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Analysing exchange rate volatility in India using GARCH family models

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  • Rachna Mahalwala

    (University of Delhi)

Abstract

Volatility in foreign exchange market is an important issue of concern for market participants and policy makers as higher the volatility the more unstable the foreign exchange market is. The volatility of the foreign exchange market in India is modelled using daily spot rate of the Indian rupee per US Dollar (USD/INR) obtained from the RBI’s website from January 1, 2010 to December 31, 2020. All empirical work is done on USD/INR return series which was first modelled with ARMA framework and tested for ARCH effects with ARCH-LM test for heteroscedasticity. When ARCH-LM test approved the use of GARCH family models for modelling volatility, both symmetric and asymmetric models namely, GARCH (1,1), EGARCH (1,1), TGARCH (1,1) and APARCH (1,1) were used. Post-estimation test for remaining ARCH effects were done to check the efficiency of the models. TGARCH (1,1) turned to be the best model using both the AIC and SIC criterions showing the presence of significant asymmetric response to positive and negative shocks but leverage effects could not be established. This refers that foreign exchange market in India responds differently to information depending whether it positive or negative. This information is helpful for market participants in making trade, investment and other economic decisions.

Suggested Citation

  • Rachna Mahalwala, 2022. "Analysing exchange rate volatility in India using GARCH family models," SN Business & Economics, Springer, vol. 2(9), pages 1-16, September.
    • Handle: RePEc:spr:snbeco:v:2:y:2022:i:9:d:10.1007_s43546-022-00317-z
    DOI: 10.1007/s43546-022-00317-z
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    References listed on IDEAS

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    More about this item

    Keywords

    Exchange rate; Volatility; ARCH; GARCH; EGARCH; TGARCH; APARCH;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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