def test_FinInterpolatedForwards():
import matplotlib.pyplot as plt
tValues = np.array([0.0, 3.0, 5.0, 10.0])
rValues = np.array([0.04, 0.07, 0.08, 0.09])
df_values = np.exp(-tValues*rValues)
tInterpValues = np.linspace(0.0, 12.0, 49)
curve_date = Date(1, 1, 2019)
tDates = curve_date.add_years(tValues)
tInterpDates = curve_date.add_years(tInterpValues)
for interp_type in InterpTypes:
discount_curve = DiscountCurve(
curve_date, tDates, df_values, interp_type)
dfInterpValues = discount_curve.df(tInterpDates)
fwdInterpValues = discount_curve.fwd(tInterpDates)
zeroInterpValues = discount_curve.zero_rate(tInterpDates)
if PLOT_GRAPHS:
plt.figure(figsize=(8, 6))
plt.plot(tValues, df_values, 'o', color='g', label="DFS:")
plt.plot(tInterpValues, dfInterpValues, color='r',
label="DF:" + str(interp_type))
plt.legend()
plt.figure(figsize=(8, 6))
plt.plot(tInterpValues, fwdInterpValues, color='r',
label="FWD:" + str(interp_type))
plt.plot(tInterpValues, zeroInterpValues, color='b',
label="ZERO:" + str(interp_type))
plt.plot(tValues, rValues, 'o', color='g', label="ZERO RATES")
plt.legend()
def test_FinDiscountCurve():
# Create a curve from times and discount factors
start_date = Date(1, 1, 2018)
years = np.linspace(0, 10, 6)
rate = 0.05 + 0.005*years - 0.0003*years*years
dfs = np.exp(-rate * years)
dates = start_date.add_years(years)
curve = DiscountCurve(start_date, dates, dfs, InterpTypes.FLAT_FWD_RATES)
testCases.header("T", "DF", "ZERORATE", "CC_FWD", "MM_FWD", "SURVPROB")
plotYears = np.linspace(0, 12, 12*12+1)[1:]
plotDates = start_date.add_years(plotYears)
# Examine dependency of curve on compounding rate
zero_rates_A = curve.zero_rate(plotDates, FrequencyTypes.ANNUAL)
zero_rates_S = curve.zero_rate(plotDates, FrequencyTypes.SEMI_ANNUAL)
zero_rates_Q = curve.zero_rate(plotDates, FrequencyTypes.QUARTERLY)
zero_rates_M = curve.zero_rate(plotDates, FrequencyTypes.MONTHLY)
zero_rates_C = curve.zero_rate(plotDates, FrequencyTypes.CONTINUOUS)
if PLOT_GRAPHS:
plt.figure(figsize=(6, 4))
plt.plot(plotYears, scale(zero_rates_A, 100), label='A')
plt.plot(plotYears, scale(zero_rates_S, 100), label='S')
plt.plot(plotYears, scale(zero_rates_Q, 100), label='Q')
plt.plot(plotYears, scale(zero_rates_M, 100), label='M')
plt.plot(plotYears, scale(zero_rates_C, 100), label='C')
plt.ylim((5, 8))
plt.title('Discount Curves')
plt.xlabel('Time (years)')
plt.ylabel('Zero Rate (%)')
plt.legend(loc='lower right', frameon=False)
# Examine dependency of fwd curve on the interpolation scheme
for interp in InterpTypes:
curve = DiscountCurve(start_date, dates, dfs, interp)
fwd_rates = curve.fwd(plotDates)
zero_rates = curve.zero_rate(plotDates, FrequencyTypes.ANNUAL)
parRates = curve.swap_rate(
start_date, plotDates, FrequencyTypes.ANNUAL)
if PLOT_GRAPHS:
plt.figure(figsize=(6, 4))
plt.plot(plotYears, scale(fwd_rates, 100), label='FWD RATES')
plt.plot(plotYears, scale(zero_rates, 100), label='ZERO RATES')
plt.plot(plotYears, scale(parRates, 100), label='PAR RATES')
plt.ylim((3.0, 8.5))
plt.title('Forward Curves using ' + str(interp))
plt.xlabel('Time (years)')
plt.ylabel('Fwd Rate (%)')
plt.legend(loc='lower right', frameon=False)