International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Abstract: The theoretical relationship of the long-run equilibrium between real exchange rates and interest rate differentials is essentially derived from the Purchasing Power Parity (PPP) and the uncovered interest parity. However, empirical evidence on this long-run relationship has rather been inconclusive. While several authors are able to establish the long-run relationship between real exchange rates and interest rate differentials other could not found this relationship. The reason for lack of relationship in some of the studies is as a result of omitted variables (Meese and Rogoff, 1988). Therefore, attempt is made in this study to evaluate this relationship between real exchange rate and interest rate differential for the case of Nigeria by controlling for foreign exchange reserves. The paper uses monthly data for the period 1993:1-2012:12 and applies Autoregressive Distributed Lags (ARDL) model. The estimates suggest the existence of long-run relationship between real exchange rate, interest rate differential and foreign exchange reserves. In the long run, the exchange rate coefficient has a positive effect on the foreign reserves. However, the effect of interest rate differential is negative and statistically significant. On the short run dynamics, the finding indicates a non-monotonic relationship between real exchange rate, interest rate differential and foreign exchange reserves. The out-of-sample forecast indicates a better forecast using ARMA model as all Theil coefficients are close zero for all the horizons used in the model.
Inflation is a continual increase in general price level of goods and services in an economy over a period of time. It is caused by many factors, important among them are excess of demand of goods and services over supply, macroeconomic performance, money supply, economic policies implications, environmental factors etc. A number of researchers in the past made attempts to identify determinants of inflation and to investigate the impact of identified variables on inflation in European and also in some Asian economies. But, in context of India, not many studies can be traced in the literature. The purpose of this paper is to shed some light on the impact of selected variables on inflation in India. The paper considers CPI (Consumer Price Index) inflation as dependent variable and a set of independent macroeconomic variables, which includes Gross Domestic Product, Money Supply, Deposit Rate, Prime Lending Rate, Exchange Rate, Trade Volume (Value of Imports and Exports) and Crude Oil Prices. The empirical analysis covers the quarterly data series for ten financial years from 2002Q1 to 2012Q1. The collected data is analyzed using ADF Unit root test, Granger Causality test, and the Ordinary Least Square (OLS) technique.
Empirical literature on money demand is mainly based on the estimation of a long run relation by means of time-invariant cointergration approach. Taiwan has experienced the economic and financial regime change since 1979. The purpose of this paper is to test structural breaks in Taiwan long run money demand equation. We examine six of the most influential specifications proposed in the literature. The classical set of explanatory variables (e.g. income and interest rates) is extended on the base of a number underlying economic reasons related to financial, labor and international portfolio characteristics. The results suggest that international financial market variables and the classical specifications are the key determinants of structural instability observed in Taiwan broad money.
Devanayagam_Impact of Macroeconomic Variables on Global Stock MarketsDevanayagam N
This presentation is about how macroeconomic variables such as GDP, GDP growth rate, Inflation, Unemployment Rate and Development Status of countries influence the performance of Global stock markets (Stock Exchanges across the world).
The Causal Analysis of the Relationship between Inflation and Output Gap in T...inventionjournals
The purpose of the paper is to study dynamic relationships between the inflation and output gap by using Granger causality, Impulse response and variance decompositions analysis within VECM framework for the quarterly data over the first period of 2003 and second period of 2016. The results of the study indicate that the output gap Granger cause the inflation in Turkey both in short-and long-runs. Also, sign of the causality is negative and same causal relationships between two variables hold beyond the sample period. The results should be taken as an evidence of the conclusion that the output gap has important implications for the CBRT's monetary policy.
Abstract: The theoretical relationship of the long-run equilibrium between real exchange rates and interest rate differentials is essentially derived from the Purchasing Power Parity (PPP) and the uncovered interest parity. However, empirical evidence on this long-run relationship has rather been inconclusive. While several authors are able to establish the long-run relationship between real exchange rates and interest rate differentials other could not found this relationship. The reason for lack of relationship in some of the studies is as a result of omitted variables (Meese and Rogoff, 1988). Therefore, attempt is made in this study to evaluate this relationship between real exchange rate and interest rate differential for the case of Nigeria by controlling for foreign exchange reserves. The paper uses monthly data for the period 1993:1-2012:12 and applies Autoregressive Distributed Lags (ARDL) model. The estimates suggest the existence of long-run relationship between real exchange rate, interest rate differential and foreign exchange reserves. In the long run, the exchange rate coefficient has a positive effect on the foreign reserves. However, the effect of interest rate differential is negative and statistically significant. On the short run dynamics, the finding indicates a non-monotonic relationship between real exchange rate, interest rate differential and foreign exchange reserves. The out-of-sample forecast indicates a better forecast using ARMA model as all Theil coefficients are close zero for all the horizons used in the model.
Inflation is a continual increase in general price level of goods and services in an economy over a period of time. It is caused by many factors, important among them are excess of demand of goods and services over supply, macroeconomic performance, money supply, economic policies implications, environmental factors etc. A number of researchers in the past made attempts to identify determinants of inflation and to investigate the impact of identified variables on inflation in European and also in some Asian economies. But, in context of India, not many studies can be traced in the literature. The purpose of this paper is to shed some light on the impact of selected variables on inflation in India. The paper considers CPI (Consumer Price Index) inflation as dependent variable and a set of independent macroeconomic variables, which includes Gross Domestic Product, Money Supply, Deposit Rate, Prime Lending Rate, Exchange Rate, Trade Volume (Value of Imports and Exports) and Crude Oil Prices. The empirical analysis covers the quarterly data series for ten financial years from 2002Q1 to 2012Q1. The collected data is analyzed using ADF Unit root test, Granger Causality test, and the Ordinary Least Square (OLS) technique.
Empirical literature on money demand is mainly based on the estimation of a long run relation by means of time-invariant cointergration approach. Taiwan has experienced the economic and financial regime change since 1979. The purpose of this paper is to test structural breaks in Taiwan long run money demand equation. We examine six of the most influential specifications proposed in the literature. The classical set of explanatory variables (e.g. income and interest rates) is extended on the base of a number underlying economic reasons related to financial, labor and international portfolio characteristics. The results suggest that international financial market variables and the classical specifications are the key determinants of structural instability observed in Taiwan broad money.
