Technological Progress, Managerial Learning, and the Investment-to-Stock Price Sensitivity

(with Kevin Aretz and Gaurav Kankanhalli)

Motivated by a real-options framework in which managers learn about the unobservable characteristics of new production technologies from their recently installed assets and their stock price, we show that the corporate investment-to-stock price sensitivity rises with the time since a firm last acquired new capacity. Notably, managers learn less from the stock price when they have better information, investors have worse information, or when alternative outside information sources exist. We shed light on the nature of information managers extract from markets by showing that firms with outdated capital learn more from the stock price when exogenously exposed to accelerated innovation.

Equity ETF Inefficiencies During Market Disruptions: The Role of Liquidity, Short-Selling, and Information Shocks

(with Sanjeev Bhojraj, Felipe Bastos Gurgel Silva, and Suning Zhang)

We document that the magnitude of spreads between equity ETF prices and the value of their corresponding constituent equities widened substantially during the period of market disruption at the onset of the COVID–19 pandemic, with plethora of equity ETF premiums and discounts that are directionally consistent with the smaller premiums and discounts of the period before the market distress. We show that ETF-constituent spreads widen particularly in days of high return volatility, typically indicating a dumping effect wherein ETF prices move in line with the value of the constituent basket but displaying returns of smaller magnitude. We show that relative differences in liquidity and short-selling constraints between the ETF and constituent equities partly explain the dynamics of ETF-constituent spreads, particularly in days of large price movements. Overall, our results shed light on how frictions in equity ETF markets are manifested in periods of high volatility.