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Is USD-INR Really an Excessively Volatile Currency Pair?

Author

Listed:
  • Parthajit Kayal

    (Institute for Financial Management and Research)

  • S. Maheswaran

    (Institute for Financial Management and Research)

Abstract

The USD-INR currency pair has often been in the news for its excess volatility. This study examines the veracity of this belief by using the extreme value estimator proposed by Rogers and Satchell (Ann Appl Prob 1(4):504–512, 1991) and the VRatio proposed by Maheswaran et al. (J Emerg Mark Finance 10(2):175–196, 2011). The volatility in the USD-INR exchange rate is determined for the period beginning January 2009 and ending June 2015. The volatility of the GBP-INR and EUR-INR currency pairs is also determined for making comparisons. The results show that the EUR-INR and the GBP-INR currency pairs exhibit excess volatility, but not the USD-INR. This result runs counter to the commonly held view. This study also examines the volatility of the three currency pairs using the multiple-days’ time windows for better approximation of Brownian motion while embedding the jumps in the daily opening prices. There is no evidence to support the existence of excess volatility in the USD-INR.

Suggested Citation

  • Parthajit Kayal & S. Maheswaran, 2017. "Is USD-INR Really an Excessively Volatile Currency Pair?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(2), pages 329-342, June.
    • Handle: RePEc:spr:jqecon:v:15:y:2017:i:2:d:10.1007_s40953-016-0054-3
    DOI: 10.1007/s40953-016-0054-3
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    1. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    2. Patnaik, Ila & Shah, Ajay, 2010. "Does the currency regime shape unhedged currency exposure?," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 760-769, September.
    3. J. Bradford De Long & Richard Grossman, 1992. "Excess Volatility on the London Stock Market, 1870-1990," J. Bradford De Long's Working Papers _133, University of California at Berkeley, Economics Department.
    4. Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012. "Stochastic volatility models including open, close, high and low prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
    5. Cuthbertson, Keith & Hyde, Stuart, 2002. "Excess volatility and efficiency in French and German stock markets," Economic Modelling, Elsevier, vol. 19(3), pages 399-418, May.
    6. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    7. Kaushik I. Amin & Robert A. Jarrow, 2008. "Pricing foreign currency options under stochastic interest rates," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 14, pages 307-326, World Scientific Publishing Co. Pte. Ltd..
    8. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    9. Ball, Clifford A & Torous, Walter N, 1984. "The Maximum Likelihood Estimation of Security Price Volatility: Theory, Evidence, and Application to Option Pricing," The Journal of Business, University of Chicago Press, vol. 57(1), pages 97-112, January.
    10. Shiller, Robert J, 1979. "The Volatility of Long-Term Interest Rates and Expectations Models of the Term Structure," Journal of Political Economy, University of Chicago Press, vol. 87(6), pages 1190-1219, December.
    11. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    12. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    13. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    14. Kunitomo, Naoto, 1992. "Improving the Parkinson Method of Estimating Security Price Volatilities," The Journal of Business, University of Chicago Press, vol. 65(2), pages 295-302, April.
    15. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    16. Maheswaran, S. & Kumar, Dilip, 2013. "An automatic bias correction procedure for volatility estimation using extreme values of asset prices," Economic Modelling, Elsevier, vol. 33(C), pages 701-712.
    17. Malik Magdon-Ismail & Amir Atiya, 2003. "A maximum likelihood approach to volatility estimation for a Brownian motion using high, low and close price data," Quantitative Finance, Taylor & Francis Journals, vol. 3(5), pages 376-384.
    18. Kleidon, Allan W, 1986. "Variance Bounds Tests and Stock Price Valuation Models," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 953-1001, October.
    19. LeRoy, Stephen F & Porter, Richard D, 1981. "The Present-Value Relation: Tests Based on Implied Variance Bounds," Econometrica, Econometric Society, vol. 49(3), pages 555-574, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Excess volatility; Foreign exchange; Random walk; Simulation; Extreme value estimator; Market efficiency;
    All these keywords.

    JEL classification:

    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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