Journal of Financial and Quantitative Analysis, June 2018, Vol. 53, 1371–1390.
We propose a market-based framework that exploits time-varying parameter vector autoregressions to estimate the dynamic network of financial spillover effects. We apply it to financials in the Standard & Poor's 500 index and estimate interconnectedness at the sector and institution level. At the sector level, we uncover two main events in terms of interconnectedness: the Long Term Capital Management crisis and the 2008 financial crisis. After these crisis events, we find a gradual decrease in interconnectedness, not observable using the classical rolling window approach. At the institution level, our framework delivers more stable interconnectedness rankings over time than other market-based measures of systemic risk.
- selected for the "Best Paper Session" at the Royal Economic Society PhD Meetings (Jan. 2017)
Journal of Financial Stability, Dec. 2018, Vol. 39, 90-103.
We study the association between daily changes in short selling activity and financial stock prices during extreme events using TailCoR, a measure of tail correlation. For the largest European and US banks, as well as European insurers, we uncover a strong relation during exceptional (extreme) days and a weak relation during normal (average) days. Examining days with large increases in short positions and large downfalls in stock prices, we find evidence of both momentum and contrarian short selling taking place. For North American bank stocks, contrarian short selling appears more practiced than for European bank and insurance stocks. We find that the uncovered relationship decreases with firm size and increases during ban periods, which is in line with short selling becoming more informative when constrained.
Assessing dynamic changes of the US financial market: insights from network science, (with Y. Gandica, J.Y. Gnabo and S. Béreau) PLOS ONE Journal, April 2018, Vol. 13(4).
Short selling and excess return correlation (With J.Y. Gnabo and D. Veredas)
We show that the number of common short sellers shorting two stocks can predict their excess correlation one-month ahead, controlling for many pair characteristics, including similarities in size, book-to-market, and momentum. We verify that this result holds out-of-sample and show that it can be used to establish a trading strategy that yields positive cumulative returns over 12 months. We explore the possible mechanisms that could give rise to this relationship. We find that neither the price-impact mechanism nor the liquidity mechanism can explain the uncovered relationship. Rather, it seems that the relationship is due to informed short selling, which we identify using several indicators of value obtained from financial statement analyses.