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Price Discovery Efficiency and Resilience of Financial Futures - A Case Study of Indian Banking Sector

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  • Mandal, Nivedita
  • Das, Rituparna

Abstract

India has proven to be the second most attractive emerging market among other large emerging economies in world. S&P has predicted India to be the one among fastest growing emerging markets in FY’22. According to Morgan Stanley report, banking is found to be the dominant sector in most of the emerging markets. Hence the banking sector in an emerging economy like India has the potential to attract fresh investment, so as their financial derivatives instruments. In this backdrop, the present work explores the price discovery mechanism between futures and spot markets in particular to Indian banking industry to bring forth sector specific insights. Alongside the paper tries to capture the impact of global slowdown due to Covid-19 pandemic during 2020-21on the Indian banking industry to check for its ‘resilience’ which is always a major concern for any emerging markets. The authors have used Bi-variate VEC-EGARCH framework to examine the price-discovery mechanism in the Bank-Nifty futures and spot markets. The short run impact of Covid-19 shock is measured with help of the ‘market model’ under ‘event study’ methodology.

Suggested Citation

  • Mandal, Nivedita & Das, Rituparna, 2022. "Price Discovery Efficiency and Resilience of Financial Futures - A Case Study of Indian Banking Sector," MPRA Paper 112844, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:112844
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    References listed on IDEAS

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    1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    2. Pratap Chandra Pati & Prabina Rajib, 2011. "Intraday return dynamics and volatility spillovers between NSE S&P CNX Nifty stock index and stock index futures," Applied Economics Letters, Taylor & Francis Journals, vol. 18(6), pages 567-574.
    3. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    4. Telser, Lester G, 1981. "Why There Are Organized Futures Markets," Journal of Law and Economics, University of Chicago Press, vol. 24(1), pages 1-22, April.
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    More about this item

    Keywords

    Bank-Nifty; Covid-19; Emerging Markets; Financial Futures; Price Discovery; Resilience; E-GARCH; Granger Causality; VAR; ECM;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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