diff --git a/backtester/backtester.py b/backtester/backtester.py
index 2eaf95d..e87cccd 100644
--- a/backtester/backtester.py
+++ b/backtester/backtester.py
@@ -113,7 +113,8 @@ class Backtest:
         """
 
         leg_candidates = [
-            self._strategy._exit_candidates(l.direction, self.inventory[l.name], options) for l in self._strategy.legs
+            self._strategy._exit_candidates(l.direction, self.inventory[l.name], options, self.inventory.index)
+            for l in self._strategy.legs
         ]
 
         # If a contract is missing we replace the NaN values with those of the inventory
diff --git a/backtester/strategy/strategy.py b/backtester/strategy/strategy.py
index 522657d..4808ab2 100644
--- a/backtester/strategy/strategy.py
+++ b/backtester/strategy/strategy.py
@@ -101,16 +101,18 @@ class Strategy:
             pd.DataFrame:               Exit signals
         """
 
-        leg_candidates = [self._exit_candidates(l.direction, inventory[l.name], options) for l in self.legs]
+        leg_candidates = [
+            self._exit_candidates(l.direction, inventory[l.name], options, inventory.index) for l in self.legs
+        ]
 
-        filter_mask = []
+        filter_masks = []
         for i, leg in enumerate(self.legs):
             flt = leg.exit_filter
 
             # This mask is to ensure that legs with missing contracts exit.
             missing_contracts_mask = leg_candidates[i]['cost'].isna()
 
-            filter_mask.append(flt(leg_candidates[i]) | missing_contracts_mask)
+            filter_masks.append(flt(leg_candidates[i]) | missing_contracts_mask)
             fields = self._signal_fields((~leg.direction).value)
             leg_candidates[i] = leg_candidates[i].loc[:, fields.values()]
             leg_candidates[i].columns = pd.MultiIndex.from_product([["leg_{}".format(i + 1)],
@@ -133,7 +135,7 @@ class Strategy:
 
         # Compute which contracts need to exit, either because of price thresholds or user exit filters
         threshold_exits = self._filter_thresholds(inventory['totals']['cost'], total_costs)
-        filter_mask = reduce(lambda x, y: x | y, filter_mask)
+        filter_mask = reduce(lambda x, y: x | y, filter_masks)
         exits_mask = threshold_exits | filter_mask
 
         exits = candidates[exits_mask]
@@ -226,7 +228,7 @@ class Strategy:
 
         return pd.concat(dfs, axis=1)
 
-    def _exit_candidates(self, direction, inventory_leg, options):
+    def _exit_candidates(self, direction, inventory_leg, options, inventory_index):
         """Returns the exit candidates for the given inventory leg with their order and cost (positive for STC orders).
 
         Args:
@@ -244,6 +246,9 @@ class Strategy:
         fields = self._signal_fields((~direction).value)
         options = options.rename(columns=fields)
         candidates = inventory_leg[['contract']].merge(options, how='left', on='contract')
+        # candidates.index needs to be the same as the inventory's so that the exit masks that are constructed
+        # from it can be correctly applied to the inventory.
+        candidates.index = inventory_index
 
         order = get_order(direction, Signal.EXIT)
         candidates['order'] = order