Handling Missing Stock Returns in Value-Weighted Portfolios
Summary
The document discusses how to calculate portfolio returns when some constituent stocks have missing monthly returns, using a value-weighted portfolio as its example. It contrasts treating a missing return as zero with calculating the portfolio return from the available stocks, and points to Fama and French’s portfolio construction as context. Their cited procedure averages the non-missing stock returns for a portfolio during the month, which effectively assigns missing stocks the average return of the observed stocks.
The response cautions that this treatment may be tolerable in a broad portfolio but can make results unreliable when only a few stocks represent it. It recommends checking how many securities contribute to each portfolio. The method also has an important caveat: a missing observation may reflect bankruptcy or another event that makes average-return imputation inappropriate. The document gives no detailed rule for value-weighted missing-data calculations, so its equal-weighted example should not be assumed to resolve the original weighting question.
Key ideas
- A missing stock return should not automatically be treated as zero.
- The cited Fama and French procedure averages the non-missing stock returns for each portfolio period.
- This effectively imputes a missing return using the average return of observed stocks.
- Results are especially sensitive to missing observations when a portfolio contains very few stocks.
- Average-return imputation may be unsuitable when missingness reflects bankruptcy.
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Full text
# Creating value weighted portfolio returns. How to handle missing data? # Creating value weighted portfolio returns. How to handle missing data? I am creating portfolios using stock data. I have some missing data for certain months. What is the best way to handle this? Should I treat missing months as a return of zero? I want to try and replicate Kenneth Frenches data, so if anyone had any insight into how that it dealt with in creating his portfolios would be useful. To give an example, WSay I've got two stocks, A and B, both starting with a weight of 50%, in month 1, the return of A is 10% and the Return of B is -10%, in the next month the weights 55% and 45% for A and B respectively, however, the return of A is 10% and the return of B is missing. So in month two will, I display the return of my portfolio as 10% or 5.5%, or something else? ## Answer by Tim Wilding (score 1, accepted) https://quant.stackexchange.com/a/42397 Fama and French (1992) state that they "calculate each portfolio's monthly equal-weighted return for July of year $t$ to June of year $t+1$" (see, e.g. Table IV). In that case, it would appear that the results should be fairly insensitive to missing returns, since one would just calculate the average of all of the non-missing stocks. I would say that your hypothetical scenario of just two stocks in the portfolio is slightly misleading because the portfolio returns would be highly dependent on a single missing stock. Fama and French are looking for systematic factors, and using 1 or 2 stocks to represent a systematic factor would not seem to be very sensible. Given that, I would test to see whether there are more than a handful of stocks in any particular portfolio. This approach effectively substitutes the missing return with the average return of all the other stocks for the period. This may be a bad assumption if a security has gone bankrupt, but is probably pretty reasonable otherwise. There is an extended discussion of how to deal with missing returns at How to deal with missing returns when creating value (equal) weighted returns
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