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As much as we’re awash in data, a huge problem for building predictive models is the information we don’t have.
A Better Way for Finance (and Others) to Handle Missing DataWhat Information Drives Asset Prices?
- By
- March 10, 2017
- CBR - Finance
Investors are inundated with news about business, politics, and the global economy—and use it to assess the health of the economy, set prices, and forecast returns. But in this flood of information, what in particular are investors paying attention to?
Carnegie Mellon’s Anisha Ghosh and Chicago Booth’s George M. Constantinides find empirical evidence that regardless of what information investors are considering, their focus manifests itself in price-level and labor-market variables.
The researchers start with the market price–dividend ratio, which is an important indicator of investors’ expectations about future dividend growth and discount rates. Many economists believe that the market price–dividend ratio is highly correlated with aggregate consumption growth, but Ghosh and Constantinides find otherwise—they see it as highly correlated with changes in price-level and labor-market variables.
Ghosh and Constantinides incorporate this observation in a model in which investors learn whether the economy is in recession, recovery, or expansion from changes in two prominent price-level and labor-market variables: the consumer-price index and average hourly earnings of production.
The empirical results highlight how much information these macroeconomic variables provide investors. The model explains the level and volatility of consumption and dividend growth, stock market returns, the price-dividend ratio, and the risk-free rate—and it performs well in predicting future returns, while a model with learning from consumption history does not. The findings suggest that changes in the variables the researchers identify have long-term economic implications.
Anisha Ghosh and George M. Constantinides, “What Information Drives Asset Prices?” Working paper, November 2016.
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