Working Papers
Informed Trading and the Cost of Capital: The Influence of Public and Private Information
with Florian Bardong, Söhnke M. Bartram, and Pradeep K. Yadav
Abstract: We find large time-series persistence for individual stocks, and strong commonality across stocks, in the profits from informed trading, indicating that the informational advantages driving informed trading do not arise just from idiosyncratic private information, but arguably also from skilled public information processing. We accordingly estimate the level of informed trading attributable separately to (skilled processing of) public information and to private information. We find that the risk-adjusted cost of capital is significantly higher for firms with higher expected levels of price-relevant informed trading based on public information, but it is not sensitive to higher residual levels of price-relevant informed trading based on private information. These findings hold, after fully controlling for liquidity, in both cross-sectional tests – using Fama and MacBeth (1973) regressions – and in time-series pricing tests that use risk factors based on returns of firms with high and low levels of informed trading driven by skilled public information processing and residual private information respectively. A long-short portfolio based on the expected level of informed trading arising from skilled processing of public information has annualized abnormal returns of 9.45%. When limited to the smallest quintile of stocks, these annualized abnormal returns grow to 29.30%. Furthermore, consistent with skilled processing of public information being a product of firms’ public information environments, we also find that the relation between cost of capital and public information based informed trading is weaker in firms with more competition for information. Overall, our results remain supportive (from different perspectives) of recent theoretical models – Easley and O’Hara (2004), Hughes, Liu, and Liu (2007) and Lambert, Luiz, and Verrechia (2011).
Intraday Volatility and Information Spillover in Leveraged and Unleveraged ETFs
with M. Jobaer Hossain and Pankaj K. Jain
Abstract: We examine intraday volatility spillover, trading market share, and information share of inverse and leveraged exchange traded funds (LETFs) relative to ETFs. LETFs market share declines with volatility indicating that traders balance aggregate risks arising from leverage versus volatility. However, informed traders increase LETFs use on volatile days, suggesting that macroeconomic information allows them to simultaneously partake in both risks. Market makers widen LETF spreads to compensate for this adverse selection. LETFs information share of 13% is 2.7 times their volume share. We also find strong inter-security dependence in returns, volatility, and price impact with more persistent spillover from LETFs to ETFs.
Margin Trading and Price Discovery in Cryptocurrency Markets
with Md. Jobaer Hossain and Shawn McFarland
Under Review
Abstract: We study the impact of a margin trading ban in cryptocurrencies on market dynamics. We document a decline in volume, market share, and volatility of the affected currency pairs following Binance’s ban on margin trading. Interestingly, we find that Binance’s information share of the affected currencies increased after the ban, and the proportion of information share-to-market share increased following the announcement of the ban (even though information share did not change until the ban itself), suggesting margin trading bans may reduce volatility from noise trading while increasing informed trading on a particular venue.