j arguments and tests

Author: microprediction

precise/skaters/managers/allmanagers.py

@@ -2,7 +2,7 @@
 from precise.skaters.managers.ppomanagers import PPO_LONG_MANGERS
 from precise.skaters.managers.hrpmanagers import HRP_LONG_MANAGERS
 from precise.skaters.managers.schurmanagers import SCHUR_LONG_MANAGERS
-from precise.skaters.managers.rflmanagers import RFL_HRP_LONG_MANAGERS
+#from precise.skaters.managers.rflmanagers import RFL_HRP_LONG_MANAGERS
 from precise.skaters.managers.equalmanagers import EQUAL_LONG_MANAGERS
 from precise.skaters.managers.ldpmanagers import LDP_LONG_MANAGERS
 from precise.skaters.managers.molybogamanagers import MOLYBOGA_LONG_MANAGERS
@@ -12,9 +12,9 @@
 
 # d0 managers unless otherwise stated
 
-LONG_MANAGERS = WEAK_LONG_MANAGERS + PPO_LONG_MANGERS + HRP_LONG_MANAGERS + SCHUR_LONG_MANAGERS + RFL_HRP_LONG_MANAGERS
+LONG_MANAGERS = WEAK_LONG_MANAGERS + PPO_LONG_MANGERS + HRP_LONG_MANAGERS + SCHUR_LONG_MANAGERS
 LONG_MANAGERS = WEAK_LONG_MANAGERS + PPO_LONG_MANGERS[:100] + HRP_LONG_MANAGERS +\
-SCHUR_LONG_MANAGERS + RFL_HRP_LONG_MANAGERS[:2] + EQUAL_LONG_MANAGERS + LDP_LONG_MANAGERS + MOLYBOGA_LONG_MANAGERS + RP_LONG_MANAGERS
+SCHUR_LONG_MANAGERS + EQUAL_LONG_MANAGERS + LDP_LONG_MANAGERS + MOLYBOGA_LONG_MANAGERS + RP_LONG_MANAGERS
 
 RELIABLE_LONG_MANAGERS = [ m for m in LONG_MANAGERS if not 'ppo' in m.__name__]
 

precise/skaters/managers/covmanagerfactory.py

@@ -5,6 +5,7 @@
 from precise.skaters.locationutil.vectorfunctions import normalize
 
 
+
 def _buy_and_hold_port(port, j:int, y, s:dict, cov, port_kwargs):
     """
 
@@ -20,24 +21,27 @@ def _buy_and_hold_port(port, j:int, y, s:dict, cov, port_kwargs):
     :return:  w   Portfolio weights
     """
     if j==1:
-        return port(cov=cov, **port_kwargs)
+        w = port(cov=cov, **port_kwargs)
+        s = {}
+        return w, s
     else:
         n_dim = len(y)
         if s.get('w') is None:
             s['multiplier']=[1 for _ in range(n_dim)]
             s['count']=0
             s['w'] = port(cov=cov, **port_kwargs)
-            return s['w']
+            w = s['w']
+            return w, s
         else:
             s['count'] = s['count']+1
             if s['count'] % j == 0:
                 s['multiplier'] = [1 for _ in range(n_dim)]
                 s['w'] = port(cov=cov, **port_kwargs)
-                return s['w']
+                return s['w'], s
             else:
                 s['multiplier'] = [ mi*math.exp(yi) for mi,yi in zip(s['multiplier'],y)]
                 w = normalize( [ wi*mi for wi,mi in zip(s['w'],s['multiplier']) ] )
-                return w
+                return w, s
 
 
 def static_cov_manager_factory_d0(y, s, f, port, e=1, f_kwargs:dict=None, port_kwargs:dict=None, n_cold=5, zeta=0.0, j=1):
@@ -64,14 +68,15 @@ def static_cov_manager_factory_d0(y, s, f, port, e=1, f_kwargs:dict=None, port_k
         s = {'f_state':{},
              'port_state':{},
              'count':0,
-             'hodl_state':{}}
+             'account_state':{}}
 
