Knowledge that Transforms

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The growth rate of industrial electricity usage predicts future stock returns up to 1 year with an R 2 of 9%. High industrial electricity usage today predicts low stock returns in the future, consistent with a countercyclical risk premium. Industrial electricity usage tracks the output of the most cyclical sectors. Our findings bridge a gap between the asset pricing literature and the business cycle literature, which uses industrial electricity usage to gauge production and output in real time. Industrial electricity growth compares favorably with traditional financial variables, and it outperforms Cooper and Priestley’s output gap measure in real time.

I develop a new predictive approach using Bayesian model averaging to account for incomplete knowledge of the true model behind corporate default and bankruptcy filing. I find that uncertainty over the correct model is empirically large, with far fewer variables being significant predictors of default compared with conventional approaches. Only the ratio of total liabilities to total assets and the volatility of market returns are robust default predictors in the overall sample and individual industry groups. Model-averaged forecasts that aggregate information across models or allow for industry-specific effects substantially outperform individual models.

Using unique transactions data for individual high-frequency trading (HFT) firms in the U.K. equity market, we examine the extent to which the trading activity of individual HFT firms is correlated with each other and the impact on price efficiency. We find that HFT order flow, net positions, and total volume exhibit significantly higher commonality than those of a comparison group of investment banks. However, intraday HFT order flow commonality is associated with a permanent price impact, suggesting that commonality in HFT activity is information based and so does not generally contribute to undue price pressure and price dislocations.

On Mar. 21, 2007, the U.S. Securities and Exchange Commission (SEC) passed Exchange Act Rule 12h-6 to make it easier for cross-listed firms to deregister from the U.S. market and escape its regulatory costs. Using difference-in-difference (DD) tests, we find that, on average, Rule 12h-6’s passage induced an increase in voting premium, a decline in equity raising, and a decline in cross-listing premium. These effects are observed for exchange-listed firms and for firms from countries with weak investor protection. We conclude that although cross-listed firms are still valued at a significant premium over non-cross-listed firms, the rule decreased the value of commitment to the U.S. regulatory system.

Analysts’ functions are divided into discovery and interpretation roles, but distinguishing between the two is nontrivial. We conjecture that analysts’ interpretation skill can be gauged by their forecast revisions following material unanticipated news, in particular, following nonearnings 8-K reports, which arrive at the market unexpectedly. We establish that unanticipated 8-Ks are informative for analysts and find that analysts who are more likely to revise their forecasts following unanticipated 8-Ks provide more timely and accurate forecasts. We document a positive association between analysts’ tendency to react to unanticipated 8-Ks and market reaction to their recommendation changes, suggesting investors prefer these analysts’ opinions.

Deregulation of the trucking industry and significantly lowered transportation costs led to large, widespread, and plausibly exogenous reductions in inventory for U.S. firms, with consequent increased supply-chain disruption (SCD) costs. We find evidence that increased SCD costs help explain the puzzling long-term trend of increasing average U.S. firm cash holdings. We also find that firms facing higher expected costs of disruptions generally save more cash from capital freed up via supply-chain management innovations. Finally, we document significant postdisruption declines in cash holdings consistent with cash as a primary source of financing during disruptions.

Deleveraging risk is the risk attributable to investing in a security held by levered investors. When there is an aggregate negative shock to the availability of funding capital, securities with a greater presence of levered investors experience extreme return realizations as these investors unwind their positions. Using data on equity loans as a proxy for the degree of levered positions in a given stock, we find robust evidence of deleveraging risk. Stocks with a high degree of short selling experience large positive returns and a decrease in short selling around periods of funding capital scarcity.