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Price and Volatility Linkages Between Indian Stocks and Their European GDRs

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  • Vinodh Madhavan
  • Partha Ray

Abstract

This article tests for price and volatility linkages between Indian global depositary receipts (GDRs) traded in Luxembourg/London and their underlying shares traded in Mumbai. The relationship is studied between the GDR price and the domestic share price along with the appropriate exchange rates, the foreign stock index and the domestic stock index using the vector autoregression (VAR) and dynamic conditional correlation (DCC) specification of multivariate generalised autoregressive conditional heteroscedasticity (GARCH) models. VAR results indicate a similarity between the two prices of scrips: one trading in Mumbai and the other trading in Luxembourg (London). Further, DCC-GARCH model outcomes point to, by and large, a high-dynamic correlation between Indian GDRs traded in Luxembourg/London and their underlying stocks listed in Mumbai. Thus, the price and volatility linkages between the Indian stock and its European counterpart are invariant with respect to the choice of the foreign stock exchange. Such a similarity in findings, notwithstanding the difference in degree of information disclosure as well as listing requirements at London and Luxembourg, is perhaps indicative of the stock-exchange-invariant nature of law of one price. JEL Classification: G15, C22

Suggested Citation

  • Vinodh Madhavan & Partha Ray, 2019. "Price and Volatility Linkages Between Indian Stocks and Their European GDRs," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2_suppl), pages 213-237, August.
    • Handle: RePEc:sae:emffin:v:18:y:2019:i:2_suppl:p:s213-s237
    DOI: 10.1177/0972652719846353
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    More about this item

    Keywords

    Dual listing; GDR; India; vector autoregression; DCC-GARCH;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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