 
     x_mean, x_cov, s['f_state'] = f(y=y,s=s['f_state'], k=1, e=e, **f_kwargs)
     s['count']+=1
     if s['count']>=n_cold and (e>0):
-        s_hodl = s['hodl_state']
-        w = _buy_and_hold_port(port=port, y=y, j=j, s=s_hodl, cov=x_cov, port_kwargs=port_kwargs)
+        s_account = s['account_state']
+        w, s_account = _buy_and_hold_port(port=port, y=y, j=j, s=s_account, cov=x_cov, port_kwargs=port_kwargs)
+        s['account_state'] = s_account
         if zeta is not None and (zeta>0):
             x_diag = np.diag(x_cov)
             x_corr = cov_to_corrcoef(x_cov)

precise/skaters/managers/equalmanagers.py

@@ -5,41 +5,35 @@
 from precise.skaters.managers.buyandholdfactory import buy_and_hold_manager_factory
 
 
-def equal_long_manager(y, s, k=1, e=1, zeta=None):
+def equal_daily_long_manager(y, s, k=1, e=1, zeta=None, j=None):
+    """ Trivial version ignored j argument """
     n_dim = len(y)
     w = np.ones(n_dim) / n_dim
     return w, {}
 
 
-def equal_long_manager_j5(y, s, k=1, e=1, zeta=None):
-    """ Rebalance every 5 observations """
-    return static_cov_manager_factory_d0(y=y, s=s, f=identity_scov, port=equal_long_port, e=e, n_cold=0, zeta=zeta, j=5)
+def equal_long_manager(y, s, k=1, e=1, zeta=None, j=1):
+    """ Rebalance every j observations """
+    return static_cov_manager_factory_d0(y=y, s=s, f=identity_scov, port=equal_long_port, e=e, n_cold=0, zeta=zeta, j=j)
 
 
-def equal_long_manager_j5_verify(y, s, k=1, e=1, zeta=None):
-    """ Rebalance every 5 observations, implemented a different way as a check """
-    return buy_and_hold_manager_factory(mgr=equal_long_manager, j=5, y=y, s=s)
+def equal_weekly_long_manager(y, s, k=1, e=1, zeta=None, j=None):
+    """ Rebalance every 5 observations, ignoring supplied j """
+    return static_cov_manager_factory_d0(y=y, s=s, f=identity_scov, port=equal_long_port, e=e, n_cold=0, zeta=zeta, j=5)
 
 
-def equal_long_manager_j10(y, s, k=1, e=1, zeta=None):
-    """ Rebalance every 5 observations """
-    return static_cov_manager_factory_d0(y=y, s=s, f=identity_scov, port=equal_long_port, e=e, n_cold=0, zeta=zeta,
-                                         j=10)
+def equal_weekly_buy_and_hold_long_manager(y, s, k=1, e=1, zeta=None, j=None):
+    """ Rebalance every 5 observations, implemented a different way as a check for tests """
+    return buy_and_hold_manager_factory(mgr=equal_daily_long_manager, j=5, y=y, s=s)
 
 
-def equal_long_manager_j20(y, s, k=1, e=1, zeta=None):
-    """ Rebalance every 5 observations """
-    return static_cov_manager_factory_d0(y=y, s=s, f=identity_scov, port=equal_long_port, e=e, n_cold=0, zeta=zeta,
-                                         j=20)
+def equal_monthly_long_manager(y, s, k=1, e=1, zeta=None, j=None):
+    """ Rebalance every 20 observations, ignoring supplied j """
+    return static_cov_manager_factory_d0(y=y, s=s, f=identity_scov, port=equal_long_port, e=e, n_cold=0, zeta=zeta, j=20)
 
 
-def equal_long_manager_j60(y, s, k=1, e=1, zeta=None):
-    """ Rebalance every 5 observations """
-    return static_cov_manager_factory_d0(y=y, s=s, f=identity_scov, port=equal_long_port, e=e, n_cold=0, zeta=zeta,
-                                         j=60)
 
