Growth Opportunities,Technology Shocks,and Asset Prices

We explore the impact of investment‐specific technology (IST) shocks on the cross section of stock returns. Using a structural model, we show that IST shocks have a differential effect on the value of assets in place and the value of growth opportunities. This differential sensitivity to IST shocks has two main implications. First, firm risk premia depend on the contribution of growth opportunities to firm value. Second, firms with similar levels of growth opportunities comove with each other, giving rise to the value factor in stock returns and the failure of the conditional CAPM. Our empirical tests confirm the model's predictions.     

The Price Impact and Survival of Irrational Traders

Milton Friedman argued that irrational traders will consistently lose money, will not survive, and, therefore, cannot influence long‐run asset prices. Since his work, survival and price impact have been assumed to be the same. In this paper, we demonstrate that survival and price impact are two independent concepts. The price impact of irrational traders does not rely on their long‐run survival, and they can have a significant impact on asset prices even when their wealth becomes negligible. We also show that irrational traders' portfolio policies can deviate from their limits long after the price process approaches its long‐run limit.     

Measuring “Dark Matter” in Asset Pricing Models

We formalize the concept of “dark matter” in asset pricing models by quantifying the additional informativeness of cross-equation restrictions about fundamental dynamics. The dark-matter measure captures the degree of fragility for models that are potentially misspecified and unstable: a large dark-matter measure indicates that the model lacks internal refutability (weak power of optimal specification tests) and external validity (high overfitting tendency and poor out-of-sample fit). The measure can be computed at low cost even for complex dynamic structural models. To illustrate its applications, we provide quantitative examples applying the measure to (time-varying) rare-disaster risk and long-run risk models.     

Trading Complex Assets

We perform an experimental study to assess the effect of complexity on asset trading. We find that higher complexity leads to increased price volatility, lower liquidity, and decreased trade efficiency especially when repeated bargaining takes place. However, the channel through which complexity acts is not simply due to the added noise induced by estimation error. Rather, complexity alters the bidding strategies used by traders, making them less inclined to trade, even when we control for estimation error across treatments. As such, it appears that adverse selection plays an important role in explaining the trading abnormalities caused by complexity.     

Mutual Fund Trading Pressure: Firm‐Level Stock Price Impact and Timing of SEOs

We use price pressure resulting from purchases by mutual funds with large capital inflows to identify overvalued equity. This is a relatively exogenous overvaluation indicator as it is associated with who is buying—buyers with excess liquidity—rather than what is being purchased. We document substantial stock price impact associated with purchases by high‐inflow mutual funds, and find the probability of a seasoned equity offering (SEO), insider sales, and the probability of a stock‐based acquisition increase significantly in the four quarters following the mutual fund buying pressure. These results provide new evidence that firm managers are able to identify and exploit overvalued equity.     

Oil Futures Prices in a Production Economy with Investment Constraints

We document a new stylized fact, that the relationship between the volatility of oil futures prices and the slope of the forward curve is nonmonotone and has a V-shape. This pattern cannot be generated by standard models that emphasize storage. We develop an equilibrium model of oil production in which investment is irreversible and capacity constrained. Investment constraints affect firms' investment decisions and imply that the supply elasticity changes over time. Since demand shocks must be absorbed by changes in prices or changes in supply, time-varying supply elasticity results in time-varying volatility of futures prices. Estimating this model, we show it is quantitatively consistent with the V-shape relationship between the volatility of futures prices and the slope of the forward curve.     

Operating Hedge and Gross Profitability Premium

We show theoretically that variable production costs reduce systematic risk of firms' cash flows if capital and variable inputs are complementary in firms' production and input prices are procyclical. In our dynamic model, this operating hedge effect is weaker for more profitable firms, giving rise to a gross profitability premium. Moreover, gross profitability and value factors are distinct and negatively correlated, and their premia are not captured by the capital asset pricing model (CAPM). We estimate the model by simulated method of moments, and find that its main implications for stock returns and cash flow dynamics are quantitatively consistent with the data.