Research
Research
with Hamilton Galindo (Cleveland State University)
Journal of Financial Markets
A growing literature employs equity mutual fund flows to measure a stock’s exposure to non-fundamental demand risk - stock price fragility. However, this approach may be biased by confounding fundamental information, potentially leading to underestimating risk exposure. We propose an alternative estimation procedure incorporating readily available primary market data from exchange-traded funds (ETFs). Our proposed procedure significantly enhances the predictive power of fragility in forecasting stock return volatility. Moreover, we find that our measure captures the influence of increased ETF activeness while partially capturing the effect of institutional investors’ demand on price return volatility. Additionally, our analysis reveals a decrease in the explanatory power of mutual fund-based fragility. These results highlight the advantages of employing an ETF-based fragility measure that takes into account recent developments in the asset management industry, particularly the rise of passive investing.
[The Journal of Financial Markets ]
[Media Coverage: AlphaArchitect ]
[Data: Stock-Level ETF fragility]
with Ludwig Chincarini (U San Francisco) and Fabio Moneta (UOttawa)
Review and Resubmit at the Journal of Banking and Finance
This paper investigates the relation between crowded trades, those in which many investors hold the same stocks possibly exhausting their liquidity provision, and future stock returns on a set of well-known stock market anomalies. We find that anomaly risk - adjusted returns appear to be concentrated among the most (least) crowded stocks for the long-leg (short-leg) portfolio. Moreover, we find that our results remain significant after publication dates. We hypothesize that crowded equity positions in anomaly stocks increase institutional investor's exposure to crash risk and liquidity risk. Our findings are consistent with this hypothesis and suggest that crowding adds a new consideration to the limits of arbitrage.
[SSRN]