Devanayagam_Impact of Macroeconomic Variables on Global Stock MarketsDevanayagam N
This presentation is about how macroeconomic variables such as GDP, GDP growth rate, Inflation, Unemployment Rate and Development Status of countries influence the performance of Global stock markets (Stock Exchanges across the world).
The Causal Analysis of the Relationship between Inflation and Output Gap in T...inventionjournals
The purpose of the paper is to study dynamic relationships between the inflation and output gap by using Granger causality, Impulse response and variance decompositions analysis within VECM framework for the quarterly data over the first period of 2003 and second period of 2016. The results of the study indicate that the output gap Granger cause the inflation in Turkey both in short-and long-runs. Also, sign of the causality is negative and same causal relationships between two variables hold beyond the sample period. The results should be taken as an evidence of the conclusion that the output gap has important implications for the CBRT's monetary policy.
This paper provides a review of the empirical macroeconomic model (EMMA) built for forecasting purposes at the Finnish Labour Institute for Economic Research. The model is quite small, consisting of 71 endogenous and 70 exogenous variables. The number of behavioural equations is 15. The basis of the model is Keynesian, although the model has some novel properties. They are the treatment of the supply side and prices that follow the routes of the neoclassical synthesis. The parameters of the model are estimated from quarterly data that cover the years 1990–2005. The model also contains a Kalman-filtered variable to control the deep recession in Finland at the beginning of the ’90s. This special feature brings the model closer to the new calibrated models.
The identification of a possible European business cycle has been inconclusive and is complicated by the enlargement to the new member states and their transition to market economies. This paper shows how to decompose a business cycle into a time-frequency framework in a way that allows us to accommodate structural breaks and nonstationary variables. To illustrate, calculations of the growth rate spectrum and coherences for the Hungarian, Polish, German and French economies show the instability of the transition period. However, since then there has been convergence on the Eurozone economy at short cycle lengths, but little convergence in long cycles. We argue that this shows evidence of nominal convergence, but little real convergence. The Maastricht criteria for membership of the Euro therefore need to be adapted to test for real convergence.
Authored by: Andrew Hughes Hallett, Christian R. Richter
Published in 2007
This article seeks to examine the impact of the Bangladesh’s stock market development on its economic growth from the period of 1989-2012. We have used Johansen Cointegration test to estimate the long-run equilibrium relationship between the variables and the Granger causality test was conducted in order to establish causal relationship, while the model was estimated using the error correction model (ECM). Johansen co-integration test results show that the Bangladesh’s stock market development and economic growth are co-integrated. This indicates that a long run relationship exists between stock market development and economic growth in Bangladesh. The causality test results suggest a unidirectional causality from stock market development to the economic growth. On the other hand, there is no “reverse causation” from economic growth to stock market development. The evidence from this study reveals that the activities in the stock market tend to impact positively on the economy. It is recommended therefore that stock market regulatory authority should therefore address policy issues that are capable of boosting the investors’ confidence through improved policy formulation and creation of awareness.
Forecasting the Exchange Rates of the Iraqi Dinar against the US Dollar using...Dr. Amarjeet Singh
Estimating the exchange rate is considered a key
tool for economic planning and reaching economic stability.
This study aims to reach the best model for predicting
exchange rates of Iraqi Dinar against the U.S. dollar in the
period (2008-2017). For this purpose the following methods
have been adopted: - Time-series analysis using the Box –
Jenkins approach.
Forecasts obtained from the two models were
compared using both mean of the absolute values of the errors
(MAE) and the square root of the mean square error (RMSE).
The ARIMA (1,1,1) model produced the best forecasts and it
can be used as a reliable method of estimating the exchange
rate of any foreign currency.
This paper empirically examines the role of uncertainty occurred by ‘news’ in Japanese financial markets. A GARCH-MIDAS model is used for estimation. It finds that news-based implied volatility performs well in predicting long-term aggregate market volatilities. A subsample analysis provides that the predictive power of news-based volatility is continuing, as most of the coefficients are positive and significant. So, in general, the news based implied volatility model is associated with high market volatility. Moreover, stock market prices go on rising, different effects that appeared in each subsample period. On the recent period, when Abenomics was conducted, the effect decreased. Also, the effect of exchange rates decrease in short time. When stock prices decrease, volatilities of the stock prices in the past period increase. There is some possibility that markets were too unstable about the movements because of the low prices. Also, the volatility of long-term interest rates increases when the interest rate declines in the recent period under Abenomics. Although interest rates have been quite low in both sample periods, the Bank of Japan (BOJ) started to manage long-term interest rates in the recent period, so market participants seem to begin noticing the movements.
The paper proposes two econometric models of inflation for Azerbaijan: one based on monthly data and eclectic, another based on quarterly data and takes into account disequilibrium at the money market. Inflation regression based on monthly data showed that consumer prices dynamics is explained by money growth (the more money, the higher the inflation), exchange rate behaviour (appreciation drives disinflation), commodities price dynamics (“imported” inflation) and administrative changes in regulated prices. For the quarterly model, nominal money demand equation (with inflation, real non-oil GDP and nominal interest rate on foreign currency deposits as predictors) and money supply equation were estimated, and error-correction mechanism from money demand equation was included into inflation equation. It is shown that disequilibrium at the money market (supply higher than demand) drives inflation together with money supply growth and nominal exchange rate depreciation and administrative changes in prices. No cost-push variables appeared to be significant in this equation specification. Both models give similar inflation projections, but sudden changes in money demand (2012) lead to significant differences between the projections. It is shown that money is the most important inflation determinant that explains up to 97.8% of CPI growth between 2012 and 2015, and that in order to keep inflation under control the Central Bank of Azerbaijan should link money supply to real non-oil GDP growth.
Authored by: Alexander Chubrik, Przemyslaw Wozniak, Gulnar Hajiyeva
Published in 2012
Developing economies are different than developed economies in many aspects, i.e., in terms of institutional framework and political situation etc. Thus, the monetary policy needed in developing countries is also different than developed countries. The goal of this study is to investigate exchange rate channel of monetary transmission mechanism in a developing country’s setup. The variables included in our analysis are interest rate, exchange rate, exports, consumer price index and gross domestic product. Johansen cointegration technique is applied to analyze the long run relationship among variables while multivariate VECM granger causality test is used to explore the direction of causality among the set of our variables. We use annual data ranging from 1980 to 2015 while taking account of the limitations of time series data. Our findings suggest that output has a negative long run relationship with exchange rate and interest rate, positive relationship with exports and no statistically significant relationship with inflation. Interest rate granger causes all four of our variables thus showing the power of this policy tool. Exchange rate causes exports, consumer price index and output which means exchange rate is the second most powerful variable in our analysis. Output is granger caused by interest rate, exports and exchange rate which confirms the sensitivity of output to these variables. Consumer price index is granger caused by all four of our variables and came out to be the most sensitive variable in our analysis.
