def test_mirr(self):
v1 = [-4500,-800,800,800,600,600,800,800,700,3000]
assert_almost_equal(np.mirr(v1,0.08,0.055),
0.0665, 4)
v2 = [-120000,39000,30000,21000,37000,46000]
assert_almost_equal(np.mirr(v2,0.10,0.12),
0.1344, 4)
def test_mirr(self):
val = [-4500, -800, 800, 800, 600, 600, 800, 800, 700, 3000]
assert_almost_equal(np.mirr(val, 0.08, 0.055), 0.0666, 4)
val = [-120000, 39000, 30000, 21000, 37000, 46000]
assert_almost_equal(np.mirr(val, 0.10, 0.12), 0.126094, 6)
val = [100, 200, -50, 300, -200]
assert_almost_equal(np.mirr(val, 0.05, 0.06), 0.3428, 4)
val = [39000, 30000, 21000, 37000, 46000]
assert_(np.isnan(np.mirr(val, 0.10, 0.12)))
def test_mirr(self):
val = [-4500,-800,800,800,600,600,800,800,700,3000]
assert_almost_equal(np.mirr(val, 0.08, 0.055), 0.0666, 4)
val = [-120000,39000,30000,21000,37000,46000]
assert_almost_equal(np.mirr(val, 0.10, 0.12), 0.126094, 6)
val = [100,200,-50,300,-200]
assert_almost_equal(np.mirr(val, 0.05, 0.06), 0.3428, 4)
val = [39000,30000,21000,37000,46000]
assert_(np.isnan(np.mirr(val, 0.10, 0.12)))
def test_mirr_decimal(self):
val = [
Decimal("-4500"),
Decimal("-800"),
Decimal("800"),
Decimal("800"),
Decimal("600"),
Decimal("600"),
Decimal("800"),
Decimal("800"),
Decimal("700"),
Decimal("3000"),
]
assert_equal(
np.mirr(val, Decimal("0.08"), Decimal("0.055")),
Decimal("0.066597175031553548874239618"),
)
val = [
Decimal("-120000"),
Decimal("39000"),
Decimal("30000"),
Decimal("21000"),
Decimal("37000"),
Decimal("46000"),
]
assert_equal(
np.mirr(val, Decimal("0.10"), Decimal("0.12")),
Decimal("0.126094130365905145828421880"),
)
val = [
Decimal("100"),
Decimal("200"),
Decimal("-50"),
Decimal("300"),
Decimal("-200"),
]
assert_equal(
np.mirr(val, Decimal("0.05"), Decimal("0.06")),
Decimal("0.342823387842176663647819868"),
)
val = [
Decimal("39000"),
Decimal("30000"),
Decimal("21000"),
Decimal("37000"),
Decimal("46000"),
]
assert_(np.isnan(np.mirr(val, Decimal("0.10"), Decimal("0.12"))))
def compute_mirr(cash_flows=list(), rate=0):
"""
:param cash_flows: cash flows data list
:param rate: discount rate value
:return: mirr value of cash_flows data list
"""
return np.mirr(cash_flows, rate, rate)
def test_mirr_decimal(self):
val = [Decimal('-4500'), Decimal('-800'), Decimal('800'), Decimal('800'),
Decimal('600'), Decimal('600'), Decimal('800'), Decimal('800'),
Decimal('700'), Decimal('3000')]
assert_equal(np.mirr(val, Decimal('0.08'), Decimal('0.055')),
Decimal('0.066597175031553548874239618'))
val = [Decimal('-120000'), Decimal('39000'), Decimal('30000'),
Decimal('21000'), Decimal('37000'), Decimal('46000')]
assert_equal(np.mirr(val, Decimal('0.10'), Decimal('0.12')), Decimal('0.126094130365905145828421880'))
val = [Decimal('100'), Decimal('200'), Decimal('-50'),
Decimal('300'), Decimal('-200')]
assert_equal(np.mirr(val, Decimal('0.05'), Decimal('0.06')), Decimal('0.342823387842176663647819868'))
val = [Decimal('39000'), Decimal('30000'), Decimal('21000'), Decimal('37000'), Decimal('46000')]
assert_(np.isnan(np.mirr(val, Decimal('0.10'), Decimal('0.12'))))
def test_mirr_decimal(self):
val = [Decimal('-4500'), Decimal('-800'), Decimal('800'), Decimal('800'),
Decimal('600'), Decimal('600'), Decimal('800'), Decimal('800'),
Decimal('700'), Decimal('3000')]
assert_equal(np.mirr(val, Decimal('0.08'), Decimal('0.055')),
Decimal('0.066597175031553548874239618'))
val = [Decimal('-120000'), Decimal('39000'), Decimal('30000'),
Decimal('21000'), Decimal('37000'), Decimal('46000')]
assert_equal(np.mirr(val, Decimal('0.10'), Decimal('0.12')), Decimal('0.126094130365905145828421880'))
