ASYMMETRIC GARCH-TYPE AND HALF-LIFE VOLATILITY MODELLING OF USD/KZT EXCHANGE RATE RETURNS

Year 2020, Volume: 2 Issue: 2, 7 - 18, 15.07.2020

Mert Ural Erhan Demırelı

Abstract

Empirical studies have shown that a large number of financial assets returns exhibit fat tails (leptokurtosis) and are often characterized by volatility clustering and asymmetry. This paper considers the ability of the asymmetric GARCHtype models to capture the stylized features of volatility in USD/KZT exchange rate returns. Therefore, the half-life parameter of the USD/KZT returns series were calculated for three sub-periods. The results revealed that the half-life was 6 days, 16 days and 12 days for 1st sub-period, 2nd sub-period and 3rd sub-period respectively. According to the results, in the presence of asymmetric responses to innovations in the Kazakhstan foreign exchange market, the EGARCH (1.1)-GED model which accommodates the kurtosis of financial time series is preferred. Also, these results show that the USD/KZT exchange rate returns have strong mean reversion and short half-life.

Keywords

EGARCH, GJRGARCH, APGARCH, USD/KZT exchange rate, Half-life volatility

References

• Abdalla, Suliman Z.S. (2012). “Modelling Exchange Rate Volatility Using GARCH Models: Empirical Evidence from Arab Countries”. International Journal of Economics and Finance 4(3): 216-229.
• Ahmed, Rizwan R., Jolita Vveinhardt, Dalia Streimikiene and Zahid A. Channar (2018). “Mean Reversion in International Markets: Evidence from G.A.R.C.H. and Half-Life Volatility Models”. Economic Research-Ekonomska Istrazivanja 31(1): 1198-1217.
• Baltagi, Badi H. (2000). Econometrics, Fourth Edition. Springer Press. USA. Bollerslev, Tim (1986). “Generalized Autoregressive Conditional Heteroscedasticity”. Journal of Econometrics 31(3): 307-327.
• Bollerslev, Tim (1987). “A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return”. Review of Economics and Statistics 69(3): 542-547.
• Box, G.E.P. and David R. Cox (1964). “An Analysis of Transformation”. Journal of the Royal Statistical Society 26(2): 211-252.
• Brooks, Chris (2002). Introductory Econometrics for Finance. Cambridge University Press. UK.
• Chatfield, Chris (2003). The Analysis of Time Series: An Introduction, Sixth Edition. Chapman and Hall/CRC Publishing. USA.
• Ding, Zhuanxin, Clive W.J. Granger and Robert F. Engle (1993). “A Long Memory Property of Stock Market Returns and a New Model”. Journal of Empirical Finance 1(1): 83-106.
• Engle, Robert F. and Andrew J. Patton (2001). “What Good is a Volatility Model”. Quantitative Finance 1(2): 237–245.
• Engle, Robert F. (1982). “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation”. Econometrica 50(4): 987–1007.
• Fiser, Radovan and Roman Horvath (2010). “Central Bank Communication and Exchange Rate Volatility: A GARCH Analysis”. Macroeconomics and Finance in Emerging Market Economies 3(1): 25-31.
• Gbenro, Nathaniel and Richard K. Moussa (2019). “Asymmetric Mean Reversion in Low Liquid Markets: Evidence from BRVM”. Journal of Risk and Financial Management 12(38): 1-19.
• Glosten, G. Lawrence, Ravi Jagannathan and David E. Runkle (1993). “On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks”. Journal of Finance 48(5): 1779-1801.
• Hafner, Christian M. (1998). “Estimating High-Frequency Foreign Exchange Rate Volatility with Nonparametric ARCH Models”. Journal of Statistical Planning and Inference 68(2): 247-269.
• Hamadu, Dallah and Ismaila Adeleke (2009). “On Modelling the Nigerian Currency (Naira) Exchange Rates Against Major Regional and World Currencies”. NUST Journal of Business and Economics 2(1): 42-52.
• Harris, Richard and Sollis Robert (2003). Applied Time Series Modeling and Forecasting. John Wiley and Sons. USA.
• Kamal, Yasir, Hammad Ul-Haq, Usman Ghani and Muhammad M. Khan (2012). “Modeling the Exchange Rate Volatility, Using Generalized Autoregressive Conditionally Heteroscedastic (GARCH) Type Models: Evidence from Pakistan”. African Journal of Business Management 6(8): 2830-2838.
• Longmore, Rohan and Wayne Robinson (2004). “Modelling and Forecasting Exchange Rate Dynamics: An Application of Asymmetric Volatility Models”. Bank of Jamaica Working Paper WP2004/03.
• Nelson, Daniel B. (1991). “Conditional heteroskedasticity in asset returns: A new approach”. Econometrica 59(2): 347-370.
• Olowe, Rufus A. (2009). “Modeling Naira/Dollar Exchange Rate Volatility: Application of GARCH and Asymmetric Models”. International Review of Business Research Papers 5(3): 377-398.
• Thomas, Stuart and Heather Mitchell (2005). “GARCH Modeling of High-Frequency Volatility in Australia’s National Electricity Market. Discussion Paper”. Melbourne Centre for Financial Studies Discussion Paper.
• Ural, Mert (2010). Yatirim Fonlarinin Performans ve Risk Analizi (Performance and Risk Analysis of Investment Funds). First edition. Ankara: Detay Yayincilik.
• Wang, Alan T. (2006). “Does Implied Volatility of Futures Currency Option Imply Volatility of Exchange Rates”. Physica A: Statistical Mechanics and its Applications 374(2): 773-782.
• Yoon, Seok and Lee Ki Seong (2008). “The Volatility and Asymmetry of Won/Dollar Exchange Rate”. Journal of Social Sciences 4(1): 7-9.
• Zholamanova, Makpal, Maya Arzayeva, Raikhan Doszhan, Assel Turlybekova and Abai Kukiev (2018). “Devaluation in Kazakhstan: History, Causes, Consequences”. European Research Studies Journal 21(4): 831-842.