We show that corporate investment decisions can explain the conditional dynamics in expected asset returns. Our approach is similar in spirit to Berk, Green, and Naik (1999), but we introduce to the investment problem operating leverage, reversible real options, fixed adjustment costs, and finite growth opportunities. Asset betas vary over time with historical investment decisions and the current product market demand. Book-to-market effects emerge and relate to operating leverage, while size captures the residual importance of growth options relative to assets in place. We estimate and test the model using simulation methods and reproduce portfolio excess returns comparable to the data. CORPORATE INVESTMENT DECISIONS are often evaluated in a real options context, 1 and option exercise can change the riskiness of a firm in various ways. For example, if growth opportunities are finite, the decision to invest changes the ratio of growth options to assets in place. Additionally, the resulting increase in physical capital may generate operating leverage through long-term obligations, including the fixed operating costs of a larger plant, wage contracts, and commitments to suppliers. It is natural to conclude that expected returns might be related to current and historical investment decisions of the firm.The empirical literature has long recognized a need to account for the dynamic structure of risk when testing asset pricing models. 2 A small but growing literature that endogenizes expected returns through firm-level

We present a rational theory of SEOs that explains a pre-issuance price run-up, a negative announcement effect, and long-run post-issuance underperformance. When SEOs finance investment in a real options framework, expected returns decrease endogenously because growth options are converted into assets in place. Regardless of their risk, the new assets are less risky than the options they replace. Although both size and book-to-market effects are present, standard matching procedures fail to fully capture the dynamics of risk and expected return. We calibrate the model and show that it closely matches the primary features of SEO return dynamics. Copyright 2006 by The American Finance Association.

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. AbstractWe study own and rival risk in a dynamic duopoly with a homogeneous output good. A competitor's options to adjust capacity reduce own-firm risk through a simple hedging channel. For example, if a rival possesses a growth option, an increase in industry demand directly enhances current profits but also encourages value-reducing competitor expansion. As a consequence, when a leader and a follower emerge in equilibrium, risk dynamics depart substantially from previouslystudied simultaneous move benchmarks. Own-firm and competitor required returns tend to move together through contractions and oppositely during expansions, providing testable new empirical predictions. AbstractWe study own and rival risk in a dynamic duopoly with a homogeneous output good. A competitor's options to adjust capacity reduce own-firm risk through a simple hedging channel. For example, if a rival possesses a growth option, an increase in industry demand directly enhances current profits but also encourages value-reducing competitor expansion. As a consequence, when a leader and a follower emerge in equilibrium, risk dynamics depart substantially from previously-studied simultaneous move benchmarks. Own-firm and competitor required returns tend to move together through contractions and oppositely during expansions, providing testable new empirical predictions.JEL Classification: C23, C35.