[We develop a model for markets for catastrophic risk. The model explains why insurance providers may choose not to offer insurance for catastrophic risks and not to participate in reinsurance markets, even though there is a large enough market capacity to reach full risk sharing through diversification in a reinsurance market. This is a "nondiversification trap." We show that nondiversification traps may arise when risk distributions have heavy left tails and insurance providers have limited liability. When they are present, there may be a coordination role for a centralized agency to ensure that risk sharing takes place.]

[We show that several well-known asset pricing puzzles are largely mitigated if we endow the representative agent with an arbitrarily small minimum consumption level. This allows us to solve the model for parameter values where the standard "Lucas tree" model is not defined. For these parameters, disasters become more important, and the market risk premium therefore higher, even though consumption is less risky. Our model yields reasonable risk premia, Sharpe ratios, and discount rates; excess price volatility; and a high market price-dividend ratio. We derive closed-form solutions for all variables of interest.]

We study consumption, savings, and asset prices in economies with disagreement and production, focusing on settings with real effects of disagreement. Aggregate savings may be significantly distorted under disagreement, possibly related to the undersaving puzzle. In the production economy, mispricing mainly manifests itself in idiosyncratic risk, in contrast to the exchange economy, where the risk-free rate and expected return on the market may be distorted. Potential policy implications include the introduction of investment taxes or subsidies. Our results highlight the real effects of disagreement in financial markets, and the differences between economies with and without production.

We develop a theoretical model of a network of intermediaries whose optimal behavior is jointly determined, leading to heterogeneous financial norms and systemic vulnerabilities. We apply the model to the network of U.S. mortgage intermediaries from 2005 to 2007, using a data set containing all private-label, fixed-rate mortgages, with loan flows defining links. Default risk was closely related to network position, evolving predictably among linked nodes, and loan quality estimated from the model was related to independent quality measures, altogether pointing to the vital importance of network effects in this market. Received April 20, 2016; editorial decision July 11, 2017 by Editor Stijn Van Nieuwerburgh.

We study the trading behavior of investors in an entire stock market. Using an account level dataset of all trades on the Istanbul Stock Exchange in 2005, we identify investors with similar trading behavior as linked in an empirical investor network (EIN). Consistent with the theory of information networks, we find that central investors earn higher returns and trade earlier than peripheral investors with respect to information events. Overall, our results support the view that information diffusion among the investor population influences trading behavior and returns.

We develop a model for markets for catastrophic risk. The model explains why insurance providers may choose not to offer insurance for catastrophic risks and not to participate in reinsurance markets, even though there is a large enough market capacity to reach full risk sharing through diversification in a reinsurance market. This is a “nondiversification trap.” We show that nondiversification traps may arise when risk distributions have heavy left tails and insurance providers have limited liability. When they are present, there may be a coordination role for a centralized agency to ensure that risk sharing takes place.

We show that several well-known asset pricing puzzles are largely mitigated if we endow the representative agent with an arbitrarily small minimum consumption level. This allows us to solve the model for parameter values where the standard “Lucas tree” model is not defined. For these parameters, disasters become more important, and the market risk premium therefore higher, even though consumption is less risky. Our model yields reasonable risk premia, Sharpe ratios, and discount rates; excess price volatility; and a high market price-dividend ratio. We derive closed-form solutions for all variables of interest.

We study the trading behavior of investors in an entire stock market. Using an account level dataset of all trades on the Istanbul Stock Exchange in 2005, we identify investors with similar trading behavior as linked in an empirical investor network (EIN). Consistent with the theory of information networks, we find that central investors earn higher returns and trade earlier than peripheral investors with respect to information events. Overall, our results support the view that information diffusion among the investor population influences trading behavior and returns.