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Correlated Beliefs, Returns, and Stock Market Volatility

Joel David () and Ina Simonovska ()

No 21480, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Firm-level stock returns exhibit comovement above that in fundamentals, and the gap tends to be higher in developing countries. We investigate whether correlated beliefs among sophisticated, but imperfectly informed, traders can account for the patterns of return correlations across countries. We take a unique approach by turning to direct data on market participants’ information - namely, real-time firm-level earnings forecasts made by equity market analysts. The correlations of firm-level forecasts exceed those of fundamentals and are strongly related to return correlations across countries. A calibrated information-based model demonstrates that the correlation of beliefs implied by analyst forecasts leads to return correlations broadly in line with the data, both in levels and across countries - the correlation between predicted and actual is 0.63. Our findings have implications for market-wide volatility - the model-implied correlations alone can explain 44% of the cross-section of aggregate volatility. The results are robust to controlling for a number of alternative factors put forth by the existing literature.

JEL-codes: D8 G12 G15 G17 (search for similar items in EconPapers)
Date: 2015-08
New Economics Papers: this item is included in nep-fmk, nep-for and nep-ger
Note: AP CF EFG IFM
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Published as Joel M. David & Ina Simonovska, 2015. "Correlated beliefs, returns, and stock market volatility," Journal of International Economics, vol ().
Published as Correlated Beliefs, Returns, and Stock Market Volatility , Joel M. David, Ina Simonovska. in NBER International Seminar on Macroeconomics 2015 , Devereux, Giavazzi, and West. 2016

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Chapter: Correlated Beliefs, Returns, and Stock Market Volatility (2016)
Journal Article: Correlated beliefs, returns, and stock market volatility (2016) Downloads
Working Paper: Correlated Beliefs, Returns, and Stock Market Volatility (2016) Downloads
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