def growth_pe(stockpriceserie, financialdf):
growth_pe = {}
lasteps = financialdf.eps.iloc[-1]
try:
n_year = len(financialdf) # Year duration in financialdf
growth_pe['growth_min'] = financialdf['epsgrowth'].min()
if financialdf.eps.iloc[0] >= 0:
growth_pe['growth_mean'] = round(
npf.rate(n_year, 0, -1 * financialdf.eps.iloc[0], lasteps), 4)
else:
# The above equation doesn't work mathematicaly with negative 1st year EPS.
# As alternative, mean value will be used.
growth_pe['growth_mean'] = financialdf['epsgrowth'].mean()
growth_pe['growth_max'] = financialdf['epsgrowth'].max()
pe_historical = min_mean_max_pe(stockpriceserie, financialdf)
growth_pe['pe_min'] = pe_historical[0]
growth_pe['pe_mean'] = pe_historical[1]
growth_pe['pe_max'] = pe_historical[2]
# print('growth_pe', growth_pe)
return growth_pe
except:
print('EPS does not exist.')
return {}
def get_rate_savings(self) -> float:
return (rate(
self.freq * self.num_of_years,
-self.reg_dep,
-self.ini_dep,
self.fin_bal,
self.dep_when,
) * self.freq * 100)
def get_rate_loans(self):
return (rate(
self.freq * self.num_of_years,
-self.reg_pmt,
self.loan,
0,
self.pmt_when,
) * self.freq * 100)
def calc_parameter(ask_reply, input_string):
""" calc_parameter is a calculator to calculate the final goal based on ino given by users.
Parameters
---------
Param1 : Dictionary
The dictionary stores the float provided by user as value, stores corresponding terms as the key.
Param2 : String
The string is the specified goal for caculation.
The string implies what the dictionary would be since each value is dependent to the remaining values.
Returns
------
Return1 : Float
The final result of requested value after caculation.
"""
user_fin_dict = ask_reply
try:
if (ask_reply['input_string']) == 'present value':
output = abs(
npf.pv(user_fin_dict["required rate per year"],
user_fin_dict["required time period"],
0 - user_fin_dict["payment"],
user_fin_dict["future value"]))
elif (ask_reply['input_string']) == "future value":
output = abs(
npf.fv(user_fin_dict["required rate per year"],
user_fin_dict["required time period"],
0 - user_fin_dict["payment"],
0 - user_fin_dict["present value"]))
elif (ask_reply['input_string']) == "payment":
output = abs(
npf.pmt(user_fin_dict["required rate per year"],
user_fin_dict["required time period"],
0 - user_fin_dict["present value"],
user_fin_dict["future value"]))
elif (ask_reply['input_string']) == "required rate per year":
output = abs(
npf.rate(user_fin_dict["required time period"],
0 - user_fin_dict["payment"],
0 - user_fin_dict["present value"],
user_fin_dict["future value"]))
elif (ask_reply['input_string']) == "required time period":
output = abs(
npf.nper(user_fin_dict["required rate per year"],
0 - user_fin_dict["payment"],
0 - user_fin_dict["present value"],
user_fin_dict["future value"]))
else:
output = random.choice(unknown_input_reply)
return output
except KeyError:
print("I'm dead because of you !")
print("You should never have encountered this. What did you do?")
return None
def infer_reasonable_share_price(ticker, financialreportingdf, stockpricedf, discountrate, marginrate):
years = 2 # period
dfprice = pd.DataFrame(
columns=['ticker', 'annualgrowthrate', 'lasteps', 'futureeps'])
pd.options.display.float_format = '{:20,.2f}'.format
# Find EPS Annual Compounded Growth Rate
# annualgrowthrate = financialreportingdf.epsgrowth.mean() #growth rate
# print('financialreportdf:\n',financialreportingdf)
try:
# Calcuate the rate per period
# parameter: periods , payment, present value, future value
firstEPS = financialreportingdf.eps.iloc[0]
lastEPS = financialreportingdf.eps.iloc[-1]
# Adjust firstEPS at least 1 , prevent npf.rate get NaN
if (firstEPS<1):
adj = 1 - firstEPS
firstEPS = firstEPS + adj
lastEPS = lastEPS + adj
annualgrowthrate = npf.rate(len(financialreportingdf.eps)-1, 0, -1 * firstEPS,lastEPS)
#print("Annual Growth Rate %f" % annualgrowthrate)
# Non Conservative
#print(financialreportingdf)
lasteps = financialreportingdf.eps.tail(1).values[0] # presentvalue
#print('1st eps ',financialreportingdf.eps.iloc[0])
#print('last eps ',financialreportingdf.eps.iloc[-1])
#print('annual growth rate ',annualgrowthrate)
# conservative
# lasteps = financialreportingdf.eps.mean()
# np.fv, compute the future value. parameters: interest rate , periods, payment, present value
futureeps = abs(npf.fv(annualgrowthrate, years, 0, lasteps))
dfprice.loc[0] = [ticker, annualgrowthrate, lasteps, futureeps]
except:
print('eps does not exist')
dfprice.set_index('ticker', inplace=True)
# conservative
dfprice['peratio'] = findMinimumPER(stockpricedf, financialreportingdf)
# future stock price
dfprice['FV'] = dfprice['futureeps'] * dfprice['peratio']
#print('dfprice:\n',dfprice)
#print('discountrate: %s' % discountrate)
dfprice['PV'] = abs(npf.pv(discountrate, years, 0, fv=dfprice['FV']))
if dfprice['FV'].values[0] > 0:
dfprice['marginprice'] = dfprice['PV']*(1-marginrate)
else:
dfprice['marginprice'] = 0
dfprice['lastprice'] = stockpricedf.Close.tail(1).values[0]
dfprice['suggestion'] = np.where(
(dfprice['lastprice'] < dfprice['marginprice']), 'BUY', 'SELL')
return dfprice
def test_gh48(self):
"""
Test the correct result is returned with only infeasible solutions
converted to nan.