This paper analysed the forecasting ability of yield-curve as a predictor of the short-run fluctuations in economic activities in Namibia. The study employed the techniques of unit root, cointegration, impulse response functions and forecast error variance decomposition on the quarterly data covering the period 1996 to 2015. The results revealed a negative relationship between the term structure of interest rates and economic activities, though statistically insignificant. This suggests that the yield-curve has no forecasting ability as a predictor of economic activity in Namibia.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This paper provides a review of the empirical macroeconomic model (EMMA) built for forecasting purposes at the Finnish Labour Institute for Economic Research. The model is quite small, consisting of 71 endogenous and 70 exogenous variables. The number of behavioural equations is 15. The basis of the model is Keynesian, although the model has some novel properties. They are the treatment of the supply side and prices that follow the routes of the neoclassical synthesis. The parameters of the model are estimated from quarterly data that cover the years 1990–2005. The model also contains a Kalman-filtered variable to control the deep recession in Finland at the beginning of the ’90s. This special feature brings the model closer to the new calibrated models.
The identification of a possible European business cycle has been inconclusive and is complicated by the enlargement to the new member states and their transition to market economies. This paper shows how to decompose a business cycle into a time-frequency framework in a way that allows us to accommodate structural breaks and nonstationary variables. To illustrate, calculations of the growth rate spectrum and coherences for the Hungarian, Polish, German and French economies show the instability of the transition period. However, since then there has been convergence on the Eurozone economy at short cycle lengths, but little convergence in long cycles. We argue that this shows evidence of nominal convergence, but little real convergence. The Maastricht criteria for membership of the Euro therefore need to be adapted to test for real convergence.
Authored by: Andrew Hughes Hallett, Christian R. Richter
Published in 2007
This article seeks to examine the impact of the Bangladesh’s stock market development on its economic growth from the period of 1989-2012. We have used Johansen Cointegration test to estimate the long-run equilibrium relationship between the variables and the Granger causality test was conducted in order to establish causal relationship, while the model was estimated using the error correction model (ECM). Johansen co-integration test results show that the Bangladesh’s stock market development and economic growth are co-integrated. This indicates that a long run relationship exists between stock market development and economic growth in Bangladesh. The causality test results suggest a unidirectional causality from stock market development to the economic growth. On the other hand, there is no “reverse causation” from economic growth to stock market development. The evidence from this study reveals that the activities in the stock market tend to impact positively on the economy. It is recommended therefore that stock market regulatory authority should therefore address policy issues that are capable of boosting the investors’ confidence through improved policy formulation and creation of awareness.
Forecasting the Exchange Rates of the Iraqi Dinar against the US Dollar using...Dr. Amarjeet Singh
Estimating the exchange rate is considered a key
tool for economic planning and reaching economic stability.
This study aims to reach the best model for predicting
exchange rates of Iraqi Dinar against the U.S. dollar in the
period (2008-2017). For this purpose the following methods
have been adopted: - Time-series analysis using the Box –
Jenkins approach.
Forecasts obtained from the two models were
compared using both mean of the absolute values of the errors
(MAE) and the square root of the mean square error (RMSE).
The ARIMA (1,1,1) model produced the best forecasts and it
can be used as a reliable method of estimating the exchange
rate of any foreign currency.
This paper empirically examines the role of uncertainty occurred by ‘news’ in Japanese financial markets. A GARCH-MIDAS model is used for estimation. It finds that news-based implied volatility performs well in predicting long-term aggregate market volatilities. A subsample analysis provides that the predictive power of news-based volatility is continuing, as most of the coefficients are positive and significant. So, in general, the news based implied volatility model is associated with high market volatility. Moreover, stock market prices go on rising, different effects that appeared in each subsample period. On the recent period, when Abenomics was conducted, the effect decreased. Also, the effect of exchange rates decrease in short time. When stock prices decrease, volatilities of the stock prices in the past period increase. There is some possibility that markets were too unstable about the movements because of the low prices. Also, the volatility of long-term interest rates increases when the interest rate declines in the recent period under Abenomics. Although interest rates have been quite low in both sample periods, the Bank of Japan (BOJ) started to manage long-term interest rates in the recent period, so market participants seem to begin noticing the movements.
The paper proposes two econometric models of inflation for Azerbaijan: one based on monthly data and eclectic, another based on quarterly data and takes into account disequilibrium at the money market. Inflation regression based on monthly data showed that consumer prices dynamics is explained by money growth (the more money, the higher the inflation), exchange rate behaviour (appreciation drives disinflation), commodities price dynamics (“imported” inflation) and administrative changes in regulated prices. For the quarterly model, nominal money demand equation (with inflation, real non-oil GDP and nominal interest rate on foreign currency deposits as predictors) and money supply equation were estimated, and error-correction mechanism from money demand equation was included into inflation equation. It is shown that disequilibrium at the money market (supply higher than demand) drives inflation together with money supply growth and nominal exchange rate depreciation and administrative changes in prices. No cost-push variables appeared to be significant in this equation specification. Both models give similar inflation projections, but sudden changes in money demand (2012) lead to significant differences between the projections. It is shown that money is the most important inflation determinant that explains up to 97.8% of CPI growth between 2012 and 2015, and that in order to keep inflation under control the Central Bank of Azerbaijan should link money supply to real non-oil GDP growth.
Authored by: Alexander Chubrik, Przemyslaw Wozniak, Gulnar Hajiyeva
Published in 2012
Developing economies are different than developed economies in many aspects, i.e., in terms of institutional framework and political situation etc. Thus, the monetary policy needed in developing countries is also different than developed countries. The goal of this study is to investigate exchange rate channel of monetary transmission mechanism in a developing country’s setup. The variables included in our analysis are interest rate, exchange rate, exports, consumer price index and gross domestic product. Johansen cointegration technique is applied to analyze the long run relationship among variables while multivariate VECM granger causality test is used to explore the direction of causality among the set of our variables. We use annual data ranging from 1980 to 2015 while taking account of the limitations of time series data. Our findings suggest that output has a negative long run relationship with exchange rate and interest rate, positive relationship with exports and no statistically significant relationship with inflation. Interest rate granger causes all four of our variables thus showing the power of this policy tool. Exchange rate causes exports, consumer price index and output which means exchange rate is the second most powerful variable in our analysis. Output is granger caused by interest rate, exports and exchange rate which confirms the sensitivity of output to these variables. Consumer price index is granger caused by all four of our variables and came out to be the most sensitive variable in our analysis.