val = [Decimal('100'), Decimal('200'), Decimal('-50'),
Decimal('300'), Decimal('-200')]
assert_equal(np.mirr(val, Decimal('0.05'), Decimal('0.06')), Decimal('0.342823387842176663647819868'))
val = [Decimal('39000'), Decimal('30000'), Decimal('21000'), Decimal('37000'), Decimal('46000')]
assert_(np.isnan(np.mirr(val, Decimal('0.10'), Decimal('0.12'))))
def mirr(values, finance_rate, reinvest_rate, *args, **kwargs):
""" MIRR is calculated by assuming NPV as zero
:param values: Positive or negative cash flows
:param finance_rate: Interest rate paid for the money used in cash flows
:param reinvest_rate: Interest rate paid for reinvestment of cash flows
:return:
"""
return np.mirr(values=values,
finance_rate=float(finance_rate),
reinvest_rate=float(reinvest_rate))
def npfin_practice():
# pv：年利率3%，按季度付息，每月付10，5年后获取1376.09633204，求现值
val_pv = np.pv(rate=0.03 / 4, nper=4 * 5, pmt=-10, fv=1376.09633204)
print('年利率3%，按季度付息，每月付10，5年后获取1376.09633204，现值:\t{:.2f}'.format(-val_pv))
# fv：年利率3%，按季度付息，本金1000，每月付10，求5年后的终值
val_fv = np.fv(rate=0.03 / 4, nper=4 * 5, pmt=-10, pv=-1000)
print('年利率3%，按季度付息，本金1000，每月付10，终值:\t{:.2f}'.format(val_fv))
# fvals = []
# for i in range(1, 11):
# fvals.append(np.fv(rate=0.03/4, nper=4*i, pmt=-10, pv=-1000))
# plt.plot(fvals, 'bo')
# plt.title('年利率3%，按季度付息，本金1000，每月付10，1-10年后的终值')
# plt.show()
# pmt：年利率1%，贷款1000万，求每月的分期付款
val_pmt = np.pmt(rate=0.01 / 12, nper=12 * 30, pv=10000000)
print('年利率1%，贷款1000万，每月的分期付款：\t{:.2f}'.format(-val_pmt))
# nper：年利率10%，贷款9000，每月付款100，求付款期数
val_nper = np.nper(rate=0.10 / 12, pmt=-100, pv=9000)
print('年利率10%，贷款9000，每月付款100，付款期数：\t{:.2f}'.format(val_nper))
# irr：现金流[-100, 38, 48, 90, 17, 36]，求内部收益率
val_irr = np.irr(values=[-100, 38, 48, 90, 17, 36])
print('现金流[-100, 38, 48, 90, 17, 36]，内部收益率：\t{:.0f}%'.format(100 *
val_irr))
# mirr：现金流[-100, 38, 48, 90, 17, 36]，投资成本3%，现金再投资收益率3%，求修正内部收益率
val_mirr = np.mirr(values=[-100, 38, 48, 90, 17, 36],
finance_rate=0.03,
reinvest_rate=0.03)
print('现金流[-100, 38, 48, 90, 17, 36]，投资成本3%，现金再投资收益率3%，求修正内部收益率：\t{:.0f}%'\
.format(100 * val_mirr))
# rate：贷款9000，每月付100，贷款167个月，求利率
val_rate = 12 * np.rate(nper=167, pmt=-100, pv=9000, fv=0)
print('贷款9000，每月付100，贷款167个月，利率：\t{:.0f}%'.format(100 * val_rate))
# npv：随机在0-100之间取5个数作为现金流，利率3%，求净现值
cashflows = np.random.randint(100, size=5)
cashflows = np.insert(cashflows, 0, -100)
print('Cashflows: {}'.format(cashflows))
val_npv = np.npv(rate=0.03, values=cashflows)
print('利率3%，上述现金流下，净现值：\t{:.2f}'.format(val_npv))
def mirr(cflo, finance_rate=0, reinvest_rate=0):
"""Computes the modified internal rate of return of a generic cashflow
as a periodic interest rate.
Args:
cflo (pandas.Series): Generic cashflow.
finance_rate (float): Periodic interest rate applied to negative values of the cashflow.
reinvest_rate (float): Periodic interest rate applied to positive values of the cashflow.
Returns:
Float or list of floats.
**Examples.**
>>> cflo = cashflow([-200] + [100]*4, start='2000Q1', freq='Q')
>>> mirr(cflo) # doctest: +ELLIPSIS
18.92...
>>> mirr([cflo, cflo]) # doctest: +ELLIPSIS
0 18.920712
1 18.920712
dtype: float64
"""
# negativos: finance_rate
# positivos: reinvest_rate
if isinstance(cflo, pd.Series):
cflo = [cflo]
retval = pd.Series([0] * len(cflo), dtype=np.float64)
for index, xcflo in enumerate(cflo):
retval[index] = (100 * np.mirr(xcflo,
finance_rate,
reinvest_rate))
if len(retval) == 1:
return retval[0]
return retval
def mirr(cflo, finance_rate=0, reinvest_rate=0):
"""Computes the modified internal rate of return.
