Renamed G_DAYS_IN_YEARS TO G_DAYS_IN_YEAR

Author: domokane

financepy/market/curves/discount_curve.py

@@ -8,7 +8,7 @@
 
 from ...utils.date import Date
 from ...utils.error import FinError
-from ...utils.global_vars import G_DAYS_IN_YEARS, G_SMALL
+from ...utils.global_vars import G_DAYS_IN_YEAR, G_SMALL
 from ...utils.frequency import annual_frequency, FrequencyTypes
 from ...utils.day_count import DayCount, DayCountTypes
 from ...utils.math import test_monotonicity
@@ -64,7 +64,7 @@ def __init__(
                 start_index = 1
 
         for i in range(start_index, num_points):
-            t = (df_dates[i] - value_dt) / G_DAYS_IN_YEARS
+            t = (df_dates[i] - value_dt) / G_DAYS_IN_YEAR
             self._times.append(t)
             self._dfs.append(df_values[i])
 
@@ -395,7 +395,7 @@ def fwd(self, dts: Date):
 
         df1 = self.df(dts)
         df2 = self.df(dts_plus_one_days)
-        dt = 1.0 / G_DAYS_IN_YEARS
+        dt = 1.0 / G_DAYS_IN_YEAR
         fwd = np.log(df1 / df2) / (1.0 * dt)
 
         if isinstance(dts, Date):

financepy/market/volatility/equity_vol_surface.py

@@ -12,7 +12,7 @@
 
 from ...utils.error import FinError
 from ...utils.date import Date
-from ...utils.global_vars import G_DAYS_IN_YEARS
+from ...utils.global_vars import G_DAYS_IN_YEAR
 from ...utils.global_types import OptionTypes
 from ...models.option_implied_dbn import option_implied_dbn
 from ...utils.helpers import check_argument_types, label_to_string
@@ -152,11 +152,7 @@ def _solve_to_horizon(
     fastmath=True,
 )
 def vol_function(
-    vol_function_type_value: int,
-    params: np.ndarray,
-    f: float,
-    k: float,
-    t: float
+    vol_function_type_value: int, params: np.ndarray, f: float, k: float, t: float
 ) -> float:
     """Return the volatility for a strike using a given polynomial
     interpolation following Section 3.9 of Iain Clark book."""
@@ -327,7 +323,7 @@ def vol_from_strike_dt(self, k: float, expiry_dt: Date) -> float:
         interpolation is done in variance space and then converted back to a
         lognormal volatility."""
 
-        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEARS
+        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEAR
 
         vol_type_value = self._vol_func_type.value
 
@@ -402,7 +398,7 @@ def vol_from_strike_dt(self, k: float, expiry_dt: Date) -> float:
     #     """ Interpolates the strike at a delta and expiry date. Linear
     #     interpolation is used in strike."""
 
-    #     t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEARS
+    #     t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEAR
 
     #     vol_type_value = self._vol_func_type.value
 
@@ -497,7 +493,7 @@ def vol_from_delta_date(
         self,
         call_delta: float,
         expiry_dt: Date,
-        delta_method = None,
+        delta_method=None,
     ) -> Tuple[float, float]:
         """Interpolates the Black-Scholes volatility from the volatility
         surface given a call option delta and expiry date. Linear interpolation
@@ -509,7 +505,7 @@ def vol_from_delta_date(
         interpolation is done in variance space and then converted back to a
         lognormal volatility."""
 
-        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEARS
+        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEAR
 
         vol_type_value = self._vol_func_type.value
 
@@ -611,7 +607,9 @@ def vol_from_delta_date(
 
     ####################################################################################
 
-    def _build_vol_surface(self, fin_solver_type: Any = FinSolverTypes.NELDER_MEAD) -> None:
+    def _build_vol_surface(
+        self, fin_solver_type: Any = FinSolverTypes.NELDER_MEAD
+    ) -> None:
         """Main function to construct the vol surface."""
 