This paper analysed the forecasting ability of yield-curve as a predictor of the short-run fluctuations in economic activities in Namibia. The study employed the techniques of unit root, cointegration, impulse response functions and forecast error variance decomposition on the quarterly data covering the period 1996 to 2015. The results revealed a negative relationship between the term structure of interest rates and economic activities, though statistically insignificant. This suggests that the yield-curve has no forecasting ability as a predictor of economic activity in Namibia.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The theoretical relationship of the long-run equilibrium between real exchange rates and interest rate differentials is essentially derived from the Purchasing Power Parity (PPP) and the uncovered interest parity. However, empirical evidence on this long-run relationship has rather been inconclusive. While several authors are able to establish the long-run relationship between real exchange rates and interest rate differentials other could not found this relationship. The reason for lack of relationship in some of the studies is as a result of omitted variables (Meese and Rogoff, 1988). Therefore, attempt is made in this study to evaluate this relationship between real exchange rate and interest rate differential for the case of Nigeria by controlling for foreign exchange reserves. The paper uses monthly data for the period 1993:1-2012:12 and applies Autoregressive Distributed Lags (ARDL) model. The estimates suggest the existence of long-run relationship between real exchange rate, interest rate differential and foreign exchange reserves. In the long run, the exchange rate coefficient has a positive effect on the foreign reserves. However, the effect of interest rate differential is negative and statistically significant. On the short run dynamics, the finding indicates a non-monotonic relationship between real exchange rate, interest rate differential and foreign exchange reserves. The out-of-sample forecast indicates a better forecast using ARMA model as all Theil coefficients are close zero for all the horizons used in the model.
The study gauged the influence of exchange rate fluctuations on the Performance of the Nigerian Economy over the time from of 1986 to 2016, utilizing secondary data tracked from the statistical report of the Apex Nigerian bank, and utilizing techniques such as Unit root test, Generalized autoregressive conditional heteroscedasticity (GARCH), Impulse-Response Output and Variance-Decomposition Test to evaluate variables such as Interest rate, inflation rate, exchange rate against a sole indicator of Economic Performance I.e. Gross Domestic Product Growth rate (GDPGR), it was discovered that despite the short run influx of the spill over volatility of Interest rate and inflation rate, there exist no long run volatility influence of interest rate on Economic Performance in Nigeria. It was therefore recommended that the apex financial institution and relevant policy makers should ensure an interest rate system and status that could stimulate growth or production and the nation should endeavour to utilize her interest rate in controlling its output level as it motivates Economic Performance (GDPGR).
This paper uses NIESR’s global econometric model, NiGEM, to analyse possible adjustment paths for the US current account, if its current level of 6 per cent of GDP proves unsustainable. Nominal exchange rate shifts have only a transitory impact on current account balances, so any long-term improvement of the US current account balance would require a real and sustained reduction in domestic absorption, or a rise in foreign absorption. This could be effected through a sequence of exchange rate movements driven by a gradual rise in the risk premium on US assets. This would induce a permanent change in the real exchange rate, and would also reduce domestic absorption in the US due to a rise in real interest rates. Global policy coordination, which involved raising domestic demand in countries such as China and Japan, could speed the process of adjustment and ease the negative impact on the US economy.
Authored by: Ray Barrell, Dawn Holland, Ian Hurst
Published in 2007
After the fall of Bretton Woods System, exchange rates become the focus of researchers and politicians. When a floating exchange rate system was started researchers investigated the impact of exchange rate volatility on international trade but the development of derivative instruments changed the researchers focus from currency volatility towards the impact of currency appreciation or depreciation on international trade. The main objective of this research was to investigate the short run and long run relationship between Turkey’s merchandise trade deficit and real effective exchange rate. The monthly data was collected from Central Bank of Republic of Turkey from March 2005 to September 2017. Autoregressive distributed lag (ARDL) approach and Error correction model (ECM) was used for the analysis. The finding shows that the variables have long run relationship but it is not significant at 5% significance level. The short run model also shows the insignificant results. These findings have the following policy implication: Turkey cannot improve the merchandise trade deficit by devaluating its currency.
Foreign capital flows depends on the prevailing monetary forces as supported by capital flows
theory and the mechanism linking these two variables is that contraction of net domestic assets through an
open market sale of bonds will place upward pressure on domestic interest rates. Higher interest rates attract
foreign funds, generating a capital inflow which relieves the pressure on domestic interest rates. Has this
actually happened? It is against this backdrop that the present study investigated the impact of monetary policy
on international capital inflows in Nigeria for a period of 22 years (1994-2015) using time series data. The
autoregressive distributed lag technique revealed that the short-run and long-run significant determinants of
foreign capital inflows are largely from broad money supply, nominal exchange rate, inflation rate and interest
rates spread except inflation rate that is insignificant in the long-run. This outcome upholds theoretical
prediction. Long-run equilibrium relationship was found between the dependent variable and the regressors.
Further examination of the short run dynamics of the model showed that the speed of adjustment coefficients
ECM (-1) to restore equilibrium have a negative sign and statistically significant at 1% level, ensuring that
long-run equilibrium can be attained and about 89% of the short-run deviation from the equilibrium (long-run)
position is corrected annually to maintain the equilibrium. Since the empirical evidence revealed that monetary
aggregates such as broad money supply, nominal exchange rate, inflation rate and interest rates spread
influence foreign capital inflows, it is therefore recommended that government should continue to pursue
expansionary monetary policy and foreign exchange policies that would ensure competitiveness of the
economy in order to attract the much needed foreign capital inflows that would engender economic growth.
