Exchange rate volatility and global shocks in Russia: an application of GARCH and APARCH models

Adebayo Augustine Kutu,Harold Ngalawa

doi:10.21511/imfi.13(4-1).2016.06

Abstract

This study examines global shocks and the volatility of the Russian rubble/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models. The GARCH and APARCH are employed under normal (Normal Gaussian) and non-normal (Student’s t and Generalized Error) distributions. Using monthly exchange rate data covering January 1994 – December 2013, the study finds that the symmetric (GARCH) model has the best fit under the non-normal distribution, which improves the overall estimation for measuring conditional variance. Conversely, the APARCH model does not show asymmetric response in exchange rate volatility and global shocks, resulting in no presence of leverage effect. The GARCH model under the Student’s t distribution produces better fit for estimating exchange rate volatility and global shocks in Russia, compared to the APARCH model. Keywords: exchange rate volatility, global Shocks, GARCH and APARCH models. JEL Classification: F30, F31, P33

Highlights

The Central Bank of Russia’s (CBR’s) control over the supply of money as its intermediate target of monetary policy became operational in 1995 after the dissolution of the Soviet Union.Prior to 1995, the country was “managing base money supply” with inflation, output and real exchange rate as the central targets of the central bank (Vdovichenko and Voronina, 2006)
In Russia, prolonged periods of low exchange rate volatility are followed by prolonged periods of low exchange rate volatility and prolonged periods of high exchange rate volatility are follow by prolonged periods of high exchange rate volatility
The results show that the parameters estimated under the three models are all significant, indicating that the lagged exchange rate, the ARCH and Generalized Autoregressive Conditional Heteroscedasticity (GARCH), as well as the global shocks contribute to exchange rate volatility in Russia

Summary

Introduction

The Central Bank of Russia’s (CBR’s) control over the supply of money as its intermediate target of monetary policy became operational in 1995 after the dissolution of the Soviet Union.Prior to 1995, the country was “managing base money supply” with inflation, output and real exchange rate as the central targets of the central bank (Vdovichenko and Voronina, 2006). The CBR has been gradually reducing its control of the exchange rate and creating a process for a shift to a floating exchange rate regime This regime shift is seen as one of the prerequisites for ensuring price stability. The currency has been facing serious challenges brought about by a number of factors in the international markets such as effects of the global financial crisis (see Kobersy et al, 2016). Against this background, this study estimates the volatility of Russia’s exchange rate and investigates its behavior vis-à-vis global shocks. Harold Ngalawa, College of Law and Management Studies, University of KwaZulu-Natal, South Africa

Objectives

Methods

Results

Conclusion