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The nonlinear price dynamics of U.S. equity ETFs

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  • Caginalp, Gunduz
  • DeSantis, Mark
  • Sayrak, Akin

Abstract

We investigate the price dynamics of large market-capitalization U.S. equity exchange-traded funds (ETFs) in order to uncover trader motivations and strategy. We show that prices of highly liquid ETFs can deviate significantly from their daily net asset values. By adjusting for changes in valuations, we report the impact of non-classical variables including price trend and volatility using data from 2008 to 2011. We find a cubic nonlinearity in the trend suggesting that traders are not only aware of the underreaction of others, but also self-optimize by anticipating others’ reactions, and sell when the uptrend is stronger than usual.

Suggested Citation

  • Caginalp, Gunduz & DeSantis, Mark & Sayrak, Akin, 2014. "The nonlinear price dynamics of U.S. equity ETFs," Journal of Econometrics, Elsevier, vol. 183(2), pages 193-201.
  • Handle: RePEc:eee:econom:v:183:y:2014:i:2:p:193-201
    DOI: 10.1016/j.jeconom.2014.05.009
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    Citations

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    Cited by:

    1. Caginalp, Gunduz & DeSantis, Mark, 2017. "Does price efficiency increase with trading volume? Evidence of nonlinearity and power laws in ETFs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 436-452.
    2. Caginalp, Gunduz & DeSantis, Mark, 2020. "Nonlinear price dynamics of S&P 100 stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    3. Zhu, Dingju, 2016. "Qualitative and quantitative combined nonlinear dynamics model and its application in analysis of price, supply–demand ratio and selling rate," Chaos, Solitons & Fractals, Elsevier, vol. 89(C), pages 54-72.
    4. Naeem, Muhammad & Umar, Zaghum & Ahmed, Sheraz & Ferrouhi, El Mehdi, 2020. "Dynamic dependence between ETFs and crude oil prices by using EGARCH-Copula approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    5. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2017. "A multifractal detrended fluctuation analysis of financial market efficiency: Comparison using Dow Jones sector ETF indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 182-192.
    6. Caginalp, Carey & Caginalp, Gunduz & Swigon, David, 2021. "Stochastic asset flow equations: Interdependence of trend and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    7. Gunduz Caginalp & Mark DeSantis, 2019. "Nonlinear price dynamics of S&P 100 stocks," Papers 1907.04422, arXiv.org.
    8. Zura Kakushadze & Juan Andrés Serur, 2018. "151 Trading Strategies," Springer Books, Springer, number 978-3-030-02792-6, November.
    9. Liu, Pan & Vedenov, Dmitry & Power, Gabriel J., 2020. "Commodity financialization and sector ETFs: Evidence from crude oil futures," Research in International Business and Finance, Elsevier, vol. 51(C).
    10. Carey Caginalp & Gunduz Caginalp, 2018. "Valuation, Liquidity Price, and Stability of Cryptocurrencies," Papers 1802.09959, arXiv.org.
    11. Caginalp, Carey & Caginalp, Gunduz, 2018. "The quotient of normal random variables and application to asset price fat tails," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 457-471.

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    More about this item

    Keywords

    Exchange-traded funds; Momentum; Volatility; Nonlinear dynamics;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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