Knowledge that Transforms

We estimate an ex ante probability of extreme negative returns (crashes) of individual stocks as a measure of potential overpricing and find that stocks with a high probability of crashes earn abnormally low returns. Stocks with high crash probability are overpriced regardless of the level of institutional ownership or variations in investor sentiment, and moreover, they exhibit increasing institutional demand until their prices reach the peak of overvaluation. We also find that institutional investors who overweight high crash probability stocks outperform the others, indicating that they have skill in timing bubbles and crashes of individual stocks. Our findings imply that sophisticated investors may not always trade against mispricing but time the correction of overpricing, and suggest that the crash effect we find could arise at least partially from rational speculative bubbles, not entirely from sentiment-driven overpricing.

We test whether bear market risk, time variation in the probability of future bear market states, is priced. We construct an Arrow–Debreu security that pays off in bear market states (AD Bear) from traded Standard & Poor’s (S&P) 500 index options and use its returns to measure bear market risk. We find that bear beta (exposure to bear market risk) has a strong relation with expected stock returns that is robust, persistent, and remains strong among liquid and large stocks. Historical bear beta also predicts future bear market risk exposure. We conclude that bear market risk is priced in the cross section of stock returns.

We propose a new modeling approach for the cross section of returns. Our method, Instrumented Principal Component Analysis (IPCA), allows for latent factors and time-varying loadings by introducing observable characteristics that instrument for the unobservable dynamic loadings. If the characteristics/expected return relationship is driven by compensation for exposure to latent risk factors, IPCA will identify the corresponding latent factors. If no such factors exist, IPCA infers that the characteristic effect is compensation without risk and allocates it to an “anomaly” intercept. Studying returns and characteristics at the stock-level, we find that five IPCA factors explain the cross section of average returns significantly more accurately than existing factor models and produce characteristic-associated anomaly intercepts that are small and statistically insignificant. Furthermore, among a large collection of characteristics explored in the literature, only ten are statistically significant at the 1% level in the IPCA specification and are responsible for nearly 100% of the model’s accuracy.

We evaluate Eugene F. Fama's claim that stock prices do not exhibit price bubbles. Based on US industry returns (1926‒2014) and international sector returns (1985‒2014), we present four findings (1) Fama is correct in that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward; (2) such sharp price increases predict a substantially heightened probability of a crash but not of a further price boom; (3) attributes of the price run-up, including volatility, turnover, issuance, and the price path of the run-up, help forecast an eventual crash; and (4) these attributes also help forecast future returns. Results hold similarly in US and international samples.

We examine the impact of investor coordination on governance. We identify coordinating groups of investors (cliques) as those connected through the network of institutional holdings. Clique members vote together on proxy items: a one standard deviation increase in clique ownership more than doubles votes against low quality management proposals. We use the 2003 mutual fund trading scandal to show that this effect is causal. These findings suggest coordination strengthens governance via voice. Coordination, however, also weakens governance via threat of exit. Clique owners exit positions more slowly, and firm value responds negatively to liquidity shocks when clique ownership is high.

Differences among bidder type-specific outcomes of asset sales are theoretically related to differences in bidders’ valuations and participation. The lead application to quantify these relations is takeover auctions: bidders are classified into strategic and financial, and bids are available. I structurally estimate valuations from all bids. The positive difference in premiums between strategic and financial acquirers is driven by the difference in dispersions of valuations (e.g., strategic bidders’ synergies are more dispersed) and the set of auction participants. The difference in average valuations is relatively unimportant. My approach can help explain outcomes of asset sales, even in settings with limited bidder data.

We study the effect of collateralized lending and securitization on international capital flows and welfare in a two-country general equilibrium model with idiosyncratic investment risk. The low-margin country (Home) endogenously supplies more safe assets and enables more risk sharing. Upon financial integration, capital flows from Foreign (high-margin country) to Home, leading to lower interest rates and a larger global supply of safe assets. Unlike in standard models with partial equity issuance, in our model, Home can lose from financial integration due to the endogenous reduction in risk sharing and aggregate shocks can generate large gross capital flows.

Using a data set covering one quarter of the U.S. general-purpose credit card market, we document that 29% of accounts regularly make payments at or near the minimum payment. To explain the prevalence of low payment amounts, we exploit changes in issuers’ minimum payment formulas to quantify the explanatory power of two potential theories: liquidity constraints and anchoring. At least 22% of near-minimum payers (and 9% of all accounts) respond to the formula changes in a manner consistent with anchoring as opposed to liquidity constraints alone. Our results show that anchoring to a salient contractual term has a significant impact on household repayment decisions.

We build a model of endogenous, innovation-driven growth in which innovative firms have costly access to outside financing and hoard cash reserves to maintain financial flexibility. We show that financing frictions slow down Schumpeterian creative destruction by discouraging entry. As a result, financing frictions importantly affect the composition of growth, by reducing the contribution of entrants but spurring the contribution of incumbents. We investigate the net impact of these countervailing effects on the equilibrium growth rate and welfare.

This paper is concerned with statistical inference and model evaluation in possibly misspecified and unidentified linear asset pricing models estimated by maximum likelihood. Strikingly, when spurious factors (that is, factors that are uncorrelated with the returns on the test assets) are present, the model exhibits perfect fit, as measured by the squared correlation between the model’s fitted expected returns and the average realized returns. Furthermore, factors that are spurious are selected with high probability, and factors that are useful are driven out of the model. While ignoring potential misspecification and lack of identification can be very problematic for models with macroeconomic factors, empirical specifications with traded factors (e.g., Fama and French, 1993; Hou et al., 2015) do not suffer from the identification problems shown in this study.