This paper investigates the extent of macroeconomic volatility caused by the transfer pricing behavior of multinational corporations. The study examined two possible transmission channels through which transfer pricing causes macroeconomic volatility, namely, terms of trade and budget policy channels. Using the EGARCH model with annual data on selected variables from 1980 to 2017, the paper found evidence of macroeconomic volatility caused by transfer pricing. The size of the shock from transfer pricing is high and statistically significant in the terms of trade and budget policy channels. Negative shock from multinational corporations shifting taxable income between high and low tax regimes had a larger effect than a positive shock on the country’s budget policy. The volatility caused by transfer pricing was short-lived in the terms of trade channel. However, in the budget policy channel, past volatility of transfer pricing persisted for a longer period to explain current volatility.
International Journal of Humanities and Social Science Invention (IJHSSI)inventionjournals
International Journal of Humanities and Social Science Invention (IJHSSI) is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This study investigated a pertinent question on the lips of every Nigerian; exchange rate regime, Quo Vadis Nigeria? Nigeria, Quo Vadis (where do we go)? under two alternative managed floating regimes; Dutch Auction System and post Dutch Auction System regimes, within the Autoregressive Distributive Lag methodology using monthly data covering from July 2002 to July 2017. The results for the full sample show that none of the selected macroeconomic variables has a significant short run relationship with the nominal effective exchange rate. In the long run, all the variables, except interbank rate, show negative relationship with nominal effective exchange rate. However, while the effects of oil prices, interbank rate and the prime lending rate are significant, the effects of inflation and stock prices are insignificant. The results for the Dutch Auction System sample show little evidence of a negative short run relationship between nominal effective exchange rate and inflation while oil prices, prime lending rate, interbank rate and stock prices all show no evidence of a short run relationship with exchange rate. On the contrary, oil prices, prime lending rates and stock prices all show significant negative long run relationship with nominal effective exchange rate. The results for the post Dutch Auction System sample show evidence of a positive short run relationship between stock prices, interbank rate and nominal effective exchange rate. On the other hand, inflation, oil prices and prime lending rate show no short run relationship nominal effective exchange rate. However, there is evidence of a lagged positive relationship between inflation and nominal exchange rate. The cointegration test for post Dutch Auction System sample gives inconclusive results. We therefore, conclude that the choice of exchange rate regime matters for macroeconomics performance in Nigeria and that the closure of the Dutch Auction system by the monetary authorities significantly altered the relationship between nominal exchange effective exchange rate and macroeconomic variables.
To analyze the factors affecting the price volatility of stocks, microeconomic and macroeco-nomic elements must be considered. This paper selects elements that are appropriate with the daily data of stock prices to build the GARCH family models. External variables such as global oil prices, consumer price index, short interest rates and the exchange rate between the United States Dollar and the Euro are examined. The GARCH models are developed in order to analyze and forecast the stock price of the companies in the DAX 30, which is Germany’s most important stock exchange barometer. The volatility of the residual of the mean function is the important key point in the GARCH approach. This financial application can be extend-ed to analyze other specific shares or stock indexes in any stock market in the world. There-fore, it is necessary to understand the operating procedures of their pricing for risk manage-ment, profitability strategies, cost minimization and, in addition, to construct the optimal port-folio depending on investor’s preferences.
The output gap indicating the difference between the actual and potential levels of output is a critical factor for estimating the inflationary pressures in an economy. If the main target of a central bank is ensuring and maintaining the price stability, estimating the output gap with a minimum error is crucial for the efficiency of the monetary policy. In this study, we estimated the output gap in Turkey for the 2002-2014 period by using four different methods. Two of these estimation methods are purely statistical (Linear Trend and Hodrick-Presscot (HP) Filtering) while the others are integrated with the relations suggested by the economic theory (multivariate structural model and structural autoregressive (SVAR) model). By using empirical decision criteria common in the literature, we conclude that SVAR model produces the most reliable output gap estimates to explain inflationary pressures in Turkey. However, we also found that the Hodrick-Presscot filtering method is the second best methodology in the output gap estimation process.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
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Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
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1. International Journal of Mathematics and Statistics Invention (IJMSI)
E-ISSN: 2321 – 4767 P-ISSN: 2321 - 4759
www.ijmsi.org Volume 2 Issue 6 || June. 2014 || PP-52-65
www.ijmsi.org 52 | P a g e
Exchange rate volatility of Nigerian Naira against some major
currencies in the world: An application of multivariate GARCH
models
1,
Tasi’u Musa , 2,
Yakubu Musa , and 3,
Gulumbe S. U.
1,2,
Statistics Unit, Department of Mathematics, Usmanu Danfodiyo University, Sokoto, Nigeria
3,
Department of Mathematics, Statistics Unit, Usmanu Danfodiyo University, Sokoto, Nigeria.
ABSTRACT : Exchange rates are important financial problem that is receiving attention globally. This study
uses daily data over the period January, 1999 to February, 2014 consisting of 3950 observations. The study is
aimed to determine the volatility spillover of the nine selected countries against the U.S. Dollar simultaneously
via Multivariate GARCH models. And hence, to observe some stylize facts/common features of good volatility
modeling on financial time series. To achieve the stated objectives, we employed three multivariate volatility
models: DVECH, BEKK and CCC and the result indicated that the restricted BEKK, DVECH and CCC results
exhibit rather similar behavior for each considering countries. The result also indicated that the skewness is
greater than zero, that is to say the distribution is positively skewed which is an indication of a non symmetric
series, meaning that there is an asymmetric effects in these models. The kurtosis is also greater than 3;
relatively large kurtosis suggests that the distribution of the exchange rate return series is leptokurtic which is
another stylize fact. Conclusively, base on information criteria, the DVECH model is found to be the best model.
But according to parsimonious principle, the BEKK model is considered to be the best because it has least
number of parameters.
KEYWORDS:MULTIVARIATE GARCH, Exchange rate, Volatility
I. INTRODUCTION
The volatility of exchange rate returns is one of the central variables in mainstream financial
economics. In fact, much empirical work has been done in this area. Many authors are convinced that exchange
rate returns are in large part predictable, but only over the long term (in less than a five-year period, the
predictions seem less reliable). Fama and French (1988, 1993, 1996), among others prominent and well-known
researchers, demonstrated empirically that a few economic factors can explain the variability of returns.
Consequently, with this knowledge, we can forecast the expected exchange rate returns quite well.
