We present an investment-based asset pricing model in which firms’ exposure to systematic risk is uncertain. Beliefs about this parameter are updated from collective observations of firms’ peers, causing an endogenous shift in the discount rate, so firms’ real decisions and the market valuation should respond accordingly. We empirically show that the mean of beliefs about the risk exposure, formed through this collective learning, negatively predicts investment-capital ratio and market-to-book ratio and positively predicts the implied cost of capital. Besides, the precision of the parameter beliefs lowers the cost of capital and, in turn, raises the capital investment, consistent with the model prediction. In contrast, an alternative risk-estimate from firms’ individual history is only insignificantly connected to the observables, revealing the collective nature of the learning. 

JEL Codes: E2, E3, G12
Keywords: Parameter uncertainty, Collective learning, Systematic risk, Implied cost of capital​