def plot(self,
ucrp=False,
bah=False,
residual=False,
assets=False,
**kwargs):
""" Plot strategy equity.
:param ucrp: Add uniform CRP as a benchmark.
:param bah: Add Buy-And-Hold portfolio as a benchmark.
:param residual: Add portfolio minus UCRP as a benchmark.
:param assets: Add asset prices.
:param kwargs: Additional arguments for pd.DataFrame.plot
"""
# NOTE: order of plotting is important because of coloring
# plot portfolio
d = self.to_dataframe()
D = d.copy()
# add individual assets
if isinstance(assets, bool):
if assets:
assets = self[0].asset_equity.columns
else:
assets = []
if list(assets):
D = D.join(self[0].asset_equity)
ax = D.plot(color=_colors_hash(D.columns), **kwargs)
kwargs['ax'] = ax
ax.set_ylabel('Total wealth')
# plot residual strategy
if residual:
d['RESIDUAL'] = self[0].residual_r.cumprod()
d[['RESIDUAL']].plot(**kwargs)
# plot uniform constant rebalanced portfolio
if ucrp:
from .algos import CRP
crp_algo = CRP().run(self[0].X.cumprod())
crp_algo.fee = self[0].fee
d['UCRP'] = crp_algo.equity
d[['UCRP']].plot(**kwargs)
# add bah
if bah:
from .algos import BAH
bah_algo = BAH().run(self[0].X.cumprod())
bah_algo.fee = self[0].fee
d['BAH'] = bah_algo.equity
d[['BAH']].plot(**kwargs)
return ax
def plot(self, ucrp=False, bah=False, assets=False, **kwargs):
""" Plot strategy equity.
:param ucrp: Add uniform CRP as a benchmark.
:param bah: Add Buy-And-Hold portfolio as a benchmark.
:param assets: Add asset prices.
:param kwargs: Additional arguments for pd.DataFrame.plot
"""
# NOTE: order of plotting is important because of coloring
# plot portfolio
d = self.to_dataframe()
portfolio = d.copy()
ax = portfolio.plot(linewidth=3., legend=False, **kwargs)
kwargs['ax'] = ax
ax.set_ylabel('Total wealth')
# plot uniform constant rebalanced portfolio
if ucrp:
from universal.algos import CRP
crp_algo = CRP().run(self[0].X.cumprod())
crp_algo.fee = self[0].fee
d['UCRP'] = crp_algo.equity
d[['UCRP']].plot(**kwargs)
# add bah
if bah:
from universal.algos import BAH
bah_algo = BAH().run(self[0].X.cumprod())
bah_algo.fee = self[0].fee
d['BAH'] = bah_algo.equity
d[['BAH']].plot(**kwargs)
# add individual assets
if isinstance(assets, bool):
if assets:
assets = self[0].asset_equity.columns
else:
assets = []
if list(assets):
self[0].asset_equity.sort_index(axis=1).plot(
color=_colors(len(assets) + 1), **kwargs)
# plot portfolio again to highlight it
kwargs['color'] = 'blue'
portfolio.plot(linewidth=3., **kwargs)
return ax
def plot(self, ucrp=False, bah=False, assets=False, **kwargs):
""" Plot strategy equity.
:param ucrp: Add uniform CRP as a benchmark.
:param bah: Add Buy-And-Hold portfolio as a benchmark.
:param assets: Add asset prices.
:param kwargs: Additional arguments for pd.DataFrame.plot
"""
# NOTE: order of plotting is important because of coloring
# plot portfolio
d = self.to_dataframe()
portfolio = d.copy()
ax = portfolio.plot(linewidth=3., legend=False, **kwargs)
kwargs['ax'] = ax
ax.set_ylabel('Total wealth')
# plot uniform constant rebalanced portfolio
if ucrp:
from algos import CRP
crp_algo = CRP().run(self[0].X.cumprod())
crp_algo.fee = self[0].fee
d['UCRP'] = crp_algo.equity
d[['UCRP']].plot(**kwargs)
# add bah
if bah:
from algos import BAH
bah_algo = BAH().run(self[0].X.cumprod())
bah_algo.fee = self[0].fee
d['BAH'] = bah_algo.equity
d[['BAH']].plot(**kwargs)
# add individual assets
if isinstance(assets, bool):
if assets:
assets = self[0].asset_equity.columns
else:
assets = []
if list(assets):
self[0].asset_equity.sort_index(axis=1).plot(color=_colors(len(assets) + 1), **kwargs)
# plot portfolio again to highlight it
kwargs['color'] = 'blue'
portfolio.plot(linewidth=3., **kwargs)
return ax