         s = self._stock_price
@@ -666,7 +664,7 @@ def _build_vol_surface(self, fin_solver_type: Any = FinSolverTypes.NELDER_MEAD)
         for i in range(0, num_expiry_dts):
 
             expiry_dt = self._expiry_dts[i]
-            t_exp = (expiry_dt - spot_dt) / G_DAYS_IN_YEARS
+            t_exp = (expiry_dt - spot_dt) / G_DAYS_IN_YEAR
 
             dis_df = self._discount_curve.df_t(t_exp)
             div_df = self._dividend_curve.df_t(t_exp)
@@ -756,10 +754,7 @@ def check_calibration(self, verbose: bool) -> None:
     ####################################################################################
 
     def implied_dbns(
-        self,
-        low_s: float,
-        high_s: float,
-        num_intervals: int
+        self, low_s: float, high_s: float, num_intervals: int
     ) -> List[FinDistribution]:
         """Calculate the pdf for each tenor horizon. Returns a list of
         FinDistribution objects, one for each tenor horizon."""

financepy/market/volatility/fx_vol_surface.py

@@ -15,7 +15,7 @@
 from ...utils.error import FinError
 from ...utils.date import Date
 from ...utils.tenor import Tenor
-from ...utils.global_vars import G_DAYS_IN_YEARS
+from ...utils.global_vars import G_DAYS_IN_YEAR
 from ...utils.global_types import OptionTypes
 from ...products.fx.fx_vanilla_option import FXVanillaOption
 from ...models.option_implied_dbn import option_implied_dbn
@@ -189,7 +189,7 @@ def solve_to_horizon_fast(
     rr_25d_vol: float,
     delta_method_value: int,
     vol_type_value: int,
-    xopt: Sequence[float]
+    xopt: Sequence[float],
 ) -> Tuple[np.ndarray, float, float, float, float]:
 
     c0 = xopt
@@ -295,11 +295,7 @@ def solve_to_horizon_fast(
     fastmath=True,
 )
 def vol_function(
-    vol_function_type_value: int,
-    params: np.ndarray,
-    f: float,
-    k: float,
-    t: float
+    vol_function_type_value: int, params: np.ndarray, f: float, k: float, t: float
 ) -> float:
     """Return the volatility for a strike using a given polynomial
     interpolation following Section 3.9 of Iain Clark book."""
@@ -386,7 +382,7 @@ def solver_for_smile_strike_fast(
     delta_target: float,
     delta_method_value: int,
     initial_guess: float,
-    parameters: np.ndarray
+    parameters: np.ndarray,
 ) -> float:
     """Solve for the strike that sets the delta of the option equal to the
     target value of delta allowing the volatility to be a function of the
@@ -426,7 +422,7 @@ def solve_for_strike(
     opt_type_value: int,
     delta_target: float,
     delta_method_value: int,
-    volatility: float
+    volatility: float,
 ) -> float:
     """This function determines the implied strike of an FX option
     given a delta and the other option details. It uses a one-dimensional
@@ -623,7 +619,7 @@ def volatility(self, k: float, expiry_dt: Date) -> float:
         index0 = 0
         index1 = 0
 
-        t = (expiry_dt - self.value_dt) / G_DAYS_IN_YEARS
+        t = (expiry_dt - self.value_dt) / G_DAYS_IN_YEAR
 
         num_curves = self.num_vol_curves
 
@@ -722,7 +718,7 @@ def build_vol_surface(self) -> None:
         for i in range(0, num_vol_curves):
 
             expiry_dt = self.expiry_dts[i]
-            t_exp = (expiry_dt - spot_dt) / G_DAYS_IN_YEARS
+            t_exp = (expiry_dt - spot_dt) / G_DAYS_IN_YEAR
 
             dom_df = self.domestic_curve.df_t(t_exp)
             for_df = self.foreign_curve.df_t(t_exp)
@@ -859,7 +855,7 @@ def solver_for_smile_strike(
         opt_type_value: int,
         delta_target: float,
         tenor_index: int,
-        initial_value: float
+        initial_value: float,
     ) -> float:
         """Solve for the strike that sets the delta of the option equal to the
         target value of delta allowing the volatility to be a function of the
@@ -1259,10 +1255,7 @@ def check_calibration(self, verbose: bool, tol: float = 1e-5) -> None:
     ###########################################################################
 
     def implied_dbns(
-        self,
-        low_fx: float,
-        high_fx: float,
-        num_intervals: int
+        self, low_fx: float, high_fx: float, num_intervals: int
     ) -> List[FinDistribution]:
         """Calculate the pdf for each tenor horizon. Returns a list of
         FinDistribution objects, one for each tenor horizon."""