Understanding the volatility of the exchange rate means having indirect knowledge of the distribution of the
returns if they are normally distributed (Gaussian) because for this distribution, we need only the two first
moments. If we know the distribution or the variability of returns, then we can forecast with higher accuracy the
returns themselves. But more than one question arises here: (1) Do we really know the volatility of exchange
rates? (2) Is it this constant over time or stochastic? (3) Are the daily or monthly exchange rates really normally
distributed? But if we are unable to answer these questions with precision, can we postulate that the exchange
rate returns are predictable? In fact, if you find a model that explains something accurately, then you can be
certain that this will forecast, with small probability of failure, the true future (expected) return. Volatilities and
correlations are the two most important elements in asset pricing, portfolio management and risk assessment.
Since the seminal 1982 paper of Engel’s autoregressive conditional heteroskedasticity (ARCH) model, lots of
efforts have been spent on univariate volatility modeling. Most famous one among them is the Bollerslov’s
generalized ARCH (GARCH) model. As time goes by and computing power improves, researchers find it more
and more important and necessary to generalize the univariate ARCH/GARCH models to their multivariate
versions. This will continue to be the trend thereafter. (Xiaojun Song, 2009).
One of the central aspects in financial econometrics is the modeling, measuring and forecasting of
second and possible higher moments, because the volatility for instance is not directly observable. One of the
most important models for volatility is the class of multivariate generalized autoregressive conditional
heteroscedasticity (MGARCH) models. They allow us to specify a dynamic process for the whole time varying
variance–covariance matrix of the time series thus jointly modeling the first and second moments. The main
applications of MGARCH models are in portfolio management, hedging, analysis of volatility spillovers across
markets, option pricing and Value–at–Risk (VaR) of portfolios.
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Since correlations between asset returns and markets are important in many financial applications,
multivariate volatility models have also been extended to describe the time–varying feature of the correlations in
recent years.The univariate GARCH framework was developed by Bollerslev (1986), based on the ARCH
models by Engle (1982). Engle proposed a function for the conditional variance of the time series that depends
on the realized error of the period before. (Xiaojun Song, 2009).Analogous to the expansion from the AR
models to ARMA models, Bollerslev developed the GARCH model by taking the own history of the volatility
into account. But in this framework the restrictions to univariate time series doesn’t take the volatility spillover
into account. The possibility of interaction between one or more time series is completely excluded. Therefore
Bollerslev, Engle and Wooldridge (1988) proposed the basic framework for the multivariate GARCH model by
including additional parameters in order to capture this effect. Many expansions to the basic MGARCH models
have therefore been developed. Based on the recent theoretical and empirical developments and discoveries in
MGARCH models, this paper focuses on the investigation of volatilities and correlations of some selected
currencies in the world, these are Nigerian Naira, Euro, Great Britain Pound (GBP), Singapore Dollars, South
African Rand, Malaysian Ringgit, Japanese Yen, Chinese Yuan and Canadian Dollars. Now, let’s give some
shorts overviews on the economic standard of the countries of eight selected currencies plus the Euro for simple
comparison.
Nigeria is a middle income, mixed economy and emerging market, with expanding financial, service,
communications and technology and entertainment sectors. It is ranked 26th in the world in terms of GDP
(nominal: 30th in 2013 before rebasing, 40th in 2005, 52nd in 2000), and is the largest economy in Africa
(based on rebased figures announced in April 2014). It is also on track to become one of the 20 largest
economies in the world by 2020. Its re-emergent, though currently underperforming, manufacturing sector is the
third-largest on the continent, and produces a large proportion of goods and services for the West African
region. Previously hindered by years of mismanagement, economic reforms of the past decade have put Nigeria
back on track towards achieving its full economic potential. Nigerian GDP at purchasing power parity (PPP) has
almost tripled from $170 billion in 2000 to $451 billion in 2012, although estimates of the size of the informal
sector (which is not included in official figures) put the actual numbers closer to $630 billion. Correspondingly,
the GDP per capita doubled from $1400 per person in 2000 to an estimated $2,800 per person in 2012 (again,
with the inclusion of the informal sector, it is estimated that GDP per capita hovers around $3,900 per person).
(Population increased from 120 million in 2000 to 160 million in 2010). These figures are to be revised upwards
by as much as 80% when metrics are recalculated subsequent to the rebasing of its economy in April 2014.
(Anon., 2014).
Although much has been made of its status as a major exporter of oil, Nigeria produces only about
2.7% of the world's supply (Saudi Arabia: 12.9%, Russia: 12.7%, USA:8.6%). To put oil revenues in
perspective: at an estimated export rate of 1.9 Mbbl/d (300,000 m3
/d), with a projected sales price of $65 per
barrel in 2011, Nigeria's anticipated revenue from petroleum is about $52.2 billion (2012 GDP: $451 billion).
This accounts about 11% of official GDP figures (and drops to 8% when the informal economy is included in
these calculations). Therefore, though the petroleum sector is important, it remains in fact a small part of the
country's overall vibrant and diversified economy. (Anon.,2014).
In 1986, Nigeria adopted the structural adjustment programme (SAP) of the IMF/World Bank. With the
adoption of SAP in 1986, there was a radical shift from inward-oriented trade policies to out ward –oriented
trade policies in Nigeria. These are policy measures that emphasize production and trade along the lines dictated
by a country’s comparative advantage such as export promotion and export diversification, reduction or
elimination of import tariffs, and the adoption of market-determined exchange rates. Some of the aims of the
structural adjustment programme adopted in 1986 were diversification of the structure of exports, diversification
of the structure of production, reduction in the over-dependence on imports, and reduction in the over-
dependence on petroleum exports. The major policy measures of the SAP were:
[1] Deregulation of the exchange rate
[2] Trade liberalization
[3] Deregulation of the financial sector
[4] Adoption of appropriate pricing policies especially for petroleum products
[5] Rationalization and privatization of public sector enterprises and
[6] Abolition of commodity marketing boards. (Onasanya et al, 2013)
The economy of South Africa is the second largest in Africa behind Nigeria, it accounts for 24% of its gross
domestic product in terms of purchasing power parity, and is ranked as an upper-middle income economy by the
World Bank; this makes the country one of only four countries in Africa in this category (the others being
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Botswana, Gabon and Mauritius). Since 1996, at the end of over twelve years of international sanctions, South
Africa's Gross Domestic Product has since almost tripled to $400 billion, and foreign exchange reserves have
increased from $3 billion to nearly $50 billion; creating a growing and sizable African middle class, within two
decades of establishing democracy and ending apartheid. According to official estimates, a quarter of the
population is unemployed, According to a 2013 Goldman Sachs report, that number increases to 35% when
including people who have given up looking for work. A quarter of South Africans live on less than US $1.25 a
day. South Africa has a comparative advantage in the production of agriculture, mining and manufacturing
products relating to these sectors. South Africa has shifted from a primary and secondary economy in the mid-
twentieth century to an economy driven primarily by the tertiary sector in the present day which accounts for an
estimated 65% of GDP or $230 billion in nominal GDP terms. The country's economy is reasonably diversified
with key economic sectors including mining, agriculture and fisheries, vehicle manufacturing and assembly,
food processing, clothing and textiles, telecommunication, energy, financial and business services, real estate,
tourism, transportation, and wholesale and retail trade.
