def plot_risk_con(
w,
cov=None,
returns=None,
rm="MV",
rf=0,
alpha=0.05,
color="tab:blue",
height=6,
width=10,
ax=None,
):
r"""
Create a chart with the risk contribution per asset of the portfolio.
Parameters
----------
w : DataFrame of shape (n_assets, 1)
Portfolio weights.
cov : DataFrame of shape (n_features, n_features)
Covariance matrix, where n_features is the number of features.
returns : DataFrame of shape (n_samples, n_features)
Features matrix, where n_samples is the number of samples and
n_features is the number of features.
rm : str, optional
Risk measure used to estimate risk contribution.
The default is 'MV'. Posible values are:
- 'MV': Standard Deviation.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'CVaR': Conditional Value at Risk.
- 'EVaR': Conditional Value at Risk.
- 'WR': Worst Realization (Minimax)
- 'MDD': Maximum Drawdown of uncompounded returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded returns.
- 'DaR': Drawdown at Risk of uncompounded returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded returns.
- 'UCI': Ulcer Index of uncompounded returns.
rf : float, optional
Risk free rate or minimum aceptable return. The default is 0.
alpha : float, optional
Significante level of VaR, CVaR and CDaR. The default is 0.05.
color : str, optional
Color used to plot each asset risk contribution.
The default is 'tab:blue'.
height : float, optional
Height of the image in inches. The default is 6.
width : float, optional
Width of the image in inches. The default is 10.
ax : matplotlib axis, optional
If provided, plot on this axis. The default is None.
Raises
------
ValueError
When the value cannot be calculated.
Returns
-------
ax : matplotlib axis.
Returns the Axes object with the plot for further tweaking.
Example
-------
::
ax = plf.plot_risk_con(w=w2, cov=cov, returns=returns, rm='MSV',
rf=0, alpha=0.05, color="tab:blue", height=6,
width=10, ax=None)
.. image:: images/Risk_Con.png
"""
if not isinstance(w, pd.DataFrame):
raise ValueError("w must be a DataFrame")
if ax is None:
ax = plt.gca()
fig = plt.gcf()
fig.set_figwidth(width)
fig.set_figheight(height)
item = rmeasures.index(rm)
title = "Risk (" + rm_names[item] + ") Contribution per Asset"
ax.set_title(title)
X = w.index.tolist()
RC = rk.Risk_Contribution(w,
cov=cov,
returns=returns,
rm=rm,
rf=rf,
alpha=alpha)
ax.bar(X, RC, alpha=0.7, color=color, edgecolor="black")
ax.set_xlim(-0.5, len(X) - 0.5)
ax.set_yticks(ax.get_yticks())
ax.set_yticklabels(["{:3.5%}".format(x) for x in ax.get_yticks()])
ax.grid(linestyle=":")
fig = plt.gcf()
fig.tight_layout()
return ax
def plot_risk_con(
w,
cov=None,
returns=None,
rm="MV",
rf=0,
alpha=0.01,
color="tab:blue",
height=6,
width=10,
ax=None,
):
r"""
Create a chart with the risk contribution per asset of the portfolio.
Parameters
----------
w : DataFrame
Weights of a portfolio.
cov : DataFrame of shape (n_features, n_features)
Covariance matrix, where n_features is the number of features.
returns : DataFrame of shape (n_samples, n_features)
Features matrix, where n_samples is the number of samples and
n_features is the number of features.
rm : str, optional
Risk measure used to estimate risk contribution. The default is 'MV'.
rf : float, optional
Risk free rate or minimum aceptable return. The default is 0.
alpha : float, optional
Significante level of VaR, CVaR and CDaR. The default is 0.01.
color : str, optional
Color used to plot each asset risk contribution.
The default is 'tab:blue'.
height : float, optional
Height of the image in inches. The default is 6.
width : float, optional
Width of the image in inches. The default is 10.
ax : matplotlib axis, optional
If provided, plot on this axis. The default is None.
Raises
------
ValueError
When the value cannot be calculated.
Returns
-------
ax : matplotlib axis.
Returns the Axes object with the plot for further tweaking.
Example
-------
::
ax = plf.plot_risk_con(w=w2, cov=cov, returns=returns, rm='MSV',
rf=0, alpha=0.01, cmap="tab20", height=6,
width=10, ax=None)
.. image:: images/Risk_Con.png
"""
if not isinstance(w, pd.DataFrame):
raise ValueError("w must be a DataFrame")
if ax is None:
ax = plt.gca()
fig = plt.gcf()
fig.set_figwidth(width)
fig.set_figheight(height)
item = rmeasures.index(rm)
title = "Risk (" + rm_names[item] + ") Contribution per Asset"
ax.set_title(title)
X = w.index.tolist()
RC = rk.Risk_Contribution(w, cov=cov, returns=returns, rm=rm, rf=rf, alpha=alpha)
ax.bar(X, RC, alpha=0.7, color=color, edgecolor="black")
ax.set_xlim(-0.5, len(X) - 0.5)
ax.set_yticks(ax.get_yticks())
ax.set_yticklabels(["{:3.5%}".format(x) for x in ax.get_yticks()])
ax.grid(linestyle=":")
fig = plt.gcf()
fig.tight_layout()
return ax