update libs to new ipopt version

alphamind/cython/optimizers.pyx

@@ -75,7 +75,8 @@ cdef extern from "tvoptimizer.hpp" namespace "pfopt":
                     int,
                     double*,
                     double*,
-                    double*) except +
+                    double*,
+                    string) except +
         vector[double] xValue()
         double feval()
         int status()
@@ -98,7 +99,8 @@ cdef class CVOptimizer:
                   double target_vol=1.0,
                   cnp.ndarray[double, ndim=2] factor_cov_matrix=None,
                   cnp.ndarray[double, ndim=2] factor_loading_matrix=None,
-                  double[:] idsync_risk=None):
+                  double[:] idsync_risk=None,
+                  str linear_solver="ma27"):
 
         self.n = lbound.shape[0]
         self.m = 0
@@ -125,7 +127,8 @@ cdef class CVOptimizer:
                                         self.f,
                                         &factor_cov[0] if factor_cov is not None else NULL,
                                         &factor_loading[0] if factor_loading is not None else NULL,
-                                        &idsync_risk[0] if idsync_risk is not None else NULL)
+                                        &idsync_risk[0] if idsync_risk is not None else NULL,
+                                        bytes(linear_solver, encoding='utf8'))
         else:
             self.cobj = new TVOptimizer(self.n,
                                         &expected_return[0],
@@ -140,7 +143,8 @@ cdef class CVOptimizer:
                                         self.f,
                                         &factor_cov[0] if factor_cov is not None else NULL,
                                         &factor_loading[0] if factor_loading is not None else NULL,
-                                        &idsync_risk[0] if idsync_risk is not None else NULL)
+                                        &idsync_risk[0] if idsync_risk is not None else NULL,
+                                        bytes(linear_solver, encoding='utf8'))
 
     def __dealloc__(self):
         del self.cobj
@@ -170,7 +174,8 @@ cdef extern from "mvoptimizer.hpp" namespace "pfopt":
                     int,
                     double*,
                     double*,
-                    double*) except +
+                    double*,
+                    string) except +
         vector[double] xValue()
         double feval()
         int status()
@@ -209,7 +214,8 @@ cdef class QPOptimizer:
                   double risk_aversion=1.0,
                   cnp.ndarray[double, ndim=2] factor_cov_matrix=None,
                   cnp.ndarray[double, ndim=2] factor_loading_matrix=None,
-                  double[:] idsync_risk=None):
+                  double[:] idsync_risk=None,
+                  str linear_solver='ma27'):
 
         self.n = lbound.shape[0]
         self.m = 0
@@ -239,7 +245,8 @@ cdef class QPOptimizer:
                                         self.f,
                                         &factor_cov[0] if factor_cov is not None else NULL,
                                         &factor_loading[0] if factor_loading is not None else NULL,
-                                        &idsync_risk[0] if idsync_risk is not None else NULL)
+                                        &idsync_risk[0] if idsync_risk is not None else NULL,
+                                        bytes(linear_solver, encoding='utf8'))
         else:
             self.cobj = new MVOptimizer(self.n,
                                         &expected_return[0],
@@ -254,7 +261,8 @@ cdef class QPOptimizer:
                                         self.f,
                                         &factor_cov[0] if factor_cov is not None else NULL,
                                         &factor_loading[0] if factor_loading is not None else NULL,
-                                        &idsync_risk[0] if idsync_risk is not None else NULL)
+                                        &idsync_risk[0] if idsync_risk is not None else NULL,
+                                        bytes(linear_solver, encoding='utf8'))
 
     def __dealloc__(self):
         del self.cobj

pfopt @ 148fd8ee

-Subproject commit b78ad8a55855c448a866f91a3876a271a52d68a1
+Subproject commit 148fd8eedca5aeff85d90e6374658d96316e7f66

alphamind/strategy/strategy.py

@@ -319,26 +319,10 @@ if __name__ == '__main__':
     neutralized_risk = None
 
     alpha_factors = {
-        'ep_q_cs': CSQuantiles(LAST('ep_q'), groups='sw1_adj'),
-        'roe_q_cs': CSQuantiles(LAST('roe_q'), groups='sw1_adj'),
-        'OperatingRevenueGrowRate_cs': CSQuantiles(LAST('OperatingRevenueGrowRate'), groups='sw1_adj'),
-        'GREV_cs': CSQuantiles(LAST('GREV'), groups='sw1_adj'),
-        'con_peg_rolling_cs': CSQuantiles(LAST('con_peg_rolling'), groups='sw1_adj'),
-        'con_pe_rolling_order_cs': CSQuantiles(LAST('con_pe_rolling_order'), groups='sw1_adj'),
-        'IVR_cs': CSQuantiles(LAST('IVR'), groups='sw1_adj'),
-        'ILLIQUIDITY_cs': CSQuantiles(LAST('ILLIQUIDITY') * LAST('NegMktValue'), groups='sw1_adj'),
-        'DividendPaidRatio_cs': CSQuantiles(LAST('DividendPaidRatio'), groups='sw1_adj'),
+        'ep_q_cs': CSQuantiles(LAST('ep_q'), groups='sw1_adj')
     }
 
-    weights = dict(ep_q_cs=1.,
-                   roe_q_cs=1.,
-                   OperatingRevenueGrowRate_cs=1.,
-                   GREV_cs=0.5,
-                   con_peg_rolling_cs=-0.25,
-                   con_pe_rolling_order_cs=-0.5,
-                   IVR_cs=0.5,
-                   ILLIQUIDITY_cs=0.5,
-                   DividendPaidRatio_cs=0.5)
+    weights = dict(ep_q_cs=1.)
 
     alpha_model = ConstLinearModel(features=alpha_factors, weights=weights)
 
@@ -415,4 +399,4 @@ if __name__ == '__main__':
         return ret_df
 
 
-    create_scenario(0.01, target_vol=0.02, method='tv')
+    create_scenario(0.01, target_vol=0.01, method='tv')
\ No newline at end of file

xgboost @ a187ed6c

-Subproject commit 5cd851ccef8cf0a0a71094d0d0e33a9d102f1f55
+Subproject commit a187ed6c8f3aa40b47d5be80667cbbe6a6fd563d