问题
numpy has irr and npv function, but I need xirr and xnpv function.
this link points out that xirr and xnpv will be coming soon. http://www.projectdirigible.com/documentation/spreadsheet-functions.html#coming-soon
Is there any python library that has those two functions? tks.
回答1:
With the help of various implementations I found in the net, I came up with a python implementation:
def xirr(transactions):
years = [(ta[0] - transactions[0][0]).days / 365.0 for ta in transactions]
residual = 1
step = 0.05
guess = 0.05
epsilon = 0.0001
limit = 10000
while abs(residual) > epsilon and limit > 0:
limit -= 1
residual = 0.0
for i, ta in enumerate(transactions):
residual += ta[1] / pow(guess, years[i])
if abs(residual) > epsilon:
if residual > 0:
guess += step
else:
guess -= step
step /= 2.0
return guess-1
from datetime import date
tas = [ (date(2010, 12, 29), -10000),
(date(2012, 1, 25), 20),
(date(2012, 3, 8), 10100)]
print xirr(tas) #0.0100612640381
回答2:
Here is one way to implement the two functions.
import scipy.optimize
def xnpv(rate, values, dates):
'''Equivalent of Excel's XNPV function.
>>> from datetime import date
>>> dates = [date(2010, 12, 29), date(2012, 1, 25), date(2012, 3, 8)]
>>> values = [-10000, 20, 10100]
>>> xnpv(0.1, values, dates)
-966.4345...
'''
if rate <= -1.0:
return float('inf')
d0 = dates[0] # or min(dates)
return sum([ vi / (1.0 + rate)**((di - d0).days / 365.0) for vi, di in zip(values, dates)])
def xirr(values, dates):
'''Equivalent of Excel's XIRR function.
>>> from datetime import date
>>> dates = [date(2010, 12, 29), date(2012, 1, 25), date(2012, 3, 8)]
>>> values = [-10000, 20, 10100]
>>> xirr(values, dates)
0.0100612...
'''
try:
return scipy.optimize.newton(lambda r: xnpv(r, values, dates), 0.0)
except RuntimeError: # Failed to converge?
return scipy.optimize.brentq(lambda r: xnpv(r, values, dates), -1.0, 1e10)
回答3:
With Pandas, I got the following to work: (note, I'm using ACT/365 convention)
rate = 0.10
dates= pandas.date_range(start=pandas.Timestamp('2015-01-01'),periods=5, freq="AS")
cfs = pandas.Series([-500,200,200,200,200],index=dates)
# intermediate calculations( if interested)
# cf_xnpv_days = [(cf.index[i]-cf.index[i-1]).days for i in range(1,len(cf.index))]
# cf_xnpv_days_cumulative = [(cf.index[i]-cf.index[0]).days for i in range(1,len(cf.index))]
# cf_xnpv_days_disc_factors = [(1+rate)**(float((cf.index[i]-cf.index[0]).days)/365.0)-1 for i in range(1,len(cf.index))]
cf_xnpv_days_pvs = [cf[i]/float(1+(1+rate)**(float((cf.index[i]-cf.index[0]).days)/365.0)-1) for i in range(1,len(cf.index))]
cf_xnpv = cf[0]+ sum(cf_xnpv_days_pvs)
来源:https://stackoverflow.com/questions/8919718/financial-python-library-that-has-xirr-and-xnpv-function