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The price leadership share: a new measure of price discovery in financial markets

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  • Riccardo De Blasis

    (Università Politecnica delle Marche)

Abstract

We propose a new measure to establish price leadership among multiple related price series using a multivariate Markov chain model. This new measure, the price leadership share (PLS), can easily be calculated when price series are related but not fully cointegrated (e.g. there is a fractional cointegration and the unit root test fails) and with more than two price series simultaneously, offering advantages over the existing price discovery measures. In addition, we propose a price leadership concentration index to help the comparative analysis. The measure is tested on six gold contracts, including spot, futures, and ETF, with a global coverage over a 2-year period. Results show that gold futures contracts, mainly the US contract (CME futures), have a major role in the price discovery function confirming the previous literature’s findings. Overall, the PLS measure overcomes the limits of other existing price discovery measures.

Suggested Citation

  • Riccardo De Blasis, 2020. "The price leadership share: a new measure of price discovery in financial markets," Annals of Finance, Springer, vol. 16(3), pages 381-405, September.
    • Handle: RePEc:kap:annfin:v:16:y:2020:i:3:d:10.1007_s10436-020-00371-3
    DOI: 10.1007/s10436-020-00371-3
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    Cited by:

    1. Riccardo De Blasis & Filippo Petroni, 2021. "Price Leadership and Volatility Linkages between Oil and Renewable Energy Firms during the COVID-19 Pandemic," Energies, MDPI, vol. 14(9), pages 1-16, May.
    2. Liwei Jin & Xianghui Yuan & Li Peiran & Hailun Xu & Feng Lian, 2023. "Option features and price discovery in convertible bonds," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 384-403, March.
    3. Riccardo De Blasis, 2023. "Weighted-indexed semi-Markov model: calibration and application to financial modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    4. Kuck, Konstantin & Schweikert, Karsten, 2023. "Price discovery in equity markets: A state-dependent analysis of spot and futures markets," Journal of Banking & Finance, Elsevier, vol. 149(C).
    5. Riccardo De Blasis & Giovanni Batista Masala & Filippo Petroni, 2021. "A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm," Energies, MDPI, vol. 14(2), pages 1-16, January.
    6. Guglielmo D’Amico & Giovanni Villani, 2021. "Valuation of R&D compound option using Markov chain approach," Annals of Finance, Springer, vol. 17(3), pages 379-404, September.
    7. Guglielmo D’Amico & Shakti Singh & Dharmaraja Selvamuthu, 2023. "Analysis of fair fee in guaranteed lifelong withdrawal and Markovian health benefits," Annals of Finance, Springer, vol. 19(3), pages 383-400, September.

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    More about this item

    Keywords

    Price leadership; Price discovery; Market fragmentation; Multivariate Markov chain; Mixture transition distribution;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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