Update Solvers RLVaR

Use CLARABEL as default solver for RLVaR and RLDaR
dcajasn · Jan 6, 2024 · 88f283a · 88f283a
1 parent 0e37f1b
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diff --git a/examples/Tutorial 38 - Mean Kurtosis Optimization.ipynb b/examples/Tutorial 38 - Mean Kurtosis Optimization.ipynb
@@ -434,8 +434,7 @@
     "                  method_kurt=method_kurt,\n",
     "                  )\n",
     "\n",
-    "port.solvers = ['MOSEK'] # It is recommended to use mosek when optimizing GMD\n",
-    "port.sol_params = {'MOSEK': {'mosek_params': {'MSK_IPAR_NUM_THREADS': 2}}}\n",
+    "port.solvers = ['CLARABEL'] # It is recommended to use mosek when optimizing GMD\n",
     "\n",
     "# Estimate optimal portfolio:\n",
     "model ='Classic' # Could be Classic (historical), BL (Black Litterman) or FM (Factor Model)\n",

diff --git a/examples/Tutorial 39 - Mean Semi Kurtosis Optimization.ipynb b/examples/Tutorial 39 - Mean Semi Kurtosis Optimization.ipynb
@@ -436,8 +436,8 @@
     "\n",
     "# Estimate optimal portfolio:\n",
     "\n",
-    "port.solvers = ['MOSEK'] # It is recommended to use mosek when optimizing GMD\n",
-    "port.sol_params = {'MOSEK': {'mosek_params': {'MSK_IPAR_NUM_THREADS': 2}}}\n",
+    "port.solvers = ['CLARABEL'] # It is recommended to use mosek when optimizing GMD\n",
+    "#port.sol_params = {'MOSEK': {'mosek_params': {'MSK_IPAR_NUM_THREADS': 2}}}\n",
     "\n",
     "model ='Classic' # Could be Classic (historical), BL (Black Litterman) or FM (Factor Model)\n",
     "rm = 'SKT' # Risk measure used, this time will be Tail Gini Range\n",

diff --git a/riskfolio/src/HCPortfolio.py b/riskfolio/src/HCPortfolio.py
@@ -51,7 +51,7 @@ class HCPortfolio(object):
         The default value is None.
     solvers: list, optional
         List of solvers available for CVXPY used for the selected NCO method.
-        The default value is None.
+        The default value is ['CLARABEL', 'SCS', 'ECOS'].
     w_max : pd.Series or float, optional
         Upper bound constraint for hierarchical risk parity weights :cite:`c-Pfitzinger`.
     w_min : pd.Series or float, optional
@@ -79,8 +79,8 @@ def __init__(
         beta=None,
         b_sim=None,
         kappa=0.30,
-        solver_rl=None,
-        solvers=None,
+        solver_rl='CLARABEL',
+        solvers=['CLARABEL', 'SCS', 'ECOS'],
         w_max=None,
         w_min=None,
         alpha_tail=0.05,

diff --git a/riskfolio/src/OwaWeights.py b/riskfolio/src/OwaWeights.py
@@ -306,7 +306,7 @@ def owa_tgrg(T, alpha=0.05, a_sim=100, beta=None, b_sim=None):
     return w_
 
 
-def owa_l_moment_crm(T, k=4, method="MSD", g=0.5, max_phi=0.5, solver=None):
+def owa_l_moment_crm(T, k=4, method="MSD", g=0.5, max_phi=0.5, solver='CLARABEL'):
     r"""
     Calculate the OWA weights to calculate a convex risk measure that considers
     higher linear moments or L-moments as shown in :cite:`d-Cajas6`.
@@ -333,7 +333,7 @@ def owa_l_moment_crm(T, k=4, method="MSD", g=0.5, max_phi=0.5, solver=None):
         The default is 0.5.
     solver: str, optional
         Solver available for CVXPY. Used to calculate 'ME', 'MSS' and 'MSD' weights.
-        The default value is None.
+        The default value is 'CLARABEL'.
 
     Returns
     -------

diff --git a/riskfolio/src/PlotFunctions.py b/riskfolio/src/PlotFunctions.py
@@ -223,7 +223,7 @@ def plot_frontier(
     beta=None,
     b_sim=None,
     kappa=0.30,
-    solver=None,
+    solver='CLARABEL',
     cmap="viridis",
     w=None,
     label="Portfolio",
@@ -298,7 +298,7 @@ def plot_frontier(
         Deformation parameter of RLVaR and RLDaR, must be between 0 and 1. The default is 0.30.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
     cmap : cmap, optional
         Colorscale that represents the risk adjusted return ratio.
         The default is 'viridis'.
@@ -1103,7 +1103,7 @@ def plot_risk_con(
     beta=None,
     b_sim=None,
     kappa=0.30,
-    solver=None,
+    solver='CLARABEL',
     percentage=False,
     erc_line=True,
     color="tab:blue",
@@ -1168,7 +1168,7 @@ def plot_risk_con(
         Deformation parameter of RLVaR and RLDaR, must be between 0 and 1. The default is 0.30.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
     percentage : bool, optional
         If risk contribution per asset is expressed as percentage or as a value. The default is False.
     erc_line : bool, optional
@@ -1331,7 +1331,7 @@ def plot_hist(
     alpha=0.05,
     a_sim=100,
     kappa=0.30,
-    solver=None,
+    solver='CLARABEL',
     bins=50,
     height=6,
     width=10,
@@ -1354,7 +1354,7 @@ def plot_hist(
         Deformation parameter of RLVaR and RLDaR, must be between 0 and 1. The default is 0.30.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
     bins : float, optional
         Number of bins of the histogram. The default is 50.
     height : float, optional
@@ -1490,11 +1490,11 @@ def plot_hist(
         y,
         "--",
         color="orange",
-        label=r"Normal: \$\mu="
+        label=r"Normal: $\mu="
         + "{0:.2%}".format(mu)
-        + "\$%, \$\sigma="
+        + "$%, $\sigma="
         + "{0:.2%}".format(sigma)
-        + "\$%",
+        + "$%",
     )
 