financepy/market/volatility/fx_vol_surface_plus.py

@@ -15,7 +15,7 @@
 
 from ...utils.error import FinError
 from ...utils.date import Date
-from ...utils.global_vars import G_DAYS_IN_YEARS
+from ...utils.global_vars import G_DAYS_IN_YEAR
 from ...utils.global_types import OptionTypes
 from ...products.fx.fx_vanilla_option import FXVanillaOption
 from ...models.option_implied_dbn import option_implied_dbn
@@ -88,11 +88,7 @@ def _g(kk: float, *args: Any) -> float:
 
 
 @njit(float64(float64, float64[:], float64[:]), fastmath=True, cache=True)
-def _interpolate_gap(
-    k: float,
-    strikes: np.ndarray,
-    gaps: np.ndarray
-) -> float:
+def _interpolate_gap(k: float, strikes: np.ndarray, gaps: np.ndarray) -> float:
 
     if k <= strikes[0]:
         return 0.0
@@ -609,8 +605,20 @@ def _solve_to_horizon(
     x_inits: Sequence[float],
     ginits: Sequence[float],
     fin_solver_type: Any,
-    tol: float
-) -> Tuple[np.ndarray, np.ndarray, np.ndarray, float, float, float, float, float, float, float, float]:
+    tol: float,
+) -> Tuple[
+    np.ndarray,
+    np.ndarray,
+    np.ndarray,
+    float,
+    float,
+    float,
+    float,
+    float,
+    float,
+    float,
+    float,
+]:
 
     ###########################################################################
     # Determine the price of a market strangle from market strangle
@@ -951,7 +959,7 @@ def vol_function(
     gaps: np.ndarray,
     f: float,
     k: float,
-    t: float
+    t: float,
 ) -> float:
     """Return the volatility for a strike using a given polynomial
     interpolation following Section 3.9 of Iain Clark book."""
@@ -1059,7 +1067,7 @@ def _solver_for_smile_strike(
     initial_guess: float,
     parameters: np.ndarray,
     strikes: np.ndarray,
-    gaps: np.ndarray
+    gaps: np.ndarray,
 ) -> float:
     """Solve for the strike that sets the delta of the option equal to the
     target value of delta allowing the volatility to be a function of the
@@ -1103,7 +1111,7 @@ def solve_for_strike(
     opt_type_value: int,
     delta_target: float,
     delta_method_value: int,
-    volatility: float
+    volatility: float,
 ) -> float:
     """This function determines the implied strike of an FX option
     given a delta and the other option details. It uses a one-dimensional
@@ -1362,7 +1370,7 @@ def vol_from_strike_dt(self, kk: float, expiry_dt: Date) -> float:
         interpolation is done in variance space and then converted back to a
         lognormal volatility."""
 
-        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEARS
+        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEAR
 
         vol_type_value = self.vol_func_type.value
 
@@ -1450,15 +1458,12 @@ def vol_from_strike_dt(self, kk: float, expiry_dt: Date) -> float:
     ###########################################################################
 
     def delta_to_strike(
-        self,
-        call_delta: float,
-        expiry_dt: Date,
-        delta_method: Optional[Any]
+        self, call_delta: float, expiry_dt: Date, delta_method: Optional[Any]
     ) -> float:
         """Interpolates the strike at a delta and expiry date. Linear
         time to expiry interpolation is used in strike."""
 
