def my_portfolio_generator(N, max_months):
possible_duration = np.array([1, 3, 6, 12, 24, 36, 60, 84])
coupon_rate = np.array([1, 3, 4, 6, 12])
Coupons_per_year = np.zeros(N)
Interest = np.zeros(N)
P = np.zeros((N, max_months))
Type = np.zeros(N)
# loop to guarantee one of each bond type in order
for x in np.arange(0, 8):
i = np.random.uniform(0.01, 0.1)
Interest[x] = i
tipe = possible_duration[x]
Type[x] = tipe
cr = coupon_rate[coupon_rate <= tipe]
ncp = cr[np.random.randint(np.size(cr))]
Coupons_per_year[x] = ncp
P[x] = im.my_bond_generator(max_months, tipe, 1, i, ncp)
# loop to randomize the rest of the portfolio
for x in np.arange(8, N):
i = np.random.uniform(0.01, 0.1)
Interest[x] = i
possible_duration = possible_duration[possible_duration <= max_months]
tipe = possible_duration[np.random.randint(np.size(possible_duration))]
Type[x] = tipe
cr = coupon_rate[coupon_rate <= tipe]
ncp = cr[np.random.randint(np.size(cr))] # calculate the number of
# coupon payments in a year
Coupons_per_year[x] = ncp
P[x] = im.my_bond_generator(max_months, tipe, 1, i, ncp)
return P, Type, Coupons_per_year
def Lgen(N, max_months, possible_duration, coupon_rate):
Coupons_per_year = np.zeros(N)
Interest = np.zeros(N)
Pl = np.zeros((N, max_months))
r = np.arange(N)
Typel = np.zeros(N)
for x in r:
i = np.random.uniform(0.01, 0.1)
Interest[x] = i
possible_duration = possible_duration[possible_duration <= max_months]
tipe = possible_duration[x]
Typel[x] = tipe
cr = coupon_rate[coupon_rate <= tipe]
ncp = cr[np.random.randint(np.size(cr))] # calculate the number of
# coupon payments in a year
Coupons_per_year[x] = ncp
Pl[x] = im.my_bond_generator(max_months, tipe, 1, i, ncp)
L_portfolio = Pl
L_Type = Typel
L_CPY = Coupons_per_year
return L_portfolio, L_Type, L_CPY
def firstMonth(N, Type, possible_types, considered, coupon_rate, max_months,
monthly_rates, Portfolio_A, Portfolio_L, transaction_cost, I,
LType, Liability_number, transaction, K):
# Inputs: N, possible_types, Type, I, considered, coupon_rate, max_months,
# monthly_rates, Portfolio_A, Portfolio_L, Liability_number
# Standard computation
for y in np.arange(N):
if Type[y] == 1 & y != 0:
continue
pt = possible_types.copy()
choice = pt[possible_types <= Type[y]][-1]
LType[y] = choice
liability_interest = im.my_extract_rates(I, choice)
LI = liability_interest[considered - 1]
LI = im.my_monthly_effective_rate(LI)
li = np.random.uniform(0.01, 0.1)
cr = coupon_rate[coupon_rate <= choice]
ncp = cr[np.random.randint(np.size(cr))]
Portfolio_L[y] = im.my_bond_generator(max_months, choice, 1, li, ncp)
asset_rate = im.my_extract_rates(monthly_rates, Type[y])
asset_rate = asset_rate[considered - 1]
macD_A = im.my_macD(Portfolio_A[y], asset_rate)
macD_A = 12 * macD_A
macD_L = im.my_macD(Portfolio_L[y], LI)
macD_L = 12 * macD_L
PVA = im.my_present_value(Portfolio_A[y], asset_rate)
PVL = im.my_present_value(Portfolio_L[y], LI)
Liability_number[y] = (macD_A * PVA /
(1 + asset_rate)) / (macD_L * PVL / (1 + LI))
net = np.abs(PVA - Liability_number[y] * PVL)
acquisition = Liability_number[y] * PVL
transaction[y] = transaction_cost * (net + acquisition)
# FOR loop end
# Skip index for krd
use = np.arange(N)
index = np.ones(N)
vuse = np.arange(N)
vindex = np.ones(N)
for y in np.arange(N):
if (Type[y] == 1):
index[y] = 0
elif (Type[y] == 1):
vindex[y] = 0
use = use[index == 1]
vuse = vuse[vindex == 1]
# KRD computation
NL = K.size + 1
# one more than key rate durations
Portfolio_L_krd = Portfolio_L[0:NL]
interp_rates = krd.rateinterp(monthly_rates, considered, max_months) # krd
Qa = np.ones(krd.nbonds(Portfolio_A[use]))
N2short, err, w = krd.immunize(Portfolio_A[use],
interp_rates,
Qa,
Portfolio_L_krd,
K,
r=1)
Liability_number_krd = np.negative(N2short)
transaction_krd = np.zeros(transaction.shape)
acquisition_krd = np.zeros(transaction.shape)
Lkrd = np.zeros(transaction.shape)
#transaction_krd[NL] = krd.portfolio(Portfolio_A[NL:],interp_rates,Qa[NL:],K)[1]
for y in np.arange(NL):
acquisition_krd[y] = Liability_number_krd[y] * krd.bond(
Portfolio_L_krd[y], interp_rates, K)[1]
Lkrd[y] = Liability_number_krd[y] * krd.bond(Portfolio_L_krd[y],
interp_rates, K)[1]
net_krd = np.abs(
krd.portfolio(Portfolio_A[use], interp_rates, Qa, K)[1] - np.sum(Lkrd))
transaction_krd = transaction_cost * (net_krd + np.sum(acquisition_krd))
return transaction, Liability_number, Portfolio_L, transaction_krd, Liability_number_krd, Portfolio_L_krd
transaction = np.zeros(N)
for y in np.arange(N):
if Type[y] == 1:
continue
pt = possible_types.copy()
choice = pt[possible_types < Type[y]][-1]
# generating libaiblilty portfolio
liability_interest = im.my_extract_rates(I,choice)
LI = liability_interest[considered-1]
LI = im.my_monthly_effective_rate(LI)
li = np.random.uniform(0.01, 0.1)
cr = coupon_rate[coupon_rate <= choice]
ncp = cr[np.random.randint(np.size(cr))]
Portfolio_L[y] = im.my_bond_generator(max_months, choice, 1, li, ncp)
asset_rate = im.my_extract_rates(monthly_rates, Type[y])
asset_rate = asset_rate[considered-1]
# getting durations for each position, assests and liabilities
macD_A = im.my_macD(Portfolio_A[y],asset_rate)
macD_A = 12*macD_A
macD_L = im.my_macD(Portfolio_L[y], LI)
macD_L = 12*macD_L
# present values
PVA = im.my_present_value(Portfolio_A[y], asset_rate)
PVL = im.my_present_value(Portfolio_L[y], LI)
# computing N as a vector which will be over written