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Speculative Betas / Harrison Hong, David Sraer.

By: Contributor(s): Material type: TextTextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w18548.Publication details: Cambridge, Mass. National Bureau of Economic Research 2012.Description: 1 online resource: illustrations (black and white)Subject(s): Online resources: Available additional physical forms:
  • Hardcopy version available to institutional subscribers
Abstract: We provide a model for why high beta assets are more prone to speculative overpricing than low beta ones. When investors disagree about the common factor of cash-flows, high beta assets are more sensitive to this macro-disagreement and experience a greater divergence-of-opinion about their payoffs. Short-sales constraints for some investors such as retail mutual funds result in high beta assets being over-priced. When aggregate disagreement is low, expected return increases with beta due to risk-sharing. But when it is large, expected return initially increases but then decreases with beta. High beta assets have greater shorting from unconstrained arbitrageurs and more share turnover. Using measures of disagreement about stock earnings and economic uncertainty, we verify these predictions. A calibration exercise yields reasonable parameter values.
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November 2012.

We provide a model for why high beta assets are more prone to speculative overpricing than low beta ones. When investors disagree about the common factor of cash-flows, high beta assets are more sensitive to this macro-disagreement and experience a greater divergence-of-opinion about their payoffs. Short-sales constraints for some investors such as retail mutual funds result in high beta assets being over-priced. When aggregate disagreement is low, expected return increases with beta due to risk-sharing. But when it is large, expected return initially increases but then decreases with beta. High beta assets have greater shorting from unconstrained arbitrageurs and more share turnover. Using measures of disagreement about stock earnings and economic uncertainty, we verify these predictions. A calibration exercise yields reasonable parameter values.

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