我有包含债券信息的数据，我设法使用这些信息来引导零曲线。为了检查我的零曲线是否正确，我想使用引导曲线（使用零曲线）对债券重新定价，以返回债券的报价。我在重新定价部分遇到以下错误，如果有人可以提供帮助，我将不胜感激；
Traceback (most recent call last):
File "/Users/Library/CloudStorage/OneDrive-Personal/QuantLib Software/Valuations/IRS using Bond Bootstrapping/IRS using Bond Bootstrapping 2.py", line 369, in <module>
bondEngine = ql.DiscountingBondEngine(curve)
File "/usr/local/lib/python3.9/site-packages/QuantLib/QuantLib.py", line 25290, in __init__
_QuantLib.DiscountingBondEngine_swiginit(self, _QuantLib.new_DiscountingBondEngine(discountCurve))
TypeError: in method 'new_DiscountingBondEngine', argument 1 of type 'Handle< YieldTermStructure > const &'
在下面找到我正在运行的代码；
# Importing Libraries:
# The code imports necessary libraries:
# pandas for data manipulation, matplotlib.pyplot for plotting, and QuantLib (ql) for quantitative finance calculations.
import pandas as pd
import matplotlib.pyplot as plt
# Use the QuantLib or ORE Libraries
import QuantLib as ql
# Setting Evaluation Date:
# Sets the evaluation date
today = ql.Date(21, ql.November, 2023)
ql.Settings.instance().evaluationDate = today
# Calendar and Day Count:
# Creates a calendar object and specifies the day-count convention (Actual/365 Fixed)
calendar = ql.NullCalendar()
day_count = ql.Actual365Fixed()
# Settlement Days:
zero_coupon_settlement_days = 4
coupon_bond_settlement_days = 3
# Face Value
faceAmount = 100
data = [
('11-09-2023', '11-12-2023', 0, 99.524, zero_coupon_settlement_days),
('11-09-2023', '11-03-2024', 0, 96.539, zero_coupon_settlement_days),
('11-09-2023', '10-06-2024', 0, 93.552, zero_coupon_settlement_days),
('11-09-2023', '09-09-2024', 0, 89.510, zero_coupon_settlement_days),
('22-08-2022', '22-08-2024', 9.0, 96.406933, coupon_bond_settlement_days),
('27-06-2022', '27-06-2025', 10.0, 88.567570, coupon_bond_settlement_days),
('27-06-2022', '27-06-2027', 11.0, 71.363073, coupon_bond_settlement_days),
('22-08-2022', '22-08-2029', 12.0, 62.911623, coupon_bond_settlement_days),
('27-06-2022', '27-06-2032', 13.0, 55.976845, coupon_bond_settlement_days),
('22-08-2022', '22-08-2037', 14.0, 52.656596, coupon_bond_settlement_days)]
helpers = []
for issue_date, maturity, coupon, price, settlement_days in data:
price = ql.QuoteHandle(ql.SimpleQuote(price))
issue_date = ql.Date(issue_date, '%d-%m-%Y')
maturity = ql.Date(maturity, '%d-%m-%Y')
schedule = ql.MakeSchedule(issue_date, maturity, ql.Period(ql.Semiannual))
helper = ql.FixedRateBondHelper(price, settlement_days, faceAmount, schedule, [coupon / 100], day_count,
False)
helpers.append(helper)
curve = ql.PiecewiseCubicZero(today, helpers, day_count)
# Enable Extrapolation:
# This line enables extrapolation for the yield curve.
# Extrapolation allows the curve to provide interest rates or rates beyond the observed data points,
# which can be useful for pricing or risk management purposes.
curve.enableExtrapolation()
# Zero Rate and Discount Rate Calculation:
# Calculates and prints the zero rate and discount rate at a specific
# future date (May 28, 2048) using the constructed yield curve.
date = ql.Date(28, ql.May, 2024)
zero_rate = curve.zeroRate(date, day_count, ql.Annual).rate()
forward_rate = curve.forwardRate(date, date + ql.Period(1, ql.Years), day_count, ql.Annual).rate()
discount_rate = curve.discount(date)
print("Zero rate as at 28.05.2048: " + str(round(zero_rate*100, 4)) + str("%"))
print("Forward rate as at 28.05.2048: " + str(round(forward_rate*100, 4)) + str("%"))
print("Discount factor as at 28.05.2048: " + str(round(discount_rate, 4)))
# Print the Zero Rates, Forward Rates and Discount Factors at node dates
# print(pd.DataFrame(curve.nodes()))
node_data = {'Date': [],
'Zero Rates': [],
'Forward Rates': [],
'Discount Factors': []}
for dt in curve.dates():
node_data['Date'].append(dt)
node_data['Zero Rates'].append(curve.zeroRate(dt, day_count, ql.Annual).rate())
node_data['Forward Rates'].append(curve.forwardRate(dt, dt + ql.Period(1, ql.Years), day_count, ql.Annual).rate())
node_data['Discount Factors'].append(curve.discount(dt))
node_dataframe = pd.DataFrame(node_data)
print(node_dataframe)
node_dataframe.to_excel('NodeRates.xlsx')
# Printing Daily Zero Rates:
# Prints the daily zero rates
# It calculates and prints the zero rates for each year using the constructed yield curve.
maturity_date = calendar.advance(today, ql.Period(1, ql.Years))
current_date = today
while current_date <= maturity_date:
zero_rate = curve.zeroRate(current_date, day_count, ql.Annual).rate()
print(f"Date: {current_date}, Zero Rate: {zero_rate}")
current_date = calendar.advance(current_date, ql.Period(1, ql.Years))