 
-EQUAL_LONG_MANAGERS = [equal_long_manager, equal_long_manager_j5, equal_long_manager_j5_verify, equal_long_manager_j10,
-                       equal_long_manager_j20, equal_long_manager_j60]
+EQUAL_LONG_MANAGERS = [equal_long_manager, equal_daily_long_manager, equal_weekly_long_manager, equal_monthly_long_manager]
 EQUAL_LS_MANAGERS = []
 EQUAL_MANAGERS = EQUAL_LONG_MANAGERS + EQUAL_LS_MANAGERS

precise/skaters/managers/hrpmanagers.py

@@ -3,27 +3,27 @@
 
 
 # Some additional Hierarchical Risk-Parity managers that seem to do okay
-# (i.e. Schur managers with gamma=delta=0)
+# (i.e. Schur managers with gamma=delta=0,j=j)
 
 
-def hrp_weak_weak_pm_t0_d0_r025_n50_s5_long_manager(y, s, k=1, e=1):
+def hrp_weak_weak_pm_t0_d0_r025_n50_s5_long_manager(y, s, k=1, e=1,j=1):
     assert k==1
-    return schur_weak_weak_pm_manager_factory(y=y, s=s, target=0, r=0.025, n_emp=50, n_split=5, e=e, gamma=0, delta=0)
+    return schur_weak_weak_pm_manager_factory(y=y, s=s, target=0, r=0.025, n_emp=50, n_split=5, e=e, gamma=0, delta=0,j=j)
 
 
-def hrp_vol_vol_pm_t0_d0_r025_n50_s5_long_manager(y, s, k=1, e=1):
+def hrp_vol_vol_pm_t0_d0_r025_n50_s5_long_manager(y, s, k=1, e=1,j=1):
     assert k==1
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=50, n_split=5, e=e, gamma=0, delta=0)
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=50, n_split=5, e=e, gamma=0, delta=0,j=j)
 
 
-def hrp_vol_vol_pm_t0_d0_r025_n50_s50_long_manager(y, s, k=1, e=1):
+def hrp_vol_vol_pm_t0_d0_r025_n50_s50_long_manager(y, s, k=1, e=1,j=1):
     assert k==1
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=50, n_split=50, e=e, gamma=0, delta=0)
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=50, n_split=50, e=e, gamma=0, delta=0,j=j)
 
 
-def hrp_weak_vol_ewa_r025_n50_s50_long_manager(y, s, k=1, e=1):
+def hrp_weak_vol_ewa_r025_n50_s50_long_manager(y, s, k=1, e=1,j=1):
     assert k==1
-    return schur_weak_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=50, n_split=50, e=e, gamma=0, delta=0)
+    return schur_weak_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=50, n_split=50, e=e, gamma=0, delta=0,j=j)
 
 
 

precise/skaters/managers/ldpmanagers.py

@@ -8,20 +8,20 @@
 # (Note that seriation may be different so this is not supposed to be a replica)
 
 
-def ldp_s5_n50_long_manager(y, s, k=1, e=1):
-    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=50, e=e, gamma=0, delta=0)
+def ldp_s5_n50_long_manager(y, s, k=1, e=1,j=1):
+    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=50, e=e, gamma=0, delta=0,j=j)
 
 
-def ldp_s25_n50_long_manager(y, s, k=1, e=1):
-    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=50, e=e, gamma=0, delta=0)
+def ldp_s25_n50_long_manager(y, s, k=1, e=1,j=1):
+    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=50, e=e, gamma=0, delta=0,j=j)
 
 
-def ldp_s5_n100_long_manager(y, s, k=1, e=1):
-    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=100, e=e, gamma=0, delta=0)
+def ldp_s5_n100_long_manager(y, s, k=1, e=1,j=1):
+    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=100, e=e, gamma=0, delta=0,j=j)
 
 
-def ldp_s25_n100_long_manager(y, s, k=1, e=1):
-    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=100, e=e, gamma=0, delta=0)
+def ldp_s25_n100_long_manager(y, s, k=1, e=1,j=1):
+    return schur_diag_diag_buf_emp_manager_factory(y=y, s=s, n_buffer=100, e=e, gamma=0, delta=0,j=j)
 
 
 

precise/skaters/managers/molybogamanagers.py

@@ -6,28 +6,28 @@
 # https://jfds.pm-research.com/content/early/2020/07/03/jfds.2020.1.038
 
 
-def molyboga_r025_n50_long_manager(y, s, k=1, e=1):
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=40, e=e, gamma=0, delta=0)
+def molyboga_r025_n50_long_manager(y, s, k=1, e=1,j=1):
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=40, e=e, gamma=0, delta=0,j=j)
 
