# How to deal with missing returns when creating value (equal) weighted returns

recently I am doing cross sectional regressions, and getting confused about missing returns.

Suppose we have 100 stocks, then we want to construct a value weighted return (or equal weighted return). But the point is that the weights should be created in t-1 since we shouldn't use information which are not revealed to investors. But firm "A Corp" may have missing return for period t, then it has return record afterwards. Do we simply drop the return of "A Corp" for period t then rebalance our weights for the rest 99 firms? If we do rebalance the weights, it simply implies that investors are using the fact "A Corp" will have missing returns, which should not be revealed to the investors in t-1. If we do not rebalance the weights, then it is equivalent to impose that we have zero return for "A Corp".

How do guys you deal with missing returns in this case? Many thanks!!

The simple answer is that when you calculate the value weighted return at time $t$ all you really need is the return during time $t$ and the market-capitalization weight as of $t-1$. You can filter the securities to remove the missing ones (and others that you may remove for other reasons, e.g. too small or price too low), calculate weights based on the filtered data, and then take the weighted average to get the value-weighted return.