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. 2020 Mar 24;15(3):e0230393.
doi: 10.1371/journal.pone.0230393. eCollection 2020.

Evolutionary disruption of S&P 500 trading concentration: An intriguing tale of a financial innovation

Affiliations

Evolutionary disruption of S&P 500 trading concentration: An intriguing tale of a financial innovation

S Gowri Shankar et al. PLoS One. .

Abstract

The novel finding of Balakrishnan, Miller & Shankar (2008) that investors, overwhelmed by the plethora of stock investment offerings, limit their analysis and daily choices to only a small subset of stocks (i.e., herding behavior) now seems to be common wisdom (Iosebashvili, 2019). We investigate whether the introduction of an innovation in financial products designed to allow investors to trade the entire product bundle of S&P 500 stocks, namely S&P 500 index funds, altered "herding behavior" by creating a new class of index investors. We model the distribution of daily trading concentration as a power law function and examine changes over the last six decades. Intriguingly, we discover a unique pattern in the trading concentration distribution that exhibits two distinct trends. For the period 1960-75, the trading concentration of the S&P 500 stocks tracks the increasing trend for the entire market, i.e., the unevenness in trading has steadily increased. However, after the introduction of S&P 500 index funds in 1975, concentration of trading in the S&P 500 stocks has steadily decreased, i.e., trading distribution has become more even across all 500 stocks, contrary to the current belief of equity analysts. This is also in sharp contrast to the case of U.S. stocks that are not in the S&P 500 index where trading concentration has steadily increased. We further corroborate the uniqueness of the inverted V-shape by a counterfactual investigation of the trading concentration patterns for other sets of 500 stock portfolios. This uniquely distinctive trading concentration pattern for S&P 500 stocks appears to be driven by the increasing dominance of bundle trading by index investors.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Percentage share of the top quintile of stocks in the total trading volume of S&P 500 and non-S&P 500 stocks, 1960 to 2018.
Fig 2
Fig 2. Annual averages of the daily Trading Concentration Indices (power low exponents) for S&P 500 stock portfolios and non-S&P 500 stock portfolios, 1960 to 2018.
Fig 3
Fig 3. Different between the annual averages of the daily Trading Concentration Indices for S&P 500 and non-S&P 500 portfolios, 1960 to 2018.
Fig 4
Fig 4. Annual averages of daily Trading Concentration Indices (TCI) for all stocks, top 500 stocks, random500 stocks, S&P 500 stocks, and non-S&P 500 stocks portfolios, 1960 to 2018.
Fig 5
Fig 5. Annual averages of the daily Trading Concentration Indices for the distribution of S&P 500 trading volumes and S&P 500 market capitalizations.

References

    1. Balakrishnan PV, Miller JM, Shankar SG. Power law and evolutionary trends in stock markets. Economics Letters. 2008;98: 194–200.
    1. Axtell RL. Zipf Distribution of U.S. Firm Sizes. Science. 2001;293: 1818–1820. 10.1126/science.1062081 - DOI - PubMed
    1. Gabaix X, Gopikrishnan P, Plerou V, Eugene Stanley H. A theory of power-law distributions in financial market fluctuations. Nature. 2003;423: 267 10.1038/nature01624 - DOI - PubMed
    1. Okuyama K, Takayasu M, Takayasu H. Zipf’s law in income distribution of companies. Physica A: Statistical Mechanics and its Applications. 1999;269: 125–131. 10.1016/S0378-4371(99)00086-2 - DOI
    1. Gao X, Ritter JR, Zhu Z. Where Have All the IPOs Gone? Journal of Financial and Quantitative Analysis. 2013;48: 1692 10.1017/S0022109014000015 - DOI