This article presents a dynamic, rational expectations equilibrium model of asset prices where the drift of fundamentals (dividends) shifts between two unobservable states at random times. I show that in equilibrium, investors' willingness to hedge against changes in their own "uncertainty" on the true state makes stock prices overreact to bad news in good times and underreact to good news in bad times. I then show that this model is better able than conventional models with no regime shifts to explain features of stock returns, including volatility clustering, "leverage effects," excess volatility, and time-varying expected returns.

Using a simple dynamic asset pricing model, this paper investigates the relationship between the precision of public information about economic growth and stock market returns. After fully characterizing expected returns and conditional volatility, I show that (i) higher precision of signals tends to increase the risk premium, (ii) when signals are imprecise the equity premium is bounded above independently of investors' risk aversion, (iii) return volatility is U‐shaped with respect to investors' risk aversion, and (iv) the relationship between conditional expected returns and conditional variance is ambiguous.

A frictionless general equilibrium model featuring heterogeneous time-varying risk tolerance explains the business cycle dynamics of intermediary leverage, aggregate credit, and other asset markets’ facts. In booms, when risk tolerance is high, households borrow more and aggregate credit increases funded by higher intermediary debt. In recessions, credit contracts and intermediaries delever. Yet, their debt-to-equity ratios increase as equity drops when risk aversion increases. Because households borrow more or less as their risk tolerance increases or decreases, the intermediary’s balance sheet forecasts stock returns both in the time series and the cross section. Moreover, credit expansions correlate with negatively skewed stock returns, low credit spreads, and predict lower future returns.

Non-linear external habit persistence models, which feature prominently in the recent “equity premium” asset pricing and macroeconomics literature, generate counterfactual predictions in the cross-section of stock returns. In particular, we show that in the absence of cross-sectional heterogeneity in firms’ cash-flow risk, these models produce a “growth premium,” that is, stocks with high price-to-fundamental ratios command a higher premium than stocks with low price-to-fundamental ratios. This implication is at odds with the well-established empirical observation of a “value premium” in the cross-section of stock returns. Substantial heterogeneity in firms’ cash-flow risk yields both a value premium as well as most of the stylized facts about the cross-section of stock returns, but it generates a “cash-flow risk puzzle”: Quantitatively, value stocks have to have “too much” cash-flow risk compared to the data to generate empirically plausible value premiums.

We propose a novel economic mechanism that generates stock return predictability in both the time series and the cross-section. Investors’ income has two sources, wages and dividends that grow stochastically over time. As a consequence the fraction of total income produced by wages fluctuates depending on economic conditions. We show that the risk premium that investors require to hold stocks varies with these fluctuations. A regression of stock returns on lagged values of the labor income to consumption ratio produces statistically significant coefficients and large adjusted R2s. Tests of the model’s cross-sectional predictions on the set of 25 Fama–French portfolios sorted on size and book-to-market are also met with considerable support.

We propose a general equilibrium model with multiple securities in which investors' risk preferences and expectations of dividend growth are time-varying. While time-varying risk preferences induce the standard positive relation between the dividend yield and expected returns, time-varying expected dividend growth induces a negative relation between them. These offsetting effects reduce the ability of the dividend yield to forecast returns and eliminate its ability to forecast dividend growth, as observed in the data. The model links the predictability of returns to that of dividend growth, suggesting specific changes to standard linear predictive regressions for both. The model's predictions are confirmed empirically.

Previous work on information and financial markets has focused on a special set of assumptions: agents have exponential utility, and random variables are normally distributed. These assumptions are often necessary to obtain closed-form solutions. We present an example with alternative assumptions, and demonstrate that some of the conclusions from previous literature fail to hold. In particular, we show that in our example, as more agents acquire information, prices do not necessarily become more informative, and agents may have greater incentive to acquire information. Learning can therefore be a strategic complement, allowing for the possibility of multiple equilibria.

We develop a general equilibrium model of government policy choice in which stock prices respond to political news. The model implies that political uncertainty commands a risk premium whose magnitude is larger in weaker economic conditions. Political uncertainty reduces the value of the implicit put protection that the government provides to the market. It also makes stocks more volatile and more correlated, especially when the economy is weak. We find empirical evidence consistent with these predictions.

We calculate the costs and benefits of the largest ever US government intervention in the financial sector announced during the 2008 Columbus-day weekend. We estimate that this intervention increased the value of banks’ financial claims by 130 billion (bn) at a taxpayers’ cost of 21–44 billion with a net benefit between 86 and $109bn. By looking at the limited cross section, we infer that this net benefit arises from a reduction in the probability of bankruptcy, which we estimate would destroy 22% of the enterprise value. The big winners of the plan were the bondholders of the three former investment banks and Citigroup, while the losers were JP Morgan shareholders and the US taxpayers.

Shocks to equity options' implied volatility are followed by persistently lower short-term rates. Shocks to puts' over calls' out-of-the-money implied volatilities (P/C) are followed by persistently higher rates. Stock and Treasury bond implied volatilities, which measure market and policy uncertainty, are countercyclical, while P/C, which measures downside risk, is procyclical. An equilibrium model in which investors and the central bank learn about composite regimes of economic and policy variables explains these dynamics, linking them to a learning-based, forward-looking Taylor rule. Survey data support our model's predictions on the effect of uncertainty on the level and fluctuations of implied volatilities.