# Creating Curve Data for Plotting:
# Creates lists of curve dates, zero rates, and forward rates for plotting.
# It calculates both zero rates and forward rates for each year up to 15 years from the current date.
curve_dates = [today + ql.Period(i, ql.Years)
for i in range(15)]
curve_zero_rates = [curve.zeroRate(date, day_count, ql.Annual).rate()
for date in curve_dates]
# Converting ql.Date to Numerical Values: (years from today)
# Converts the curve dates (ql.Date objects) to numerical values representing years from the current
# date. This is done to prepare the data for plotting on the x-axis.
numeric_dates = [(date - today) / 365 for date in curve_dates]
# Plotting:
# Creates a plot showing the zero rates and forward rates over time.
# The x-axis represents the years from the current date, and the y-axis represents the interest rates.
# The plot displays two lines: one for zero rates (blue) and another for forward rates (red).
# The plot is labeled, grid lines are added, and the visualization is displayed using
plt.figure(figsize=(10, 6))
plt.plot(numeric_dates, curve_zero_rates, marker='', linestyle='-', color='b', label='Zero Rates')
plt.title('Zero Rates')
plt.xlabel('Years from Today')
plt.ylabel('Rate')
plt.legend()
plt.grid(True)
plt.xticks(rotation=0)
plt.tight_layout()
plt.show()
tenors = ['3M', '6M', '9M', '1Y', '2Y', '3Y', '5Y', '7Y', '10Y', '15Y']
# Print the Zero Rates, Forward Rates, and Discount Factors at Instrument maturity dates
node_data = {'Maturity Date': [],
'Tenors': [],
'Zero Rates': [],
'Forward Rates': [],
'Discount Factors': []}
for tenor in tenors:
maturity_date = calendar.advance(today, ql.Period(tenor), ql.ModifiedFollowing) # Calculate the maturity date
node_data['Maturity Date'].append(maturity_date)
node_data['Tenors'].append(tenor)
node_data['Zero Rates'].append(curve.zeroRate(maturity_date, day_count, ql.Annual).rate())
node_data['Forward Rates'].append(curve.forwardRate(maturity_date, maturity_date + ql.Period(0, ql.Years), day_count, ql.Annual).rate())
node_data['Discount Factors'].append(curve.discount(maturity_date))
node_dataframe = pd.DataFrame(node_data)
print(node_dataframe)
node_dataframe.to_excel('NodeRates.xlsx')
# Create a DataFrame to store bond results
bond_results = {'Issue Date': [],
'Maturity Date': [],
'Coupon Rate': [],
'Price': [],
'Settlement Days': [],
'Yield': [],
'Clean Price': [],
'Dirty Price': []}
# Calculate bond prices and yields
for issue_date, maturity, coupon, price, settlement_days in data:
price = ql.QuoteHandle(ql.SimpleQuote(price))
issue_date = ql.Date(issue_date, '%d-%m-%Y')
maturity = ql.Date(maturity, '%d-%m-%Y')
schedule = ql.MakeSchedule(issue_date, maturity, ql.Period(ql.Semiannual))
bondEngine = ql.DiscountingBondEngine(curve)
bond = ql.FixedRateBond(settlement_days, faceAmount, schedule, [coupon / 100], day_count)
bond.setPricingEngine(bondEngine)
# Calculate bond yield, clean price, and dirty price
bondYield = bond.bondYield()
bondCleanPrice = bond.cleanPrice()
bondDirtyPrice = bond.dirtyPrice()
# Append the results to the DataFrame
bond_results['Issue Date'].append(issue_date)
bond_results['Maturity Date'].append(maturity)
bond_results['Coupon Rate'].append(coupon)
bond_results['Price'].append(price.value())
bond_results['Settlement Days'].append(settlement_days)
bond_results['Yield'].append(bondYield)
bond_results['Clean Price'].append(bondCleanPrice)
bond_results['Dirty Price'].append(bondDirtyPrice)
# Create a DataFrame from the bond results
bond_results_df = pd.DataFrame(bond_results)
# Print the results
print(bond_results_df)
您忘记为要传递的曲线创建一个 YieldTermStructureHandle DisoutningBondEngine。就像在某处添加以下行一样简单 在 for 循环之前
curveHandle = ql.YieldTermStructureHandle(curve)然后像这样调用DiscountingEngine：
bondEngine = ql.DiscountingBondEngine(curveHandle)你还缺少bondYield的相关参数，你 可能想要
bondYield = bond.bondYield(day_count, ql.Compounded, ql.Annual)