-        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEARS
+        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEAR
 
         vol_type_value = self.vol_func_type.value
 
@@ -1562,7 +1567,7 @@ def vol_from_delta_date(
         self,
         call_delta: float,
         expiry_dt: Date,
-        delta_method: Optional[FinFXDeltaMethod] = None
+        delta_method: Optional[FinFXDeltaMethod] = None,
     ) -> Tuple[float, float]:
         """Interpolates the Black-Scholes volatility from the volatility
         surface given a call option delta and expiry date. Linear interpolation
@@ -1574,7 +1579,7 @@ def vol_from_delta_date(
         interpolation is done in variance space and then converted back to a
         lognormal volatility."""
 
-        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEARS
+        t_exp = (expiry_dt - self.value_dt) / G_DAYS_IN_YEAR
 
         vol_type_value = self.vol_func_type.value
 
@@ -1704,9 +1709,7 @@ def vol_from_delta_date(
     ###########################################################################
 
     def _build_vol_surface(
-        self,
-        fin_solver_type: Any = FinSolverTypes.NELDER_MEAD,
-        tol: float = 1e-8
+        self, fin_solver_type: Any = FinSolverTypes.NELDER_MEAD, tol: float = 1e-8
     ) -> None:
         """Main function to construct the vol surface."""
 
@@ -1764,7 +1767,7 @@ def _build_vol_surface(
         for i in range(0, num_vol_curves):
 
             expiry_dt = self.expiry_dts[i]
-            t_exp = (expiry_dt - spot_dt) / G_DAYS_IN_YEARS
+            t_exp = (expiry_dt - spot_dt) / G_DAYS_IN_YEAR
 
             dom_df = self.domestic_curve.df(expiry_dt)
             for_df = self.foreign_curve.df(expiry_dt)
@@ -2609,10 +2612,7 @@ def check_calibration(self, verbose: bool, tol: float = 1e-6) -> None:
     ###########################################################################
 
     def implied_dbns(
-        self,
-        low_fx: float,
-        high_fx: float,
-        num_intervals: int
+        self, low_fx: float, high_fx: float, num_intervals: int
     ) -> List[FinDistribution]:
         """Calculate the pdf for each tenor horizon. Returns a list of
         FinDistribution objects, one for each tenor horizon."""

financepy/market/volatility/ibor_cap_vol_curve.py

@@ -7,7 +7,7 @@
 from ...utils.error import FinError
 from ...utils.date import Date
 from ...utils.helpers import label_to_string
-from ...utils.global_vars import G_DAYS_IN_YEARS
+from ...utils.global_vars import G_DAYS_IN_YEAR
 from ...utils.day_count import DayCount, DayCountTypes
 
 # TODO: Calibration
@@ -19,6 +19,7 @@
 
 from typing import Any, Sequence, Union
 
+
 class IborCapVolCurve:
     """Class to manage a term structure of cap (flat) volatilities and to
     do the conversion to caplet (spot) volatilities. This does not manage a
@@ -98,7 +99,7 @@ def generate_caplet_vols(self) -> None:
         num_caps = len(self._cap_maturity_dts)
 
         for dt in self._cap_maturity_dts:
-            t = (dt - self._curve_dt) / G_DAYS_IN_YEARS
+            t = (dt - self._curve_dt) / G_DAYS_IN_YEAR
             self.times.append(t)
             tau = day_counter.year_frac(prev_dt, dt)[0]
             self._taus.append(tau)
@@ -133,7 +134,7 @@ def caplet_vol(self, dt: Union[Any, float]) -> float:
         The volatility interpolation is piecewise flat."""
 
         if isinstance(dt, Date):
-            t = (dt - self._curve_dt) / G_DAYS_IN_YEARS
+            t = (dt - self._curve_dt) / G_DAYS_IN_YEAR
         else:
             t = dt
 
@@ -164,7 +165,7 @@ def cap_vol(self, dt: Union[Any, float]) -> float:
         is piecewise flat."""
 
         if isinstance(dt, Date):
-            t = (dt - self._curve_dt) / G_DAYS_IN_YEARS
+            t = (dt - self._curve_dt) / G_DAYS_IN_YEAR
         else:
             t = dt