Enhance portfolio trimming logic in trim_portfolio.py by adding calculation for maximum ownership type value when conditions are not met. This adjustment improves the accuracy of the trimming process by ensuring all relevant ownership metrics are considered.

global_func/trim_portfolio.py

@@ -25,6 +25,8 @@ def trim_portfolio(portfolio: pd.DataFrame, trim_slack: float, performance_type:
             working_portfolio.loc[i, own_type] > own_threshold_low and \
             working_portfolio.loc[i, own_type] <= own_threshold_high:
                 rows_to_drop.append(i)
+            else:
+                curr_own_type_max = working_portfolio.loc[i, own_type] + (trim_slack * working_portfolio.loc[i, own_type])
             
     working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True)
     return working_portfolio