4Fundos DEFfloat64
4Fundos EWfloat64
2023-01-13 00:00:00
-12.84
-13.21
#### Returns ####
returns = (fundos_norm / fundos_norm.shift(1)) - 1
# Resampling to yearly (business year)
yearly_quotes = fundos_norm.resample('BA').last()
# Adding first quote (only if start is in the middle of the year)
yearly_quotes = pd.concat([fundos_norm.iloc[:1], yearly_quotes])
CAGRobject
Returnobject
4Fundos DEF
4.47%
99.00%
4Fundos EW
5.70%
139.41%
4Fundos AGR
6.83%
183.16%
Beginobject
Endobject
1
2007-06-01
2009-10-07
2
2021-11-16
N/A
3
2020-02-19
2020-10-12
4
2015-04-15
2016-08-05
5
2018-08-10
2019-03-29
Beginobject
Endobject
1
2007-06-01
2010-03-04
2
2020-02-19
2020-11-16
3
2021-11-16
N/A
4
2015-04-13
2016-11-24
5
2018-06-15
2019-04-03
Beginobject
Endobject
1
2007-06-01
2010-11-26
2
2020-02-19
2020-11-24
3
2021-11-16
N/A
4
2015-04-13
2016-12-08
5
2018-06-14
2019-04-12
EW = pl.compute_portfolio(ETFs, [0.50, 0.50])
EW.columns = ['ETFs']
portfolios = pl.normalize(pl.merge_time_series(fundos[['4Fundos EW']], EW).dropna())
portfolios = pl.normalize(portfolios['2016-11-11':])
pl.ichart(portfolios, yticksuffix='€')
pl.ichart(pl.compute_drawdowns(portfolios), yticksuffix='%')
pl.compute_performance_table(portfolios)
CAGRobject
Returnobject
4Fundos EW
3.93%
26.91%
ETFs
4.37%
30.23%