scholarly journals The Application of the Multivariate GARCH Models on the BRICS Exchange Rates

2020 ◽  
Vol 9 (4) ◽  
pp. 23
Author(s):  
Lebotsa Daniel Metsileng ◽  
Ntebogang Dinah Moroke ◽  
Johannes Tshepiso Tsoku
Keyword(s):  
South Africa ◽  
Exchange Rates ◽  
Time Series Data ◽  
Garch Model ◽  
Multivariate Garch ◽  
Series Data ◽  
Garch Models ◽  
Conditional Volatility ◽  
Volatility Persistence ◽  
Multivariate Garch Models

The study investigated the BRICS exchange rate volatility using the Multivariate GARCH models. The study used the monthly time series data for the period January 2008 to January 2018. The BEKK-GARCH model revealed that all the variables were found to be statistically significant. The diagonal parameters estimates showed that only Russia and South Africa were statistically significant. This implied that the conditional variance of Russia and South Africa’s exchange rates are affected by their own past conditional volatility and other BRICS exchange rates past conditional volatility. The BEKK-GARCH model also revealed that there is a bidirectional volatility transmission between Russia and South Africa. The results from the DCC-GARCH model revealed that Brazil, China, Russia and South Africa had the highest volatility persistence and India has the least volatility persistence. All the BRICS exchange rates show that the fitted residuals are not normally distributed except for Russia. The recommendations for future studies were articulated.

scholarly journals GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics

2001 ◽  
Vol 15 (4) ◽  
pp. 157-168 ◽  
Author(s):  
Robert Engle
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Garch Model ◽  
Applied Econometrics ◽  
Series Data ◽  
Garch Models ◽  
Portfolio Risk ◽  
Financial Applications ◽  
Analysis Of Time Series

ARCH and GARCH models have become important tools in the analysis of time series data, particularly in financial applications. These models are especially useful when the goal of the study is to analyze and forecast volatility. This paper gives the motivation behind the simplest GARCH model and illustrates its usefulness in examining portfolio risk. Extensions are briefly discussed.

scholarly journals Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models

SpringerPlus ◽  
2015 ◽  
Vol 4 (1) ◽  
Author(s):  
Ezekiel NN Nortey ◽  
Delali D Ngoh ◽  
Kwabena Doku-Amponsah ◽  
Kenneth Ofori-Boateng
Keyword(s):  
Exchange Rates ◽  
Multivariate Garch ◽  
Garch Models ◽  
Inflation Rates ◽  
Multivariate Garch Models

scholarly journals Pemodelan Pengukuran Luas Panen Padi Nasional Menggunakan Generalized Autoregressive Conditional Heteroscedastic Model (GARCH)

2014 ◽  
Vol 33 (1) ◽  
pp. 17
Author(s):  
Teuku Achmad Iqbal ◽  
Kusman Sadik ◽  
I Made Sumertajaya
Keyword(s):  
Time Series Data ◽  
Garch Model ◽  
Series Data ◽  
Percentage Error ◽  
Garch Models ◽  
Absolute Deviation ◽  
Significant Coefficient ◽  
Asymmetric Garch ◽  
Heteroscedastic Model ◽  
Better Than

This study was aimed to build a model for the estimation of national harvested area of rice by incorporating element of variant heterogeneity and the influence of asymmetry factors on time series data using five types of GARCH models, namely: symmetric GARCH, exponential asymmetric GARCH, quadratic asymmetric GARCH, Threshold GARCH, and non-linear asymmetric GARCH. Those models were compared and evaluated, and then the best model was used to predict the accuracy of the national rice harvested area. The results showed that two types of GARCH had significant coefficient, indicating the validity of the model. Those models were symmetric GARCH and quadratic GARCH models. Based on the value of mean absolute percentage error (MAPE) for the twelve month periods ahead, quadratic GARCH model was better than the symmetric GARCH model. Furthermore, based on the value of mean absolute deviation (MAD) and mean square error (MSE), quadratic GARCH model also seemed to be a better model than symmetric GARCH model. The best model can be used to predict the harvested area in the subsequent year.

