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Discussion: “Institutional Herding” by Gutierrez and Kelley

Discussion: “Institutional Herding” by Gutierrez and Kelley. G. Garvey BGI. Strengths. Clearly and honestly done. For example, just takes cluster-buys or sells as they come Packs quite a bit of info in 26 pages. Refereeing process likely to add kilos of fat, so read this version

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Discussion: “Institutional Herding” by Gutierrez and Kelley

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  1. Discussion: “Institutional Herding” by Gutierrez and Kelley G. Garvey BGI

  2. Strengths • Clearly and honestly done. • For example, just takes cluster-buys or sells as they come • Packs quite a bit of info in 26 pages. • Refereeing process likely to add kilos of fat, so read this version • Potentially interesting finding. Looks at all institutions, not just mutual funds

  3. What’s the paper’s real question and contribution? • The phenomenon of herding? • Institutional investor performance? • Role of institutional investors in price formation? • An exploitable anomaly?

  4. Does it contribute to our understanding of herding? • Does not report descriptive stats on distribution of herd-size • Note: this could strongly time-vary and methodology here suppress this (uses ranks or regression stats by month or quarter) • Source of clustering/herding still quite mysterious. • Brown et al explain only a trivial portion with analyst recs

  5. Does it tell us much about institutional investor skill? • Smart guys (good past performers) appear to play the game well • Must be a small component of overall performance • But is it a viable indicator of real skill? • Turn your experiment around: do good herd-riders do well in their overall investments in the future? • Essentially, a specific arena in which skills can be displayed. Is the skill generalisable?

  6. Does it say much about price de-stabilization? • Extreme decile of buys produces reversible return of about 2.5%. • This is less than 10% of the vol of a representative stock • Since we are looking at the top 10% of buys, this is less than 1% of market vol • Arguably should be further shrunk towards zero because we used the sample to exclude sells as a destabilizer

  7. Is this an exploitable anomaly? • Some ssrn trawlers are surely trading this (although the authors make no claim about efficiency). Problems: • Need to be sure how this aggregates to the stock level, especially since your investment horizon is longer than a quarter • Lots of degrees of freedom used to get the result • Buys, not sells. Will this hold out of sample? • Time horizon of return effect is also left wide-open

  8. Where to go from here?Link more closely to trading and market impact • Challenge is that the data here are quarterly. • But at the end of the day this is a trading phenomenon and needs to be taken seriously as such. • More proprietary datasets? • Natural experiments (quant meltdown)? • Drill down to monthly mutual fund, and then to smaller subsets of investors whose trades can be observed more frequently?

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