The unemployment rate is very high, at more than 25%, and the poor have limited access to economic
opportunities and basic services. Poverty also remains a major problem. In 2002, according to one estimate,
62% of Black Africans, 29% of Coloureds, 11% of Asians, and 4% of Whites lived in poverty. The high levels
of unemployment and inequality are considered by the government and most South Africans to be the most
salient economic problems facing the country. These issues, and others linked to them such as crime, have in
turn hurt investment and growth, consequently having a negative feedback effect on employment. Crime is
considered a major or very severe constraint on investment by 30% of enterprises in South Africa, putting crime
among the four most frequently mentioned constraints. (Anon.,2014).
The socialist market economy of China is the world's second largest economy by nominal GDP and by
purchasing power parity after the United States. It is the world's fastest-growing major economy, with growth
rates averaging 10% over the past 30 years. China is also the largest exporter and second largest importer of
goods in the world. China is the largest manufacturing economy in the world, outpacing its world rival in this
category, the service-driven economy of the United States of America. ASEAN–China Free Trade Area came
into effect on 1 January 2010. China-Switzerland FTA is China's first FTA with a major European economy,
while China–Pakistan Free Trade Agreement came in effect in 2007 is the first FTA signed with a South Asian
state. The
economy of China is the fastest growing consumer market in the world. On a per capita income basis, China
ranked 87th by nominal GDP and 92nd by GDP (PPP) in 2012, according to the International Monetary Fund
(IMF). The provinces in the coastal regions of China tend to be more industrialized, while regions in the
hinterland are less developed. As China's economic importance has grown, so has attention to the structure and
health of the economy. Xi Jinping’s Chinese Dream is described as achieving the “Two 100s”: the material goal
of China becoming a “moderately well-off society” by 2021, the 100th anniversary of the Chinese Communist
Party, and the modernization goal of China becoming a fully developed nation by 2049, the 100th anniversary of
the founding of the People’s Republic.
The internationalization of the Chinese economy continues to affect the standardized economic forecast
officially launched in China by the Purchasing Managers Index in 2005. At the start of the 2010s, China
remained the sole Asian nation to have an economy above the $10-trillion mark (along with the United States
and the European Union). Most of China's economic growth is created from Special Economic Zones of the
People's Republic of China that spread successful economic experiences to other areas. The development
progress of China's infrastructure is documented in a 2009 report by KPMG. (Anon.,2014).
The United Kingdom has the 6th-largest national economy in the world (and 3rd-largest in Europe) measured
by nominal GDP and 8th-largest in the world (and 2nd-largest in Europe) measured by purchasing power parity
(PPP). The UK's GDP per capita is the 22nd-highest in the world in nominal terms and 22nd-highest measured
by PPP. In 2012, the UK was the 10th-largest exporter in the world and the 6th-largest importer. In 2012, the
UK had the 3rd-largest stock of inward foreign direct investment and the 2nd-largest stock of outward foreign
direct investment. The British economy comprises (in descending order of size) the economies of England,
Scotland, Wales and Northern Ireland. The UK has one of the world's most globalised economies. One-sixth of
the tax revenue comes from VAT (value added tax) from the consumer market of the British Economy.The
service sector dominates the UK economy, contributing around 78% of GDP, with the financial services
industry particularly important. London is the world's largest financial centre and has the largest city GDP in
Europe.
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The UK aerospace industry is the second- or third-largest national aerospace industry depending on the
method of measurement. The pharmaceutical industry plays an important role in the economy and the UK has
the third-highest share of global pharmaceutical R&D. The automotive industry is also a major employer and
exporter. The British economy is boosted by North Sea oil and gas production; its reserves were valued at an
estimated £250 billion in 2007. There are significant regional variations in prosperity, with the South East of
England and southern Scotland the richest areas per capita. (Anon.,2014).
The economy of Japan is the third largest in the world by nominal GDP, the fourth largest by purchasing power
parity and is the world's second largest developed economy. According to the International Monetary Fund, the
country's per capita GDP (PPP) was at $35,855 or the 22nd highest in 2012. Japan is a member of Group of
Eight. The Japanese economy is forecasted by the Quarterly Tankan survey of business sentiment conducted by
the Bank of Japan.Japan is the world's third largest automobile manufacturing country, has the largest
electronics goods industry, and is often ranked among the world's most innovative countries leading several
measures of global patent filings. Facing increasing competition from China and South Korea, manufacturing in
Japan today now focuses primarily on high-tech and precision goods, such as optical instruments, Hybrid
vehicles, and robotics. Beside the Kantō region, the Kansai region is one the leading industrial clusters and the
manufacturing center for the Japanese economy. Japan is the world's largest creditor nation, generally running
an annual trade surplus and having a considerable net international investment surplus. As of 2010, Japan
possesses 13.7% of the world's private financial assets (the 2nd largest in the world) at an estimated $14.6
trillion. As of 2013, 62 of the Fortune Global 500 companies are based in Japan. (Anon.,2014).
Canada has the eleventh or 14th-largest economy in the world (measured in US dollars at market exchange
rates), is one of the world's wealthiest nations, and is a member of the Organization for Economic Co-operation
and Development (OECD) and Group of Seven (G7). As with other developed nations, the Canadian economy
is dominated by the service industry, which employs about three quarters of Canadians. Canada is unusual
among developed countries in the importance of the primary sector, with the logging and oil industries being
two of Canada's most important. Canada also has a sizable manufacturing sector, centred in Central Canada,
with the automobile industry and aircraft industry especially important. With a long coastal line, Canada has the
8th largest commercial fishing and seafood industry in the world. Canada is one of the global leaders of the
entertainment software industry. (Anon.,2014).