"""
des = [-0.39920185, -0.02305873, -0.41818459, 0.26513414, numpy.nan]
nper = 2
pmt = 0
pv = [-593.06, -4725.38, -662.05, -428.78, -13.65]
fv = [214.07, 4509.97, 224.11, 686.29, -329.67]
actual = npf.rate(nper, pmt, pv, fv)
assert_allclose(actual, des)
def get_goals(goal):
print("get_goals", goal)
raw_value = npf.rate(
goal.time,
-goal.montly_contribution,
-goal.initial_contribution,
goal.goal_value,
)
monthly = round_helper(raw_value)
yearly = round(pow(12 - 1, monthly), 2)
return {"monthly": monthly, "yearly": yearly}
def test_rate_with_infeasible_solution(self, number_type, when):
"""
Test when no feasible rate can be found.
Rate will return NaN, if the Newton Raphson method cannot find a
feasible rate within the required tolerance or number of iterations.
This can occur if both `pmt` and `pv` have the same sign, as it is
impossible to repay a loan by making further withdrawls.
"""
result = npf.rate(number_type(12.0),
number_type(400.0),
number_type(10000.0),
number_type(5000.0),
when=when)
is_nan = Decimal.is_nan if number_type == Decimal else numpy.isnan
assert is_nan(result)
def test_when(self):
# begin
assert_equal(npf.rate(10, 20, -3500, 10000, 1),
npf.rate(10, 20, -3500, 10000, 'begin'))
# end
assert_equal(npf.rate(10, 20, -3500, 10000),
npf.rate(10, 20, -3500, 10000, 'end'))
assert_equal(npf.rate(10, 20, -3500, 10000, 0),
npf.rate(10, 20, -3500, 10000, 'end'))
# begin
assert_equal(npf.pv(0.07, 20, 12000, 0, 1),
npf.pv(0.07, 20, 12000, 0, 'begin'))
# end
assert_equal(npf.pv(0.07, 20, 12000, 0),
npf.pv(0.07, 20, 12000, 0, 'end'))
assert_equal(npf.pv(0.07, 20, 12000, 0, 0),
npf.pv(0.07, 20, 12000, 0, 'end'))
# begin
assert_equal(npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 1),
npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 'begin'))
# end
assert_equal(npf.pmt(0.08 / 12, 5 * 12, 15000., 0),
npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 'end'))
assert_equal(npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 0),
npf.pmt(0.08 / 12, 5 * 12, 15000., 0, 'end'))
# begin
assert_equal(npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 1),
npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 'begin'))
# end
assert_equal(npf.ppmt(0.1 / 12, 1, 60, 55000, 0),
npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 'end'))
assert_equal(npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 0),
npf.ppmt(0.1 / 12, 1, 60, 55000, 0, 'end'))
# begin
assert_equal(npf.nper(0.075, -2000, 0, 100000., 1),
npf.nper(0.075, -2000, 0, 100000., 'begin'))
# end
assert_equal(npf.nper(0.075, -2000, 0, 100000.),
npf.nper(0.075, -2000, 0, 100000., 'end'))
assert_equal(npf.nper(0.075, -2000, 0, 100000., 0),
npf.nper(0.075, -2000, 0, 100000., 'end'))
def test_decimal_with_when(self):
"""
Test that decimals are still supported if the when argument is passed
"""
# begin
assert_equal(
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), Decimal('1')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'begin'))
# end
assert_equal(
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'end'))
assert_equal(
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), Decimal('0')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'end'))
# begin
assert_equal(
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), Decimal('1')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'begin'))
# end
assert_equal(
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'end'))
assert_equal(
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), Decimal('0')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'end'))
def get_rate(self):
return fin.rate(self.n, self.pmt, self.pv, self.fv, self.when)[0]
print(
f'年利率{rate * 100}%，贷款总额￥{abs(pv)}元，每月还款￥{abs(pmt)}，需要还款{nper / 12:.2f}年，共{nper:.2f}期。还款总金额:￥{-pmt * nper:.2f}元。'
)
'''rate：计算利率'''
nper = 240
pmt = -8055.93
pv = 1000000
fv = 0
# nper：还款期数
# pmt：每期还款金额（负值）
# pv：贷款总额（正值）
# fv：期末剩余贷款金额(正值）
rate = npf.rate(nper=nper,
pmt=pmt,
pv=pv,
fv=fv,
when='end',
guess=0.1,
tol=1e-06,
maxiter=100)
print(
