",
      "fair rate: 0.024971370182974097\n",
      "fair deposit coupon: 0.024971370182974097\n"
     ]
    }
   ],
   "source": [
    "# price deposit\n",
    "print (f\"Expected Cashflows: {DeterministicCashflowPricer.get_expected_cashflows(deposit_spec,ref_date)}\")\n",
    "print(f\"Price Deposit: {DepositPricer.get_price(ref_date, deposit_spec, dc)}\")\n",
    "\n",
    "# Determine fair rate\n",
    "fair_rate = DepositPricer.get_implied_simply_compounded_rate(ref_date, deposit_spec, dc)\n",
    "print(f\"fair rate: {fair_rate}\")\n",
    "\n",
    "# new deposit with fair rate\n",
    "fair_deposit_spec = DepositSpecification(obj_id ='dummy_id', issuer='dummy_issuer', securitization_level ='NONE', \n",
    "                                    currency=ccy, issue_date=ref_date, maturity_date=deposit_spec.end_date, notional=deposit_spec.notional, rate=fair_rate, \n",
    "                                    day_count_convention=deposit_spec.day_count_convention, payment_days=deposit_spec.payment_days, spot_days=deposit_spec.spot_days)\n",
    "#print_member_values(fair_deposit_spec)\n",
    "print(f\"fair deposit coupon: {fair_deposit_spec.coupon}\")\n",
    "#print(DepositPricer.get_price(ref_date, fair_deposit_spec, dc)) \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fair_deposit_spec.start_date: 2023-01-02 00:00:00, fair_deposit_spec.end_date: 2024-01-26 00:00:00\n",
      "0.9737259973907282\n",
      "0.9737259973907281\n"
     ]
    }
   ],
   "source": [
    "# Check fair rate\n",
    "# discount factor from curve\n",
    "print(f\"fair_deposit_spec.start_date: {fair_deposit_spec.start_date}, fair_deposit_spec.end_date: {fair_deposit_spec.end_date}\")\n",
    "df_curve = dc.value_fwd(ref_date, fair_deposit_spec.start_date, fair_deposit_spec.end_date)\n",
    "# discount factor implied by fair rate (simple compounding, Act/360)\n",
    "dcc = DayCounter(fair_deposit_spec.day_count_convention)\n",
    "#print(f\"day count convention: {fair_deposit_spec.day_count_convention}\")\n",
    "delta_t = dcc.yf(fair_deposit_spec.start_date, fair_deposit_spec.end_date)\n",
    "df_implied = 1. / (1. + delta_t * fair_rate)\n",
    "#print(f\"Discount factor from curve: {df_curve}, Delta t: {delta_t}, Implied DF: {df_implied}, dcc: {dcc}\")\n",
    "print(df_curve)\n",
    "print(df_implied)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The deposit's cashflows including relevant dates are shown below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Found start date 2022-10-02 00:00:00 such that calc_end_day(start_date, ...) == end_day, but start date is not a business day in the given calendar.\n",
      "End dates of notional structure are not set.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_deposit(deposit_spec_3M, ref_date)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-05-03T11:41:34.650886Z",
     "start_time": "2020-05-03T11:41:34.605224Z"
    }
   },
   "source": [
    "## Definition of a forward rate agreement (FRA)\n",
    "\n",
    "A forward rate agreement is in principle a forward-starting deposit for a time period $[T_1, T_2]$ in the future (which is concluded at a start date $T_0$). However, rather than actually entering into a deposit at time $T_1$, an FRA is \"cash-settled\" at $T_1$ by exchanging the present value of the agreement (using the fixing of the underlying index to discount the cash flows from $T_2$ to $T_1$):\n",
    "$$PV(T_1) = N \\tau \\frac {r - K} {1 + r\\cdot \\tau}$$\n",
    "where\n",
    "- $N$ is the nominal amount\n",
    "- $\\tau$ is the year fraction between $T_1$ and $T_2$\n",
    "- $r$ is the index fixing at $T_1$ for the period $[T_1, T_2]$\n",
    "- $K$ is the forward rate agreed upon at $T_0$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up FRA\n",
    "ccy = 'EUR'\n",
    "fra_rate = .04\n",
    "ref_date = dt.datetime(2023, 1,28)\n",
    "start_date = dt.datetime(2023, 7, 28)\n",
    "end_date = dt.datetime(2023, 10, 28)\n",
    "\n",
    "mat_date = ref_date + dt.timedelta(days=365)\n",
    "\n",
    "fra = ForwardRateAgreementSpecification( \n",
    "        obj_id= 'dummy_id',\n",
    "        trade_date=ref_date,\n",
    "        #maturity_date=mat_date,\n",
    "        notional= 1000.0,\n",
    "        rate= fra_rate,\n",
    "        start_date=start_date,\n",
    "        end_date=end_date,\n",
    "        udlID= \"dummy_underlying_index\",\n",
    "        rate_start_date=start_date,\n",
    "        rate_end_date=end_date,\n",
    "        day_count_convention= 'Act360',\n",
    "        #business_day_convention: _Union[RollConvention, str] = RollConvention.FOLLOWING,\n",
    "        rate_day_count_convention= 'Act360',\n",
    "        #rate_business_day_convention: _Union[RollConvention, str] = RollConvention.FOLLOWING,\n",
    "        #calendar: _Union[_HolidayBase, str] = None,\n",
    "        currency=ccy,\n",
    "        # ex_settle: int =0,\n",
    "        # trade_settle: int= 0,\n",
    "        spot_days = 1,\n",
    "        payment_days = 1,\n",
