def calc_cashflow(SMM_array, r, Pool1_bal, Pool2_bal, Pool1_mwac, Pool1_age,
Pool1_term, Pool2_mwac, Pool2_age, Pool2_term, coupon_rate,
Tranche_bal_arr):
# Pool cash flows arrays
# 5 columns:
#0 PMT
#1 Interest
#2 Principal
#3 pp CF
#4 Balance
### Define Tranche CF arrays outside to pre-allocate
# define Tranche CF array, Tranche x time x (Principal, Interest, Balance)
# Tranche order: 'CG', 'VE', 'CM', 'GZ', 'TC', 'CZ', 'CA', 'CY'
# Tranche order: 0, 1, 2, 3, 4, 5, 6, 7
Tranche_CF_arr = np.zeros((8, 241, 3))
for i in range(8):
Tranche_CF_arr[i, 0, 2] = Tranche_bal_arr[i]
#a=time.time()
Pool1_data = np.zeros((241, 5))
Pool2_data = np.zeros((241, 5))
Pool1_data[0, 4] = Pool1_bal
Pool2_data[0, 4] = Pool2_bal
lib.pool_cf(Pool1_data, Pool1_mwac, Pool1_age, Pool1_term, SMM_array)
lib.pool_cf(Pool2_data, Pool2_mwac, Pool2_age, Pool2_term, SMM_array)
# Reproduce Principal CF Allocation (waterfall)
Total_principal = Pool1_data[:,
2] + Pool2_data[:,
2] + Pool1_data[:,
3] + Pool2_data[:,
3]
CA_CY_princ = 0.225181598 * Total_principal
Rest_princ = 0.7748184 * Total_principal
# Temporary arrays for calculating GZ/CZ interest accrual. The "interest" here
# is not cash flow. 2 columns:
#interest
#accrued
GZ_interest = np.zeros((241, 2))
CZ_interest = np.zeros((241, 2))
# Calculate Cash flows
# redefine giant Tranche_DF
lib.tranche_CF_calc(Tranche_CF_arr, CA_CY_princ, Rest_princ, GZ_interest,
CZ_interest, coupon_rate)
CF_arr = np.zeros((241, 8))
for i in range(8):
CF_arr[:, i] = Tranche_CF_arr[i, :, 0] + Tranche_CF_arr[i, :, 1]
#print(time.time()-a)
# Calculate Bond price
price = calc_bond_price(CF_arr[1:, :], r)
return price
'CY': 13950000
}
# small for loop, pre-allocate data for tranches
for i in Tranche_list:
Tranche_dict[i] = pd.DataFrame(np.zeros((241, 3)), columns=cols)
Tranche_dict[i].loc[0, 'Balance'] = Tranche_bal_dict[i]
# Temporary arrays for calculating GZ/CZ interest accrual. The "interest" here
# is not cash flow.
cols = ['interest', 'accrued']
GZ_interest = pd.DataFrame(np.zeros((241, 2)), columns=cols)
CZ_interest = pd.DataFrame(np.zeros((241, 2)), columns=cols)
# Calculate Cash flows
lib.tranche_CF_calc(Tranche_dict, CA_CY_princ, Rest_princ, GZ_interest,
CZ_interest, coupon_rate)
CF_df = pd.DataFrame(np.zeros((240, 8)), columns=list(Tranche_bal_dict.keys()))
for i in Tranche_bal_dict.keys():
CF_df[i] = Tranche_dict[i]['Principal'] + Tranche_dict[i]['Interest']
# %% Calculate Standard Errors, Duration, Convexity, and OAS
cf_bond = CF_df.iloc[1:, :]
m = 10000
r0 = np.log((zero_df.iloc[1, 1]/2+1)**(0.5))/0.25
price_df_MC = lib.mc_bond(m, cf_bond, theta_df, kappa, sigma, r0,
antithetic=True)
price_mean_MC = price_df_MC.mean()
price_std_MC = price_df_MC.std()/np.sqrt(len(price_df_MC))