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Market, Sector, and Index Returns as Controls in Weekly Stock Return Models

Article Quant Q&A · Author: Sunv
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Summary

The document discusses additional explanatory variables for a panel regression predicting weekly stock returns. The original specification includes investor attention, company size, and momentum measured over recent weeks. The answers suggest accounting for common return drivers by adding market or sector returns, and potentially their momentum. They also propose a stock’s beta, described as its volatility relative to the broad market, as a possible control.

A further suggestion is to include returns for ETFs or index funds that hold the stock, since fund performance may be related to the returns of constituent stocks. These proposals emphasize that individual share movements can reflect broad market, industry, and fund-level exposures. The responses are suggestions, not a tested specification: they provide no sample period, estimation method, factor construction, or evidence on incremental predictive power. A researcher would still need to align weekly measurement windows, address overlapping exposures and potential look-ahead, and evaluate the variables out of sample.

Key ideas

  • Weekly market and sector returns can control for broad forces affecting individual stocks.
  • Beta is proposed as a measure of a stock’s exposure relative to the overall market.
  • Market or sector momentum may add information beyond the corresponding return.
  • Returns of ETFs or index funds holding a stock may be relevant explanatory variables.
  • The suggestions are not empirically evaluated in the document.

Tags

EquitiesStatisticsMomentumUS markets
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# Explanatory variables for regression predicting weekly stock returns


# Explanatory variables for regression predicting weekly stock returns












In an empirical analysis I'm trying to predict log() weekly stock returns. I'm trying to model stock returns in a panel data model framework.

As explanatory variables I have 1) a measure of investor attention for each stock , 2) size, and 3) price momentum during the previous 4 and 8 weeks respectively.

I have access to the WRDS database, i.e. CRSP, Compustat, IBES etc.

Any suggestions as to other variables i can include in my empirical analysis? I would like suggested variables to have the same frequency, i.e. weekly observations.

## Answer by Shahar (score 1)

https://quant.stackexchange.com/a/14624

Very often a stock's return is determined primarily by what the broad market, or perhaps the stock's sector, is doing: to see this, take a random stock, and it will be very hard to justify most moves - until you consider the market [e.g. S&P500] or sector [e.g. transportation].

Thus, I would include the beta coefficient, which measures the volatility in comparison to the market as a whole. In addition, I would consider including the returns (and perhaps also momentum) of the market or relevant sector.

## Answer by g_puffo (score 1)

https://quant.stackexchange.com/a/14662

A stock's returns are also correlated to the performance of the ETFs or Index Funds that include that stock; for example, if you look at returns for MSFT (Microsoft), you might want to look at the performance of QQQ as well.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.