Modeling volatility of Indian exchange rates under the impact of regime shifts: A study with economic significance analysis

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Dilip Kumar


In this paper, we assess the impact of regime shifts on the long memory properties of the Indian exchange rates. We make use of Sanso, Arago and Carrion (2004) Iterated Cumulative Sum of Squares (hereafter referred as AIT-ICSS) algorithm to detect the points of structural breaks in volatility series. Our findings indicate that incorporating the impact of sudden changes in volatility in the model indeed reduces the magnitude of long memory parameter. In the case of INR/JPY, we observe a shift in characteristics from long memory to mean reversion when the impact of regime shifts is included in the volatility model. Our findings also highlight that incorporating the impact of regime shifts in the model also improves the volatility forecast accuracy. Moreover, we implement a trading strategy based on risk-averse investor and find that the volatility forecasts based on the model which incorporate the impact of structural breaks provide substantial gains in return in comparison to volatility models with no structural breaks. These findings have important policy implications for financial market participants, investors and policy makers.

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Aggarwal, R, Inclan, C, and Leal, R (1999). "Volatility in emerging stock markets". Journal of Financial and Quantitative Analysis, 34, 33–55.

Baillie, R T, Bollerslev, T, and Mikkelsen, H O (1996). "Fractionally integrated generalized autoregressive conditional heteroskedasticity", Journal of Econometrics, 74, 3-30.

Beine, M and Laurent, S (2003). “Central Bank Interventions and Jump in Double Long Memory Models of Daily Exchange Rates,” Journal of Empirical Finance, 10(5), 641-660.

Bollerslev, T (1986). "Generalized autoregressive conditional heteroskedasticity", Journal of Econometrics, 31, 307–327.

Driesprong, G., Jacobsen, B., and Maat, B., (2008). “Striking oil: another puzzle?” Journal of Financial Economics. 89 (2), 307–327.

Engle, R (1982). "Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation", Econometrica, 50, 987–1007.

Engle, R F, and Bollerslev, T (1986). "Modelling the persistence of conditional variances", Econometric Reviews, 5, 1-50.

Engle, R F and Ng, V K (1993). "Measuring and Testing the Impact of News on Volatility," Journal of Finance, 48, 1749-1778.

Fernandez, A, and Arago, V (2003). "European volatility transmission with structural changes in variance", Working Paper presented at the XI Foro de Finanzas, Alicante (Spain).

Hammoudeh, S, and Li, H (2008). "Sudden changes in volatility in emerging markets: The case of Gulf Arab stock markets," International Review of Financial Analysis, 17, 47-63.

Han, Y W (2003). “Long Memory Property and Central Bank Intervention During Currency Crisis in the Daily Korean won-US dollar Exchange Rates,” The Journal of the Korean Economy, 4(1), 93-116.

Inclán, C and Tiao, G C (1994). "Use of cumulative sums of squares for retrospective detection of changes of variance," Journal of the American Statistical Association, 89, 913–923.

Kang, I (1999). "International foreign exchange agreements and nominal exchange rate volatility: A GARCH application", North American Journal of Economics and Finance, 10, 453-472.

Lamoureux, C G, and Lastrapes, W D (1990). "Persistence in variance, structural change and the GARCH model", Journal of Business and Economic Statistics, 68, 225–234.

Lastrapes, W D (1989). "Exchange rate volatility and US monetary policy: An ARCH application", Journal of Money, Credit and Banking, 21, 66–77.

Lobo, B J and Tufte D (1998). "Exchange rate volatility: Does politics matter?", Journal of Macroeconomics, 20, 351-365.

Malik, F (2003). "Sudden changes in variance and volatility Persistence in foreign exchange markets," Journal of Multinational Financial Management, 13 (3), 217-230.

Malik, F, Ewing, B T, and Payne, J E (2005). "Measuring volatility persistence in the presence of sudden changes in the variance of Canadian stock returns," Canadian Journal of Economics, 38, 1037-1056.

Marquering, W., and Verbeek, M., (2004). “The economic value of predicting stock index returns and volatility”, The Journal of Financial and Quantitative Analysis, 39 (2), 407–429.

Narayan, P. K., and Sharma, S. S., (2014). “Firm return volatility and economic gains: The role of oil prices”, Economic Modelling, 38, 142-151

Newey, W K and West, K D (1994). "Automatic lag selection in covariance matrix estimation," Review of Economic Studies, 61 (4), 631–654

Poon, S H, and Granger, C W J (2003). "Forecasting volatility in financial markets: A review," Journal of Economic Literature, 41, 478–539.

Ross, S A (1989). "Information and volatility: The no-arbitrage martingale approach to timing and resolution irrelevancy", Journal of Finance, 44, 1–7.

Sanso , A, Arago, V, and Carrion, J L (2004). "Testing for change in the unconditional variance of financial time series", Revista de Economiá Financiera, 4, 32-53.

Tse, Y K, (1998), “The Conditional Heteroscedasticity of the Yen-dollar Exchange Rate,” Journal of Applied Econometrics, 13(1), 49-55.

Wang, P, and Moore, T (2009). "Sudden changes in volatility: The case of five Central European stock markets," Journal of International Financial Markets, Institutions and money, 19, 33-46.

Wilson, B, Aggarwal, R and Inclan, C (1996). "Detecting volatility changes across the oil sector", Journal of Futures Markets, 16, 313-330.