Fix condition in volatility_preset function to correctly identify rows to drop based on median values. This change ensures accurate lineup adjustments by comparing current ownership type maximums with median values.

global_func/volatility_preset.py

@@ -16,7 +16,7 @@ def volatility_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols:
             curr_own_type_max = working_portfolio.loc[0, 'median'] + (slack_var / 20 * working_portfolio.loc[0, 'median'])
 
             for i in range(1, len(working_portfolio)):
-                if working_portfolio.loc[i, 'median'] < curr_own_type_max:
+                if working_portfolio.loc[i, 'median'] > curr_own_type_max:
                     rows_to_drop.append(i)
                 else:
                     curr_own_type_max = working_portfolio.loc[i, 'median'] + (slack_var / 20 * working_portfolio.loc[i, 'median'])