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Bootstrap Confidence Intervals and Hypothesis Testing for Market Information Shares
[Price Discovery and Common Factor Models]

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  • Karsten Schweikert

Abstract

Market information shares are widely used in empirical finance to measure one market’s contributions to price discovery. In contrast to common factor components, the literature on market information shares only provides rudimentary tools to test general hypotheses. Using Monte Carlo simulations, we show that bootstrap confidence bands proposed by Sapp (2002) perform well if markets have similar information shares but are too narrow if one market dominates price discovery. We design a new bootstrap-based method to test the “one-central-market” hypothesis and show that our tests have correct size and substantial power against the null hypothesis. Empirical results in the context of CDS and bonds markets complement the theoretical analysis.

Suggested Citation

  • Karsten Schweikert, 2021. "Bootstrap Confidence Intervals and Hypothesis Testing for Market Information Shares [Price Discovery and Common Factor Models]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 934-959.
    • Handle: RePEc:oup:jfinec:v:19:y:2021:i:5:p:934-959.
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    References listed on IDEAS

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    More about this item

    Keywords

    bootstrap inference; cointegration; Monte Carlo simulation; price discovery;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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