fix: _min_ratio_asset was fixed in multi_period.py

Author: DNTNTRSRNM

okama/frontier/multi_period.py

@@ -486,12 +486,12 @@ def minimize_risk(self, target_value: float) -> Dict[str, float]:
         n = self.assets_ror.shape[1]  # number of assets
         init_guess = np.repeat(1/n, n)  # initial weights
 
-        min_ratio_data = self._best_ratio_asset
+        min_ratio_data = self._min_ratio_asset
         max_ratio_data = self._max_ratio_asset_right_to_max_cagr
 
         if min_ratio_data is not None and max_ratio_data is not None:
             init_guess = np.repeat(0, n) # clear weights
-            init_guess[self._best_ratio_asset["list_position"]] = 1.0
+            init_guess[self._min_ratio_asset["list_position"]] = 1.0
 
         def objective_function(w):
             # annual risk
@@ -600,7 +600,7 @@ def _max_cagr_asset(self) -> dict:
         }
 
     @property
-    def _best_ratio_asset(self) -> Optional[dict]:
+    def _min_ratio_asset(self) -> Optional[dict]:
         """
         The asset with the minimum ratio between the CAGR 
         (Compound Annual Growth Rate) and the risk for assets that are "to the left" 
@@ -610,39 +610,36 @@ def _best_ratio_asset(self) -> Optional[dict]:
         risk_monthly = self.assets_ror.std()
         mean_return = self.assets_ror.mean()
         risk = helpers.Float.annualize_risk(risk_monthly, mean_return)
-        tolerance = 0.01
 
         global_max_cagr = self.global_max_return_portfolio["CAGR"]
         global_max_risk = self.global_max_return_portfolio["Risk"]
-        
-        global_max_cagr_is_not_asset = (cagr < global_max_cagr * (1 - tolerance)).all()
-        if global_max_cagr_is_not_asset:
-            cagr_diff = global_max_cagr - cagr
-            risk_diff = global_max_risk - risk   
+
+        cagr_diff = global_max_cagr - cagr
+        risk_diff = global_max_risk - risk   
 
-            if risk_diff is not None and (risk_diff == 0).any():  
-                risk_diff += 0.0001  # to avoid division by zero
+        if risk_diff is not None and (risk_diff == 0).any():  
+            risk_diff += 0.0001  # to avoid division by zero
 
-            ratio = cagr_diff / risk_diff
-            left_assets = risk_diff > 0  
+        ratio = cagr_diff / risk_diff
+        left_assets = risk_diff > 0  
 
-            if left_assets.any():
-                valid_ratios = ratio[left_assets]
-                min_ticker = valid_ratios.idxmin() 
-                return {
-                    "min_asset_cagr": cagr[min_ticker],
-                    "ticker_with_smallest_ratio": min_ticker,
-                    "list_position": self.assets_ror.columns.get_loc(min_ticker)
-                }
-            if not left_assets.any():
-                right_assets = risk_diff < 0
-                valid_ratios = ratio[right_assets]
-                min_ticker = valid_ratios.idxmin()
-                return {
-                    "min_asset_cagr": cagr[min_ticker],
-                    "ticker_with_smallest_ratio": min_ticker,
-                    "list_position": self.assets_ror.columns.get_loc(min_ticker)
-                }
+        if left_assets.any():
+            valid_ratios = ratio[left_assets]
+            min_ticker = valid_ratios.idxmin() 
+            return {
+                "min_asset_cagr": cagr[min_ticker],
+                "ticker_with_smallest_ratio": min_ticker,
+                "list_position": self.assets_ror.columns.get_loc(min_ticker)
+            }
+        if not left_assets.any():
+            right_assets = risk_diff < 0
+            valid_ratios = ratio[right_assets]
+            min_ticker = valid_ratios.idxmin()
+            return {
+                "min_asset_cagr": cagr[min_ticker],
+                "ticker_with_smallest_ratio": min_ticker,
+                "list_position": self.assets_ror.columns.get_loc(min_ticker)
+            }
         return None
 
 
@@ -701,7 +698,7 @@ def _target_cagr_range_left(self) -> np.ndarray:
         """
         Full range of CAGR values (from min to max).
         """
-        min_ratio_data = self._best_ratio_asset
+        min_ratio_data = self._min_ratio_asset
         max_ratio_data = self._max_ratio_asset_right_to_max_cagr
 
         if min_ratio_data is not None and max_ratio_data is not None: