update comments

evo_researcher/benchmark/benchmark.py

@@ -313,10 +313,14 @@ def get_markets_summary(self) -> t.Dict[str, t.List[str | float]]:
         return markets_summary
 
     def calculate_expected_returns(self, prediction: Prediction, market: Market) -> float | None:
+        """
+        The expected value if betting on a binary market in its initialized state of 50:50 'yes' and 'no' shares, with the assumption that the correct `p_yes` is that of the market.
+        """
         if not prediction.is_answered:
             return None
 
-        # TODO: Add support for different bet sizes and calculate shares based on the market's odds.
+        # TODO: Add support for different bet sizes -- if we bet a low amount (such as <10 units), the real shares will be very close to that we calculate below (bet_units / share_price),
+        # but if one bets a lot, it will change the share price along the way, and so he/she receives less than `bet_units / share_price`, but it's more complicated to calculate.
         bet_units = 10  # Assuming the agent always bet 10 units per market.
         buy_yes_threshold = 0.5  # If the agent's prediction is > 50% it should buy "yes", otherwise "no".