Using Future Fundamentals to Study Stock Return Predictability

Summary

This document asks how much future company information, especially accounting results and profits, could explain subsequent stock returns if it were known in advance. It contrasts that hypothetical question with conventional factor research, which uses information available when a forecast is made. The proposed thought experiment is to measure how much return variation future fundamentals would account for, then consider how an investor might turn that knowledge into valuations or position sizes.

The discussion also raises links to information asymmetry, insider information, information leakage, earnings surprises relative to consensus, and the value of investment research. It does not provide a study, estimate, or tested trading method; it is an open-ended research question. Any practical interpretation would depend on which future data were known, when markets incorporated it, and how trades were sized. The document explicitly sets aside look-ahead bias as a concern for its hypothetical framing.

Key ideas

• Future accounting information could be studied for its explanatory power over subsequent stock returns.
• A hypothetical foresight exercise can ask what share of return variation future fundamentals explain.
• Knowing future information raises a separate question about how to value securities and size trades.
• The topic connects to information asymmetry, insider information, leakage, consensus surprises, and research value.

Tags

# Regarding the post-facto predictability of stock market returns


# Regarding the post-facto predictability of stock market returns












Almost all of the research on equity factor investing deals with a priori predictability of the cross-section of stock market returns (i.e., models which use variables and data that would've have been available at the time of the prediction). I am curious if there's any research that deals with the a posteriori predictability. If you're unaware of research, then how would you approach this as a thought experiment.

For example, how much do firms' future profits determine future stocks prices? In other words, if I had a hypothetical crystal ball which showed me only future accounting statements, and nothing else, what would my edge be (i.e., what proportion of the variance of future returns would this data explain)?

Moreover, how could one begin to optimally use this information? Obviously, a private wire to the future should convey an insurmountable edge, but what should the edge player do with this information? E.g., should he simply discount future earnings or do something more sophisticated, as in translate his edge into Kelly optimal bets?

I am not concerned about the perils of look-ahead bias. Rather, I am interested in the types of data that might be worthwhile to predict and how this might relate back to insider information asymmetry, information leakage, surprises versus the consensus, and the value of investment research. Also, types of foresight need not be constrained to accounting items (except, obviously, future price/returns).

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