def expected_IRR(self, df,
actual_rate=True,
rate_dict={},
actual_as_compound=True,
compound_rate=0.01):
'''
Calculates expected IRR, i.e. the cube root of the sum of all the
cashflows post-adjustment by risk and time. Expected IRR figure allows
comparisons to be made between loans of the same sub-grade.
Parameters:
df: Training data with n features. pandas dataframe.
actual_rate: Choice as to whether actual interest rate is to be used, or
a custom entry. Custom interest rates are generally chosen to allow for
comparison of loans of the same sub-grade over time. boolean
rate_dict: Custom interest rate dictionary if actual_rate was True. Key-
value pair of loan sub-grade and interest rate. dictionary.
actual_as_compound: Choice as to whether actual interest rate is to be
used for time value of money calculations. boolean.
compound_rate: Custom interest rate if actual_as_compound was true. float.
Returns:
Expected IRR of each loan. list of floats.
'''
X = df[self.features].values
date_range_length = self.term * 12
if actual_rate:
X_int_rate = df['int_rate'].values
else:
X_int_rate = df['sub_grade'].map(rate_dict).values
if actual_as_compound:
X_compound_rate = X_int_rate
else:
X_compound_rate = np.array([compound_rate] * X_int_rate.shape[0])
X_sub_grade = df['sub_grade'].values
expected_cashflows = self.get_expected_cashflows(X,
X_int_rate,
X_compound_rate,
X_sub_grade,
date_range_length)
return calc_IRR(expected_cashflows, self.term)
def expected_IRR(self,
df,
actual_rate=True,
rate_dict={},
actual_as_compound=True,
compound_rate=0.01):
'''
Calculates expected IRR, i.e. the cube root of the sum of all the
cashflows post-adjustment by risk and time. Expected IRR figure allows
comparisons to be made between loans of the same sub-grade.
Parameters:
df: Training data with n features. pandas dataframe.
actual_rate: Choice as to whether actual interest rate is to be used, or
a custom entry. Custom interest rates are generally chosen to allow for
comparison of loans of the same sub-grade over time. boolean
rate_dict: Custom interest rate dictionary if actual_rate was True. Key-
value pair of loan sub-grade and interest rate. dictionary.
actual_as_compound: Choice as to whether actual interest rate is to be
used for time value of money calculations. boolean.
compound_rate: Custom interest rate if actual_as_compound was true. float.
Returns:
Expected IRR of each loan. list of floats.
'''
X = df[self.features].values
date_range_length = self.term * 12
if actual_rate:
X_int_rate = df['int_rate'].values
else:
X_int_rate = df['sub_grade'].map(rate_dict).values
if actual_as_compound:
X_compound_rate = X_int_rate
else:
X_compound_rate = np.array([compound_rate] * X_int_rate.shape[0])
X_sub_grade = df['sub_grade'].values
expected_cashflows = self.get_expected_cashflows(
X, X_int_rate, X_compound_rate, X_sub_grade, date_range_length)
return calc_IRR(expected_cashflows, self.term)
def actual_IRR(df,
actual_rate=True,
rate_dict={},
actual_as_compound=True,
compound_rate=0.01):
'''
Calculates IRR for loans that have already matured.
Parameters:
df: Validation data with features reflecting payments made.
actual_rate: Choice as to whether actual interest rate is to be used, or
a custom entry. Custom interest rates are generally chosen to allow for
comparison of loans of the same sub-grade over time. boolean
rate_dict: Custom interest rate dictionary if actual_rate was True. Key-
value pair of loan sub-grade and interest rate. dictionary.
actual_as_compound: Choice as to whether actual interest rate is to be
used for time value of money calculations. boolean.
compound_rate: Custom interest rate if actual_as_compound was true. float.
Returns:
Actual IRR of each loan. list of floats.
'''
term = 3
date_range_length = term * 12
X = df[['default_status', 'months_paid', 'residual', 'recovery']].values
if actual_rate:
X_int_rate = df['int_rate'].values
else:
X_int_rate = df['sub_grade'].map(rate_dict).values
if actual_as_compound:
X_compound_rate = X_int_rate
else:
X_compound_rate = np.array([compound_rate] * X_int_rate.shape[0])
actual_cashflows = get_actual_cashflows(X,
X_int_rate,
X_compound_rate,
date_range_length)
return calc_IRR(actual_cashflows, term)
def actual_IRR(df,
actual_rate=True,
rate_dict={},
actual_as_compound=True,
compound_rate=0.01):
'''
Calculates IRR for loans that have already matured.
Parameters:
df: Validation data with features reflecting payments made.
actual_rate: Choice as to whether actual interest rate is to be used, or
a custom entry. Custom interest rates are generally chosen to allow for
comparison of loans of the same sub-grade over time. boolean
rate_dict: Custom interest rate dictionary if actual_rate was True. Key-
value pair of loan sub-grade and interest rate. dictionary.
actual_as_compound: Choice as to whether actual interest rate is to be
used for time value of money calculations. boolean.
compound_rate: Custom interest rate if actual_as_compound was true. float.
Returns:
Actual IRR of each loan. list of floats.
'''
term = 3
date_range_length = term * 12
X = df[['default_status', 'months_paid', 'residual', 'recovery']].values
if actual_rate:
X_int_rate = df['int_rate'].values
else:
X_int_rate = df['sub_grade'].map(rate_dict).values
if actual_as_compound:
X_compound_rate = X_int_rate
else:
X_compound_rate = np.array([compound_rate] * X_int_rate.shape[0])
actual_cashflows = get_actual_cashflows(X, X_int_rate, X_compound_rate,
date_range_length)
return calc_IRR(actual_cashflows, term)