    "        #start_period: int = None,\n",
    "        #end_period: int = None,\n",
    "        issuer= \"dummy_issuer\",\n",
    "        securitization_level= \"NONE\",\n",
    "        #rating: _Union[Rating, str] = Rating.NONE, ''\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up curves for pricing\n",
    "# Discount curve\n",
    "object_id = \"TEST_DC\"\n",
    "dsc_rate = 0.01\n",
    "days_to_maturity = [1, 180, 365, 720, 3 * 365, 4 * 365, 10 * 365]\n",
    "dates = [ref_date + dt.timedelta(days=d) for d in days_to_maturity]\n",
    "df = [math.exp(-d / 365.0 * dsc_rate) for d in days_to_maturity]\n",
    "dc = DiscountCurve(id=object_id, refdate=ref_date, dates=dates, df=df, interpolation= InterpolationType.LINEAR)\n",
    "\n",
    "# Fixing curve\n",
    "object_id = \"TEST_fwd\"\n",
    "fwd_rate = 0.05\n",
    "fwd_df = [math.exp(-d / 365.0 * fwd_rate) for d in days_to_maturity]\n",
    "fwd_dc = DiscountCurve(id=object_id, refdate=ref_date, dates=dates, df=fwd_df,interpolation= InterpolationType.LINEAR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Day count fraction (yf): 0.25205479452054796, Forward rate: 0.05000074869501186\n",
      "dt: 0.25555555555555554, Specification_Rate: 0.04, Amount: 2.555746888725252\n",
      "Cashflow: 2.5235016624312805\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-10-28 00:00:00\n"
     ]
    }
   ],
   "source": [
    "fig = plot_fra(fra, ref_date, fwd_dc)\n",
    "plt.show()\n",
    "print(fra._maturity_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Day count fraction (yf): 0.25205479452054796, Forward rate: 0.05000074869501186\n",
      "dt: 0.25555555555555554, Specification_Rate: 0.04, Amount: 2.555746888725252\n",
      "Cashflow: 2.5235016624312805\n"
     ]
    }
   ],
   "source": [
    "# Price FRA \n",
    "fra_pricing_data = ForwardRateAgreementPricingData(fra= fra, val_date= ref_date, pricing_request = ForwardRateAgreementPricingRequest(), \n",
    "                                                   pricer = \"ForwardRateAgreementPricer\", discount_curve = dc, forward_curve = fwd_dc,\n",
    "                                                   parameters = {})\n",
    "fra_pricer = ForwardRateAgreementPricer(ref_date, fra, dc, fwd_dc)\n",
    "fra_price =  fra_pricing_data.price()\n",
    "# print(f'Price: {fra_price}')\n",
    "# expCF = fra_pricer.expected_cashflows()\n",
    "# print(f'Expected Cashflows: {expCF}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.05000074869501186\n"
     ]
    }
   ],
   "source": [
    "# Calculate fair FRA rate (from froward curve)\n",
    "\n",
    "pricer =  ForwardRateAgreementPricer(val_date= ref_date, fra_spec = fra, discount_curve=dc, forward_curve=fwd_dc )\n",
    "fair_rate = ForwardRateAgreementPricer.compute_fair_rate(ref_date, fra, fwd_dc)\n",
    "print(fair_rate)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Day count fraction (yf): 0.25205479452054796, Forward rate: 0.05000074869501186\n",
      "dt: 0.25555555555555554, Specification_Rate: 0.05000074869501186, Amount: 0.0\n",
      "Cashflow: 0.0\n",
      "Price: 0.0\n"
     ]
    }
   ],
   "source": [
    "# Check that \"fair\" FRA has indeed price 0, use same instrument as before but apply the fair rate from the previous step\n",
    "fair_fra = ForwardRateAgreementSpecification( \n",
    "        obj_id= 'fair_dummy_id',\n",
    "        trade_date=ref_date,\n",
    "        maturity_date=mat_date,\n",
    "        notional= 1000.0,\n",
    "        rate= fair_rate,\n",
    "        start_date=start_date,\n",
    "        end_date=end_date,\n",
    "        udlID= \"dummy_underlying_index\",\n",
    "        rate_start_date=start_date,\n",
    "        rate_end_date=end_date,\n",
    "        day_count_convention= 'Act360',\n",
    "        #business_day_convention: _Union[RollConvention, str] = RollConvention.FOLLOWING,\n",
    "        rate_day_count_convention= 'Act360',\n",
    "        #rate_business_day_convention: _Union[RollConvention, str] = RollConvention.FOLLOWING,\n",
    "        #calendar: _Union[_HolidayBase, str] = None,\n",
    "        currency=ccy,\n",
    "        # ex_settle: int =0,\n",
    "        # trade_settle: int= 0,\n",
    "        #spot_days: int = None,\n",
    "        #start_period: int = None,\n",
    "        #end_period: int = None,\n",
    "        issuer= \"dummy_issuer\",\n",
    "        securitization_level= \"NONE\",\n",
    "        #rating: _Union[Rating, str] = Rating.NONE, ''\n",
    ")\n",
    "\n",
    "\n",
    "fair_fra_pricing_data = ForwardRateAgreementPricingData(fra= fair_fra, val_date= ref_date, pricing_request = ForwardRateAgreementPricingRequest(), \n",
    "                                                   pricer = \"ForwardRateAgreementPricer\", discount_curve = dc, forward_curve = fwd_dc,\n",
    "                                                   parameters = {})\n",
    "\n",
    "fair_fra_price =  fair_fra_pricing_data.price()\n",
    "print(f'Price: {fair_fra_price}')"
   ]
  }
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