The 1987 market crash was associated with a dramatic and permanent steepening of the implied volatility curve for equity index options, despite minimal changes in aggregate consumption. We explain these events within a general equilibrium framework in which expected endowment growth and economic uncertainty are subject to rare jumps. The arrival of a jump triggers the updating of agents' beliefs about the likelihood of future jumps, which produces a market crash and a permanent shift in option prices. Consumption and dividends remain smooth, and the model is consistent with salient features of individual stock options, equity returns, and interest rates.

Recent evidence suggests that younger people update beliefs in response to aggregate shocks more than older people. We embed this generational learning bias in an equilibrium model in which agents have recursive preferences and are uncertain about exogenous aggregate dynamics. The departure from rational expectations is statistically modest, but generates high average risk premiums varying at generational frequencies, a positive relation between past returns and agents' future return forecasts, and substantial and persistent over-and undervaluation. Consistent with the model, the price-dividend ratio is empirically more sensitive to macroeconomic shocks when the fraction of young in the population is higher.

[Structural models of default calibrated to historical default rates, recovery rates, and Sharpe ratios typically generate Baa-Aaa credit spreads that are significantly below historical values. However, this "credit spread puzzle" can be resolved if one accounts for the fact that default rates and Sharpe ratios strongly covary; both are high during recessions and low during booms. As a specific example, we investigate credit spread implications of the Campbell and Cochrane (1999) pricing kernel calibrated to equity returns and aggregate consumption data. Identifying the historical surplus consumption ratio from aggregate consumption data, we find that the implied level and time variation of spreads match historical levels well.]

Parameter learning strongly amplifies the impact of macroeconomic shocks on marginal utility when the representative agent has a preference for early resolution of uncertainty. This occurs as rational belief updating generates subjective long-run consumption risks. We consider general equilibrium models with unknown parameters governing either long-run economic growth, rare events, or model selection. Overall, parameter learning generates long-lasting, quantitatively significant additional macroeconomic risks that help explain standard asset pricing puzzles.

We extend Kyle's (1985) model of insider trading to the case where noise trading volatility follows a general stochastic process. We determine conditions under which, in equilibrium, price impact and price volatility are both stochastic, driven by shocks to uninformed volume even though the fundamental value is constant. The volatility of price volatility appears 'excessive' because insiders choose to trade more aggressively (and thus more information is revealed) when uninformed volume is higher and price impact is lower. This generates a positive relation between price volatility and trading volume, giving rise to an endogenous subordinate stochastic process for prices.

Reduced-form models of default that attribute a large fraction of credit spreads to compensation for credit-event risk typically preclude the most plausible economic justification for such risk to be priced, namely, a contemporaneous drop in the market portfolio. When this "contagion" channel is introduced within a general equilibrium framework for an economy comprising a large number of firms, credit-event risk premia have an upper bound of a few basis points, and are dwarfed by the contagion premium. We provide empirical evidence that indicates credit-event risk premia are less than 1 bp, but contagion risk premia are significant.

We propose an equilibrium model for defaultable bonds that are subject to contagion risk. Contagion arises because agents with "fragile beliefs" are uncertain about the underlying economic state and its probability. Estimation on sovereign European credit default swaps (CDS) data shows that agents require a time-varying risk premium for bearing state uncertainty. The model outperforms affine specifications with the same number of state variables, suggesting that there are important nonlinearities in credit spreads that are captured by our model. Contagion drives most of the variation in CDS spreads, especially before the crisis. However, economic fundamentals account for a significant fraction during the crisis.

We solve a portfolio choice problem when expected returns, covariances, and trading costs follow a regime-switching model. The optimal policy trades towards an aim portfolio given by a weighted-average of the conditional mean-variance-efficient portfolios in all future states. The trading speed is higher in more persistent, riskier, and higher-liquidity states. It can be optimal to overweight low Sharpe-ratio assets such as Treasury bonds because they remain liquid even in crisis states. We illustrate our methodology by constructing an optimal US equity market timing portfolio based on an estimated regime-switching model and on trading costs estimated using a large-order institutional trading data set.

Most term structure models assume bond markets are complete, that is, that all fixed income derivatives can be perfectly replicated using solely bonds. How ever, we find that, in practice, swap rates have limited explanatory power for returns on at‐the‐money straddles—portfolios mainly exposed to volatility risk. We term this empirical feature unspanned stochastic volatility (USV). While USV can be captured within an HJM framework, we demonstrate that bivariate models cannot exhibit USV. We determine necessary and sufficient conditions for trivariate Markov affine systems to exhibit USV. For such USV models, bonds alone may not be sufficient to identify all parameters. Rather, derivatives are needed.

Most structural models of default preclude the firm from altering its capital structure. In practice, firms adjust outstanding debt levels in response to changes in firm value, thus generating mean‐reverting leverage ratios. We propose a structural model of default with stochastic interest rates that captures this mean reversion. Our model generates credit spreads that are larger for low‐leverage firms, and less sensitive to changes in firm value, both of which are more consistent with empirical findings than predictions of extant models. Further, the term structure of credit spreads can be upward sloping for speculative‐grade debt, consistent with recent empirical findings.