Args:
cashflow (list, cashflow): cashflow.
finance_rate (float): rate applied to negative values of the cashflow
reinvest_rate (float): rate applied to positive values of the cashflow
Returns:
(float) modified internal rate of return.
"""
# negativos: finance_rate
# positivos: reinvest_rate
if isinstance(cflo, TimeSeries):
cflo = [cflo]
retval = []
for xcflo in cflo:
retval.append(100 * xcflo.pyr *
np.mirr(xcflo.tolist(), finance_rate, reinvest_rate))
if len(retval) == 1:
return retval[0]
return retval
cashflow = pd.concat(
[dfcash_A['Cash_Flows'], dfcash_B['Cash_Flows']], axis=1
) #found through trail and error best way to join the dataframes in one df through their indexes
cashflow.columns = ['Cash Flows A', 'Cash Flows B']
print(
"\nQuestion 11:\n{}\na)The payback period for Project A is {}yrs.\nb)The payback period for Project B is {}yrs.\n\n{}\n{}\nc) The \
discounted payback period for Project A is {}yrs.\nd) The discounted payback period for Project B is {}yrs.\ne) The NPV for project A is ${:,.2f}.\nf) The NPV for project B is ${:,.2f}.\ng) The IRR for project A is {}%.\nh) The IRR for project B is {}%.\
\ni) The PI for project A is {}.\nj) The PI for project B is {}.".format(
cashflow, period_A, period_B, npv_data_A, npv_data_B, period_Ad,
period_Bd, npv_A, npv_B, irr_A, irr_B, PI_A, PI_B))
# Question 12
npv, npv_data, irr_Discount, dfcash_A, period_A, PI = calc_npv(
4, -36429.3, [12000, 14700, 16600, 13700], 9 / 100, 3
) #discounting appraoch: returned last year cash outflow to PV and added it to intial cost to derrive MIRR (Discount)
irr_reinvest = round(
np.mirr([-29800, 12000, 14700, 16600, 13700, -10200], 9 / 100, 9 / 100) *
100, 4)
irr_combination = round(
np.mirr([-36429.3, 12000, 14700, 16600, 13700], 9 / 100, 9 / 100) * 100, 4)
print(
"\nQuestion 12:\n{}\na) The MIRR using discounting approach is {}%.\nb) The MIRR using reinvestment approach is {}%.\nc) The MIRR using combination approach is {}%."
.format(dfcash_A, irr_Discount, irr_reinvest, irr_combination))
# Question 13
npv, npv_data, irr_Discount, dfcash_B, period_A, PI = calc_npv(
4, -15870.531, [6100, 6700, 6200, 5100], 9 / 100, 3
) #discounting appraoch: returned last year cash outflow to PV and added it to intial cost to derrive MIRR (Discount)
irr_reinvest = round(
(np.mirr([-13200, 6100, 6700, 6200, 5100, -4500], 11 / 100, 9 / 100)) *
100, 4)
irr_combination = round(
(np.mirr([-15870.531, 6100, 6700, 6200, 5100], 11 / 100, 9 / 100)) * 100,
def test_mirr(self):
v1 = [-4500, -800, 800, 800, 600, 600, 800, 800, 700, 3000]
assert_almost_equal(np.mirr(v1, 0.08, 0.055), 0.0665, 4)
v2 = [-120000, 39000, 30000, 21000, 37000, 46000]
assert_almost_equal(np.mirr(v2, 0.10, 0.12), 0.1344, 4)
import numpy as np print(np.fv(0.02, 20 * 12, -100, -100)) print(np.pv(0.02, 20 * 12, -100, 586032.549)) print(np.npv(0.281, [-100, 823, 59, 55, 20])) print(np.pmt(0.02 / 12, 20 * 12, 1000000)) print(np.ppmt(0.02 / 12, -100, 20 * 12, 1000000)) print(np.ipmt(0.02 / 12, 0.001, 20 * 12, 200000)) print(round(np.irr([-5, 10.5, 1, -8, 1]), 5)) print(np.mirr([-100, 823, 59, 55, 20], -100, -150)) print(np.nper(0.02, -1e7, 1e8)) print(np.rate(0.7, -1e8, 200000, 0))
import numpy as np print "Modified internal rate of return", np.mirr([-100, 38, 48, 90, 17, 36], 0.03, 0.03)
import numpy as np
print "Modified internal rate of return", np.mirr([-100, 38, 48, 90, 17, 36],
0.03, 0.03)
def test_mirr(self):
assert_almost_equal(np.mirr((100, 200, -50, 300, -200), .05, .06),
0.342823387842, 8)
import numpy values = [1, 2, 3] finance_rate = 1 reinvest_rate = 1 numpy.mirr(values, finance_rate, reinvest_rate)
def test_mirr(self):
assert_almost_equal(np.mirr((100, 200,-50, 300,-200), .05, .06),
0.342823387842, 8)
