We introduce limited liability in a model with a continuum of ex ante identical agents who face aggregate and idiosyncratic income risk. These agents can trade a complete menu of contingent claims, but they cannot commit and shares in a Lucas tree serve as collateral to back up their state-contingent promises. The limited liability option gives rise to a second risk factor, in addition to aggregate consumption growth risk. This liquidity risk is created by binding solvency constraints, and it is measured by the growth rate of one moment of the wealth distribution. The economy is said to experience a negative liquidity shock when this growth rate is high and a large fraction of agents faces severely binding solvency constraints. The adjustment to the Breeden-Lucas stochastic discount factor induces substantial time variation in equity risk premia that is consistent with the data at business cycle frequencies.

Our paper examines whether the well-documented failure of unsophisticated investors to rebalance their portfolios can help to explain the enormous counter-cyclical volatility of aggregate risk compensation in financial markets. To answer this question, we set up a model in which CRRA-utility investors have heterogeneous trading technologies. In our model, a large mass of investors do not re-balance their portfolio shares in response to aggregate shocks, while a smaller mass of active investors adjust their portfolio each period to respond to changes in the investment opportunity set. We find that these intermittent re-balancers amplify the effect of aggregate shocks on the time variation in risk premia by a factor of three by forcing active traders to sell more shares in good times and buy more shares in bad times. * We would like to thank

Our paper examines the impact of heterogeneous trading technologies for households on asset prices and the distribution of wealth. We distinguish between passive traders who hold fixed portfolios of stocks and bonds, and active traders who adjust their portfolios to changes in expected returns. To solve the model, we derive an optimal consumption sharing rule that does not depend on the trading technology, and we derive an aggregation result for state prices. This allows us to solve for equilibrium prices and allocations without having to search for market-clearing prices in each asset market separately. We show that the fraction of total wealth held by active traders, not the fraction held by all participants, is critical for asset prices, because only these traders respond to variation in state prices and hence absorb the residual aggregate risk created by non-participants. We calibrate the heterogeneity in trading technologies to match the equity premium and the risk-free rate. The calibrated model reproduces the skewness and kurtosis of the wealth distribution in the data. In contrast to existing models with heterogeneous agents, our model matches the high volatility of returns and the low volatility of the risk-free rate.

Our paper examines the impact of heterogeneous trading technologies for households on asset prices and the distribution of wealth. We distinguish between passive traders who hold fixed portfolios of stocks and bonds, and active traders who adjust their portfolios to changes in expected returns. To solve the model, we derive an optimal consumption sharing rule that does not depend on the trading technology, and we derive an aggregation result for state prices. This allows us to solve for equilibrium prices and allocations without having to search for market-clearing prices in each asset market separately. We show that the fraction of total wealth held by active traders, not the fraction held by all participants, is critical for asset prices, because only these traders respond to variation in state prices and hence absorb the residual aggregate risk created by non-participants. We calibrate the heterogeneity in trading technologies to match the equity premium and the risk-free rate. The calibrated model reproduces the skewness and kurtosis of the wealth distribution in the data. In contrast to existing models with heterogeneous agents, our model matches the high volatility of returns and the low volatility of the risk-free rate.

Our paper examines the impact of heterogeneous trading technologies for households on asset prices and the distribution of wealth. We distinguish between passive traders who hold fixed portfolios of stocks and bonds, and active traders who adjust their portfolios to changes in expected returns. To solve the model, we derive an optimal consumption sharing rule that does not depend on the trading technology, and we derive an aggregation result for state prices. This allows us to solve for equilibrium prices and allocations without having to search for market-clearing prices in each asset market separately. We show that the fraction of total wealth held by active traders, not the fraction held by all participants, is critical for asset prices, because only these traders respond to variation in state prices and hence absorb the residual aggregate risk created by non-participants. We calibrate the heterogeneity in trading technologies to match the equity premium and the risk-free rate. The calibrated model reproduces the skewness and kurtosis of the wealth distribution in the data. In contrast to existing models with heterogeneous agents, our model matches the high volatility of returns and the low volatility of the risk-free rate.