def __init__(self, r, fee=0., fee_freq='Q', start=None, end=None,
lookback={}, strict=False, dist_amt=None, dist_pct=None,
dist_freq=None, v0=float(1e6), include_start=True, freq='M',
name=None, in_format='num'):
self.gross = returns.prep(r=r, freq=freq, name=name,
in_format=in_format)
# fee_freq: if str -> frequency; if int/float -> periods/yr
# Get `fee` to a per-period float
if isinstance(fee_freq, (int, float)):
self.fee_freq = fee_freq
self.fee = fee / self.fee_freq
elif isinstance(fee_freq, str):
self.fee_freq = utils.convertfreq(fee_freq)
self.fee = fee / self.fee_freq
# Logic for interaction of `start`, `end`, and `lookback`
# TODO: how should lookback be passed? Consider params to
# `constrain_horizon`
if any((start, end)) and not lookback:
self.gross = self.gross[start:end]
elif lookback:
# TODO: cleanup
self.gross = utils.constrain_horizon(self.gross, **lookback)
elif all((any((start, end)), lookback)):
raise ValueError('if `lookback` is specified, both `start` and'
' `end` should be None')
self.index = self.gross.index
self.columns = self.gross.columns
masktypes = {12. : 'is_month_end',
4. : 'is_quarter_end',
1. : 'is_quarter_end'}
mask = getattr(self.index, masktypes[self.fee_freq])
self.feesched = np.where(mask, self.fee, 0.)
# Net of fees (not yet of distributions)
self.net = (1. + self.gross.values) \
* (1. - self.feesched.reshape(-1,1)) - 1.
self.net = DataFrame(self.net, index=self.index, columns=self.columns)
self.dist_amt = dist_amt
self.dist_pct = dist_pct
self.dist_freq = dist_freq
self.v0 = v0
self.include_start = include_start
def amortize(rate, nper, pv, freq='M'):
"""Construct an amortization schedule for a fixed-rate loan.
Rate -> annualized input
Example
=======
# a 6.75% $200,000 loan, 30-year tenor, payments due monthly
# view the 5 final months
print(amortize(rate=.0675, nper=30, pv=200000).round(2).tail())
beg_bal prin interest end_bal
356 6377.95 -1261.32 -35.88 5116.63
357 5116.63 -1268.42 -28.78 3848.22
358 3848.22 -1275.55 -21.65 2572.67
359 2572.67 -1282.72 -14.47 1289.94
360 1289.94 -1289.94 -7.26 -0.00
"""
freq = utils.convertfreq(freq)
rate = rate / freq
nper = nper * freq
periods = np.arange(1, nper + 1, dtype=int)
principal = np.ppmt(rate, periods, nper, pv)
interest = np.ipmt(rate, periods, nper, pv)
pmt = np.pmt(rate, nper, pv)
def balance(pv, rate, nper, pmt):
dfac = (1 + rate)**nper
return pv * dfac - pmt * (dfac - 1) / rate
res = DataFrame(
{
'beg_bal': balance(pv, rate, periods - 1, -pmt),
'prin': principal,
'interest': interest,
'end_bal': balance(pv, rate, periods, -pmt)
},
index=periods)['beg_bal', 'prin', 'interest', 'end_bal']
return res