f'贷款总额￥{abs(pv)}元，每月还款￥{abs(pmt)}元，分{nper}期还清，期末贷款本金剩余￥{fv}元，贷款利率为：{rate * 12 * 100:.2f}%。'
)
'''npv：净现值
净现值是指投资方案所产生的【现金净流量】（流入-流出）以资金成本为贴现率折现之后与原始投资额现值的差额
经济意义:
NPV>0表示项目实施后，除保证可实现预定的收益率外，尚可获得更高的收益。
NPV<0表示项目实施后，未能达到预定的收益率水平，而不能确定项目已亏损。
NPV=0表示项目实施后的投资收益率正好达到预期，而不是投资项目盈亏平衡。
'''
rate = 0.281
values = [-100, 39, 59, 55, 20]
def test_rate_decimal(self):
rate = npf.rate(Decimal('10'), Decimal('0'), Decimal('-3500'),
Decimal('10000'))
assert_equal(Decimal('0.1106908537142689284704528100'), rate)
def test_rate(self):
assert_almost_equal(npf.rate(10, 0, -3500, 10000), 0.1107, 4)
tir = npf.irr(cf1)
tir
#MIRR - TIR Modificada
mirr = npf.mirr(cf1, wacc, 0.10)
mirr
if tir > wacc:
print("Projeto agrega valor")
else:
print("Projeto Destrói Valor")
#Qual a taxa?
taxa = npf.rate(nper, pmt, pv, fv)
#Qual Parcela
parcela = npf.pmt(rate, nper, pv)
#Valuation de Padaria
#premissas
lucro_operacional = 50000
despesas_capital = 5000
delta_ncg = 3000
reivestimento = (despesas_capital + delta_ncg)
i_crescimento = 0.02
periodo = np.array([0, 1, 2, 3, 4, 5])
def test_decimal_with_when(self):
"""
Test that decimals are still supported if the when argument is passed
"""
# begin
assert_equal(npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), Decimal('1')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'begin'))
# end
assert_equal(npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'end'))
assert_equal(npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), Decimal('0')),
npf.rate(Decimal('10'), Decimal('20'), Decimal('-3500'),
Decimal('10000'), 'end'))
# begin
assert_equal(npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), Decimal('1')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'begin'))
# end
assert_equal(npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'end'))
assert_equal(npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), Decimal('0')),
npf.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'),
Decimal('0'), 'end'))
# begin
assert_equal(npf.pmt(Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'),
Decimal('0'), Decimal('1')),
npf.pmt(Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'),
Decimal('0'), 'begin'))
# end
assert_equal(npf.pmt(Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'),
Decimal('0')),
npf.pmt(Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'),
Decimal('0'), 'end'))
assert_equal(npf.pmt(Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'),
Decimal('0'), Decimal('0')),
npf.pmt(Decimal('0.08') / Decimal('12'),
Decimal('5') * Decimal('12'), Decimal('15000.'),
Decimal('0'), 'end'))
# begin
assert_equal(npf.ppmt(Decimal('0.1') / Decimal('12'),
Decimal('1'), Decimal('60'), Decimal('55000'),
Decimal('0'), Decimal('1')),
npf.ppmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('60'), Decimal('55000'),
Decimal('0'), 'begin'))
# end
assert_equal(npf.ppmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('60'), Decimal('55000'), Decimal('0')),
npf.ppmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('60'), Decimal('55000'), Decimal('0'),
'end'))
assert_equal(npf.ppmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('60'), Decimal('55000'), Decimal('0'),
Decimal('0')),
npf.ppmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('60'), Decimal('55000'), Decimal('0'),
'end'))
# begin
assert_equal(npf.ipmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('24'), Decimal('2000'),
Decimal('0'), Decimal('1')).flat[0],
npf.ipmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('24'), Decimal('2000'),
Decimal('0'), 'begin').flat[0])
# end
assert_equal(npf.ipmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('24'), Decimal('2000'),
Decimal('0')).flat[0],
npf.ipmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('24'), Decimal('2000'),
Decimal('0'), 'end').flat[0])
assert_equal(npf.ipmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('24'), Decimal('2000'),
Decimal('0'), Decimal('0')).flat[0],
npf.ipmt(Decimal('0.1') / Decimal('12'), Decimal('1'),
Decimal('24'), Decimal('2000'),
Decimal('0'), 'end').flat[0])
