def constant_returns(stocks=Decimal('.04'),
bonds=Decimal('.02'),
inflation=Decimal('.02')):
return itertools.repeat(
AnnualChange(year=0, stocks=stocks, bonds=bonds, inflation=inflation))
def fmt(self, row):
return AnnualChange(year=row.name,
stocks=row['NIKKEI225'],
bonds=row['Spliced Bond'],
inflation=row['CPI Japan'])
def random_year(self):
''' This is the same method name as in market.US_1871_Returns...which
allows this to be a drop-in replacement for that when simulating data '''
r = lognormal(self.mean, self.sigma) - 1
r = Decimal(r)
return AnnualChange(year=0, stocks=r, bonds=r, inflation=Decimal(0))