     factor = (np.max(a) - np.min(a)) / bins
@@ -1730,7 +1730,7 @@ def plot_drawdown(
     w,
     alpha=0.05,
     kappa=0.30,
-    solver=None,
+    solver='CLARABEL',
     height=8,
     width=10,
     height_ratios=[2, 3],
@@ -1751,7 +1751,7 @@ def plot_drawdown(
         Deformation parameter of RLVaR and RLDaR, must be between 0 and 1. The default is 0.30.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
     height : float, optional
         Height of the image in inches. The default is 8.
     width : float, optional
@@ -1920,7 +1920,7 @@ def plot_table(
     alpha=0.05,
     a_sim=100,
     kappa=0.30,
-    solver=None,
+    solver='CLARABEL',
     height=9,
     width=12,
     t_factor=252,
@@ -1955,7 +1955,7 @@ def plot_table(
         Deformation parameter of RLVaR and RLDaR, must be between 0 and 1. The default is 0.30.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
     height : float, optional
         Height of the image in inches. The default is 9.
     width : float, optional

diff --git a/riskfolio/src/Portfolio.py b/riskfolio/src/Portfolio.py
@@ -3967,7 +3967,7 @@ def efficient_frontier(
         kelly=False,
         points=20,
         rf=0,
-        solver=None,
+        solver='CLARABEL',
         hist=True,
     ):
         r"""
@@ -4019,7 +4019,7 @@ def efficient_frontier(
             Risk free rate. The default is 0.
         solver: str, optional
             Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-            The default value is None.
+            The default value is 'CLARABEL'.
         hist : bool, optional
             Indicate what kind of returns are used to calculate risk measures
             that depends on scenarios (All except 'MV' risk measure).
@@ -4304,6 +4304,12 @@ def reset_linear_constraints(self):
 
         self.ainequality = None
         self.binequality = None
+        self.b = None
+        self.network_sdp = None
+        self.network_penalty = 0.05
+        self.network_ip = None
+        self.acentrality = None
+        self.bcentrality = None
 
     def reset_inputs(self):
         r"""
@@ -4360,9 +4366,10 @@ def reset_all(self):
         self.beta = None
         self.b_sim = None
         self.kappa = 0.30
+        self.n_max_kurt = 50
         self.kindbench = True
         self.benchindex = None
-        self._benchweights = None
+        self.benchweights = None
         self.allowTO = False
         self.turnover = 0.05
         self.allowTE = False

diff --git a/riskfolio/src/Reports.py b/riskfolio/src/Reports.py
@@ -41,7 +41,7 @@ def jupyter_report(
     beta=None,
     b_sim=None,
     kappa=0.30,
-    solver=None,
+    solver='CLARABEL',
     percentage=False,
     erc_line=True,
     color="tab:blue",
@@ -111,7 +111,7 @@ def jupyter_report(
         Deformation parameter of RLVaR and RLDaR, must be between 0 and 1. The default is 0.30.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
     percentage : bool, optional
         If risk contribution per asset is expressed as percentage or as a value. The default is False.
     erc_line : bool, optional
@@ -204,8 +204,8 @@ def jupyter_report(
         MAR=rf,
         alpha=alpha,
         a_sim=a_sim,
-        kappa=0.30,
-        solver=None,
+        kappa=kappa,
+        solver=solver,
         t_factor=t_factor,
         ini_days=ini_days,
         days_per_year=days_per_year,

diff --git a/riskfolio/src/RiskFunctions.py b/riskfolio/src/RiskFunctions.py
@@ -496,7 +496,7 @@ def EVaR_Hist(X, alpha=0.05):
     return (value, t)
 
 
-def RLVaR_Hist(X, alpha=0.05, kappa=0.01, solver=None):
+def RLVaR_Hist(X, alpha=0.05, kappa=0.3, solver='CLARABEL'):
     r"""
     Calculate the Relativistic Value at Risk (RLVaR) of a returns series.
     I recommend only use this function with MOSEK solver.
@@ -523,10 +523,10 @@ def RLVaR_Hist(X, alpha=0.05, kappa=0.01, solver=None):
     alpha : float, optional
         Significance level of EVaR. The default is 0.05.
     kappa : float, optional
-        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.01.
+        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.3.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
 
