Skip to content
All library documents

How Passive Investing May Affect Market Price Efficiency

Article Quant Q&A · Author: Odyssey
Read the original

Summary

The discussion considers whether growth in passive and index investing could weaken price discovery by reducing the capital devoted to researching securities and trading on mispricing. It distinguishes low-cost passive investing from exact index replication, and raises the possibility that broad market-cap-weighted funds can reinforce existing relative valuations. A proposed alternative is a low-maintenance portfolio that does not mechanically track an index.

The answers describe indirect evidence rather than a settled causal result. They point to studies associating greater ETF ownership with trading costs, return synchronicity, analyst coverage, and measures of information in prices, and cite examples of factor and momentum effects weakening after discovery. The authors emphasize that market efficiency is difficult to measure directly, that these observations do not establish a universal threshold for active capital, and that algorithmic finance may also reduce opportunities to profit from anomalies. The issue remains open in the document.

Key ideas

  • Active investors can contribute to price discovery by researching securities and trading on mispricing.
  • A shift toward passive allocation could reduce incentives for information gathering, but its effect on efficiency is hard to measure.
  • The discussion cites associations between ETF ownership and several indicators of weaker information in prices.
  • Evidence that known anomalies weaken over time is suggestive but does not prove passive investing caused the change.
  • Passive investing can use approaches other than strict market-cap index replication.

Tags

EquitiesFactor investingPortfolio constructionMarket microstructureStatistics
Full text
# Is the realized leg of a gamma swap same as gamma-weighted variance?


# Is the realized leg of a gamma swap same as gamma-weighted variance?












option gamma is approximate to 1/S^2, so for gamma swap, the realized variance leg is just multiply by S_t, not same as gamma weighted variance, why call it gamma variance then?

anyone can explain? Thanks

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.