 
-def molyboga_r001_n100_long_manger(y, s, k=1, e=1):
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.01, n_emp=100, e=e, gamma=0, delta=0)
+def molyboga_r001_n100_long_manger(y, s, k=1, e=1,j=1):
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.01, n_emp=100, e=e, gamma=0, delta=0,j=j)
 
 
-def molyboga_r025_n50_s25_long_manager(y, s=25, k=1, e=1):
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=40, e=e, gamma=0, delta=0)
+def molyboga_r025_n50_s25_long_manager(y, s=25, k=1, e=1,j=1):
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=40, e=e, gamma=0, delta=0,j=j)
 
 
-def molyboga_r001_n100_s25_long_manger(y, s=25, k=1, e=1):
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.01, n_emp=100, e=e, gamma=0, delta=0)
+def molyboga_r001_n100_s25_long_manger(y, s=25, k=1, e=1,j=1):
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.01, n_emp=100, e=e, gamma=0, delta=0,j=j)
 
 
-def molyboga_r025_n50_s100_long_manager(y, s=100, k=1, e=1):
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=40, e=e, gamma=0, delta=0)
+def molyboga_r025_n50_s100_long_manager(y, s=100, k=1, e=1,j=1):
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.025, n_emp=40, e=e, gamma=0, delta=0,j=j)
 
 
-def molyboga_r001_n100_s100_long_manger(y, s=100, k=1, e=1):
-    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.01, n_emp=100, e=e, gamma=0, delta=0)
+def molyboga_r001_n100_s100_long_manger(y, s=100, k=1, e=1,j=1):
+    return schur_vol_vol_ewa_manager_factory(y=y, s=s, r=0.01, n_emp=100, e=e, gamma=0, delta=0,j=j)
 
 
 MOLYBOGA_LONG_MANAGERS = [molyboga_r025_n50_long_manager,

precise/skaters/managers/ppomanagerfactory.py

@@ -5,25 +5,25 @@
 from functools import partial
 
 
-def ppo_long_manager_factory(y,s, f, method, e=1, zeta=0):
+def ppo_long_manager_factory(y,s, f, method, e=1, zeta=0,j=1):
     port = partial(ppo_portfolio_factory, method=method, as_dense=True, weight_bounds=PPO_LONG_BOUNDS)
-    return static_cov_manager_factory_d0(f=f, port=port, y=y, s=s, e=e, zeta=zeta)
+    return static_cov_manager_factory_d0(f=f, port=port, y=y, s=s, e=e, zeta=zeta,j=j)
 
 
-def ppo_pm_long_manager_factory(y, s, method, target, n_emp, r, e=1, zeta=0):
+def ppo_pm_long_manager_factory(y, s, method, target, n_emp, r, e=1, zeta=0,j=1):
     """
        PyPortfolioOpt portfolio construction using partial moments cov estimation
     """
     f = partial( ewa_pm_factory, k=1,r=r,target=target, n_emp=n_emp )
     port = partial( ppo_portfolio_factory, method=method, as_dense=True, weight_bounds=PPO_LONG_BOUNDS )
-    return static_cov_manager_factory_d0(f=f, port=port, y=y, s=s, e=e, zeta=zeta)
+    return static_cov_manager_factory_d0(f=f, port=port, y=y, s=s, e=e, zeta=zeta,j=j)
 
 
-def ppo_ewa_long_manager_factory(y, s, method, n_emp, r, e=1, zeta=0):
+def ppo_ewa_long_manager_factory(y, s, method, n_emp, r, e=1, zeta=0,j=1):
     """
        PyPortfolioOpt portfolio construction using EWA cov estimation
     """
     f = partial( ewa_emp_pcov_factory, k=1, r=r, n_emp=n_emp )
     port = partial( ppo_portfolio_factory, method=method, as_dense=True, weight_bounds=PPO_LONG_BOUNDS )
-    return static_cov_manager_factory_d0(f=f, port=port, y=y, s=s, e=e, zeta=zeta)
+    return static_cov_manager_factory_d0(f=f, port=port, y=y, s=s, e=e, zeta=zeta,j=j)