     Raises
     ------
@@ -858,7 +858,7 @@ def EDaR_Abs(X, alpha=0.05):
     return (value, t)
 
 
-def RLDaR_Abs(X, alpha=0.05, kappa=0.01, solver=None):
+def RLDaR_Abs(X, alpha=0.05, kappa=0.3, solver='CLARABEL'):
     r"""
     Calculate the Relativistic Drawdown at Risk (RLDaR) of a returns series
     using uncompounded cumulative returns. I recommend only use this function with MOSEK solver.
@@ -875,10 +875,10 @@ def RLDaR_Abs(X, alpha=0.05, kappa=0.01, solver=None):
     alpha : float, optional
         Significance level of EVaR. The default is 0.05.
     kappa : float, optional
-        Deformation parameter of RLDaR, must be between 0 and 1. The default is 0.01.
+        Deformation parameter of RLDaR, must be between 0 and 1. The default is 0.3.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
 
     Raises
     ------
@@ -1239,7 +1239,7 @@ def EDaR_Rel(X, alpha=0.05):
     return (value, t)
 
 
-def RLDaR_Rel(X, alpha=0.05, kappa=0.01, solver=None):
+def RLDaR_Rel(X, alpha=0.05, kappa=0.3, solver='CLARABEL'):
     r"""
     Calculate the Relativistic Drawdown at Risk (RLDaR) of a returns series
     using compounded cumulative returns. I recommend only use this function with MOSEK solver.
@@ -1256,10 +1256,10 @@ def RLDaR_Rel(X, alpha=0.05, kappa=0.01, solver=None):
     alpha : float, optional
         Significance level of RLDaR. The default is 0.05.
     kappa : float, optional
-        Deformation parameter of RLDaR, must be between 0 and 1. The default is 0.01.
+        Deformation parameter of RLDaR, must be between 0 and 1. The default is 0.3.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
 
     Raises
     ------
@@ -1581,7 +1581,7 @@ def L_Moment(X, k=2):
     return value
 
 
-def L_Moment_CRM(X, k=4, method="MSD", g=0.5, max_phi=0.5, solver=None):
+def L_Moment_CRM(X, k=4, method="MSD", g=0.5, max_phi=0.5, solver='CLARABEL'):
     r"""
     Calculate a custom convex risk measure that is a weighted average of
     first k-th l-moments.
@@ -1662,8 +1662,8 @@ def Sharpe_Risk(
     a_sim=100,
     beta=None,
     b_sim=None,
-    kappa=0.01,
-    solver=None,
+    kappa=0.3,
+    solver='CLARABEL',
 ):
     r"""
     Calculate the risk measure available on the Sharpe function.
@@ -1726,10 +1726,10 @@ def Sharpe_Risk(
         Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value.
         The default is None.
     kappa : float, optional
-        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.01.
+        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.3.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
-        The default value is None.
+        The default value is 'CLARABEL'.
 
     Raises
     ------
@@ -1835,8 +1835,8 @@ def Sharpe(
     a_sim=100,
     beta=None,
     b_sim=None,
-    kappa=0.01,
-    solver=None,
+    kappa=0.3,
+    solver='CLARABEL',
 ):
     r"""
     Calculate the Risk Adjusted Return Ratio from a portfolio returns series.
@@ -1916,7 +1916,7 @@ def Sharpe(
         Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value.
         The default is None.
     kappa : float, optional
-        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.01.
+        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.3.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
         The default value is None.
@@ -2018,7 +2018,7 @@ def L_Moment(X, k=2):
     return value
 
 
-def L_Moment_CRM(X, k=4, method="MSD", g=0.5, max_phi=0.5, solver=None):
+def L_Moment_CRM(X, k=4, method="MSD", g=0.5, max_phi=0.5, solver='CLARABEL'):
     r"""
     Calculate a custom convex risk measure that is a weighted average of
     first k-th l-moments.
@@ -2045,7 +2045,7 @@ def L_Moment_CRM(X, k=4, method="MSD", g=0.5, max_phi=0.5, solver=None):
         The default is 0.5.
     solver: str, optional
         Solver available for CVXPY. Used to calculate 'ME', 'MSS' and 'MSD' weights.
-        The default value is None.
+        The default value is 'CLARABEL'.
 
     Raises
     ------
@@ -2099,8 +2099,8 @@ def Risk_Contribution(
     a_sim=100,
     beta=None,
     b_sim=None,
-    kappa=0.01,
-    solver=None,
+    kappa=0.3,
+    solver='CLARABEL',
 ):
     r"""
     Calculate the risk contribution for each asset based on the risk measure
@@ -2164,7 +2164,7 @@ def Risk_Contribution(
         Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value.
         The default is None.
     kappa : float, optional
-        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.01.
+        Deformation parameter of RLVaR, must be between 0 and 1. The default is 0.3.
     solver: str, optional
         Solver available for CVXPY that supports power cone programming. Used to calculate RLVaR and RLDaR.
         The default value is None.