South Africa’s Trade Performance under Alternative Exchange Rate Regimes

2018 ◽  
Vol 10 (6) ◽  
pp. 261
Author(s):  
Romaine Patrick ◽  
Phocenah Nyatanga
Keyword(s):  
South Africa ◽  
Exchange Rate ◽  
Exchange Rates ◽  
Exchange Rate Regime ◽  
Real Exchange Rates ◽  
Series Data ◽  
Growth Strategies ◽  
The Real ◽  
Real Price ◽  
Floating Exchange Rate

This study examined the effect exchange rates have on import and export volumes under alternative exchange rate policies adopted in South Africa over the period 1960 to 2017. Using quarterly time series data for the stated period, a log-linear error correction model is employed to estimate the country’s export and import elasticities, taking into account Gross Domestic Product (GDP), the real price of exports, the real price of imports and real exchange rates. Using the freely floating exchange rate regime as the base period, the study concluded that both export and import volumes are lower under a system of fixed exchange rates. Export and import volumes were also found to be lower under the dual exchange rate regime, relative to the freely floating exchange rate regime. In accordance with export-led growth strategies, exports were found to be higher and imports lower under a managed floating exchange rate regime. It is therefore recommended that South Africa revert to a more managed exchange rate regime, until the South African economy is developed to accommodate a freely floating exchange rate regime.

scholarly journals Non-bank financial institutions and economic growth: Evidence from Africa’s three largest economies

2017 ◽  
Vol 20 (1) ◽  
Author(s):  
Ronald Rateiwa ◽  
Meshach J. Aziakpono
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Financial Institutions ◽  
Time Series Data ◽  
Bank Lending ◽  
Series Data ◽  
The Sustainable Development ◽  
Long Run ◽  
The Relationship

Background: In order for the post-2015 world development agenda – termed the sustainable development goals (SDGs) – to succeed, there is a pronounced need to ensure that available resources are used more effectively and additional financing is accessed from the private sector. Given that traditional bank lending has slowed down, the development of non-bank financing has become imperative. To this end, this article intends to empirically test the role of non-bank financial institutions (NBFIs) in stimulating economic growth.Aim: The aim of this article is to empirically test the existence of a long-run equilibrium relationship between economic growth and the development of NBFIs, and the causality thereof.Setting: The empirical assessment uses time-series data from Africa’s three largest economies, namely, Egypt, Nigeria and South Africa, over the period 1971–2013.Methods: This article uses the Johansen cointegration and vector error correction model within a country-specific setting.Results: The results showed that the long-run relationship between NBFI development and economic growth is relatively stronger in Egypt and South Africa, than in Nigeria. Evidence in respect of Nigeria shows that such a relationship is weak. The nature of the relationship between NBFI development and economic growth in Egypt is positive and significant, and predominantly bidirectional. This suggests that a virtuous relationship between NBFIs and economic growth exists in Egypt. In South Africa, the relationship is positive and significant and predominantly runs from NBFI development to economic growth, implying a supply-leading phenomenon. In Nigeria, the results are weak and mixed.Conclusion: The study concludes that in countries with more developed financial systems, the role of NBFIs and their importance to the economic growth process are more pronounced. Thus, there is need for developing policies targeted at developing the NBFI sector, given their potential to contribute to economic growth.

Evidence of leverage effects and volatility spillover among exchange rates of selected emerging and growth leading economies

2019 ◽  
Vol 11 (2) ◽  
pp. 174-192 ◽  
Author(s):  
Ajaya Kumar Panda ◽  
Swagatika Nanda ◽  
Vipul Kumar Singh ◽  
Satish Kumar
Keyword(s):  
Exchange Rates ◽  
Asset Management ◽  
Spillover Effects ◽  
International Investment ◽  
Multivariate Garch ◽  
Conditional Volatility ◽  
Substantial Impact ◽  
Content Type ◽  
Volatility Spillovers ◽  
Strongly Connected

Purpose The purpose of this study is to examine the evidences of leverage effects on the conditional volatility of exchange rates because of asymmetric innovations and its spillover effects among the exchange rates of selected emerging and growth-leading economies. Design/methodology/approach The empirical analysis uses the sign bias test and asymmetric generalized autoregressive conditional heteroskedasticity (GARCH) models to capture the leverage effects on conditional volatility of exchange rates and also uses multivariate GARCH (MGARCH) model to address volatility spillovers among the studied exchange rates. Findings The study finds substantial impact of asymmetric innovations (news) on the conditional volatility of exchange rates, where Russian Ruble is showing significant leverage effect followed by Indian Rupee. The exchange rates depict significant mean spillover effects, where Rupee, Peso and Ruble are strongly connected; Real, Rupiah and Lira are moderately connected; and Yuan is the least connected exchange rate within the sample. The study also finds the assimilation of information in foreign exchanges and increased spillover effects in the post 2008 periods. Practical implications The results probably have the implications for international investment and asset management. Portfolio managers could use this research to optimize their international portfolio. Policymakers such as central banks may find the study useful to monitor and design interventions strategies in foreign exchange markets keeping an eye on the nature of movements among these exchange rates. Originality/value This is one of the few empirical research studies that aim to explore the leverage effects on exchange rates and their volatility spillovers among seven emerging and growth-leading economies using advanced econometric methodologies.

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