Singapore is a highly developed trade-oriented market economy. Singapore's economy has been ranked as the
most open in the world, least corrupt, most pro-business, with low tax rates (14.2% of Gross Domestic Product,
GDP) and has the third highest per-capita GDP in the world; in terms of Purchasing Power Parity (PPP).
Government-linked companies play a substantial role in Singapore's economy, which are owned through the
sovereign wealth fund Temasek Holdings, which holds majority stakes in several of the nation's largest
companies, such as Singapore Airlines, SingTel, ST Engineering and Media Corp. The economy of Singapore is
a major Foreign Direct Investment (FDI) outflow financier in the world. Singapore has also benefited from the
inward flow of FDI from global investors and institutions due to her highly attractive investment climate and a
stable political environment.Exports, particularly in electronics, chemicals and services including the posture
that Singapore is the regional hub for wealth management provide the main source of revenue for the economy,
which allows it to purchase natural resources and raw goods which she lacks. Moreover, water is scarce in
Singapore therefore water is defined as a precious resource in Singapore along with the scarcity of land to be
treated with land fill of Pulau Semakau. Singapore has limited arable land that Singapore has to rely on the
agrotechnology park for agricultural production and consumption. Human Resource is another vital issue for the
health of Singaporean economy. Singapore could thus be said to rely on an extended concept of intermediary
trade to Entrepôt trade, by purchasing raw goods and refining them for re-export, such as in the wafer
fabrication industry and oil refining. Singapore also has a strategic port which makes it more competitive than
many of its neighbours in carrying out such entrepot activities. Singapore has the highest trade to GDP ratio in
the world, averaging around 400% during 2008–11.The Port of Singapore is the second-busiest in the world by
cargo tonnage. In addition, Singapore's port infrastructure and skilled workforce, which is due to the success of
the country's education policy in producing skilled workers, is also fundamental in this aspect as they provide
easier access to markets for both importing and exporting, and also provide the skill(s) needed to refine imports
into exports. (Anon.,2014).
Malaysia has a newly industrialised market economy, which is relatively open and state-oriented. The state
plays a significant, but declining role in guiding economic activity through macroeconomic plans. In 2012, the
economy of Malaysia was the third largest economy in South East Asia behind more populous Indonesia and
Thailand and 29th largest economy in the world by purchasing power parity with gross domestic product stands
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at US$492.4 billion and per capita US$16,922. In 2010, GDP per capita (PPP) of Malaysia stood at US$14,700.
In 2009, the PPP GDP was US$383.6 billion, and the PPP per capita GDP was US$8,100.The Southeast Asian
country experienced an economic boom and underwent rapid development during the late 20th century and has
GDP per capita of $17,200 today, to be considered a newly industrialized country. On the income distribution,
there are 5.8 million households in 2007. Of that, 8.6% have a monthly income below RM1,000, 29.4% had
between RM1,000 and RM2,000, while 19.8% earned between RM2,001 and RM3,000; 12.9% of the
households earned between RM3,001 and RM4,000 and 8.6% between RM4,001 and RM5,000. Finally, around
15.8% of the households have an income of between RM5,001 and RM10,000 and 4.9% have an income of
RM10,000 and above. As one of three countries that control the Strait of Malacca, international trade plays a
large role in its economy. At one time, it was the largest producer of tin, rubber and palm oil in the world.
Manufacturing has a large influence in the country's economy. Malaysia is the world's largest Islamic banking
and financial centre. (Anon.,2014).
The euro is the official currency of Germany, which is a member of the European Union. The Euro
Area refers to a currency union among the European Union member states that have adopted the euro as their
sole currency. In Germany, interest rate decisions are taken by the Governing Council of the European Central
Bank (ECB).On January 1, 1999 Euro became the currency for 11 member states of the European Union (the
countries were Belgium, Germany, Spain, France, Ireland, Italy, Luxembourg, the Netherlands, Austria,
Portugal and Finland). Since then the Dollar-Euro exchange rate has completed a full turning. Euro depreciated
since its introduction steadily and without any major interruption until February 2002. Then it began to rise
against Dollar smoothly and reached a height of 0.74 Euros to 1 US$ in December 2004. Three years of
depreciation of the Euro followed by three years of appreciation without wild fluctuations asks for an
explanation which would adequately account for the position of the Euro as an emerging international currency.
Theories of the exchange rate which are based on interest rate and price differentials or revisions of expectations
causing short term capital movements cannot provide for such an explanation. Since both, Dollar and Euro are
international currencies we apply the theory of world money to explain the steep downward and upward
movement of Euro against Dollar in the period 1999 to 2014 together with eight major currencies in the world
(i. e. Nigerian Naira, Great Britain Pound (GBP), Singapore Dollars, South African Rand, Malaysian Ringgit,
Japanese Yen, Chinese Yuan and Canadian Dollars). (Rasul S., 2004).
II. LITERATURE REVIEW
Many studies provide evidence that correlation is evolving through time. Longin and Solnik (1995)
showed that correlation in international equity returns across 1960–1990 is highly volatile. Engle (2002) verified
the important evidence of time–varying correlation of many classes of assets. Tse and Tsui (2002) applied time–
varying correlation model to exchange rate data, national stock market data and the sectoral price data and
provided the time–varying correlation evidence for the three real datasets. Solnik, Boucrelle, and Le Fur (1996)
found that correlation is increasing in periods of high market volatility for the industrialized countries when risk
diversification is needed most. Campbell, Koedijk and Kofman (2002) showed that market correlations increase
in the bear market. Volatility changes not only due to the dynamic evolution of own market volatility but also
changes of interdependence across markets. Hamao, Masulis, and Ng (1990) examined the combination of
correlations in price changes and volatility across international stock markets. Engle and Susmel (1993) found
that there is common volatility in international equity markets. Bollerslev and Engle (1993) checked the
common persistence effect in the conditional variances, that is, the volatility. Bae and Karolyi (1994) found that
the spillover of stock volatility between Japan and the United States is closely related to goods news or bad
news. Karolyi (1995) used a bivariate GARCH model to investigate the transmission of stock returns and
volatility between the United States and Canada, finding that volatility is transferred from U.S. to Canada most
of the time. See King, Sentana and Wadhwani (1994), Lin, Engle, and Ito (1994) and Ng (2000) for more
evidences of volatility transmission and linkage. Lanza, Manera, and McAleer (2006) and Manera, McAleer,
and Grasso (2006) examined correlation and volatility in the oil forward and future markets. Edwards and
Susmel (2001) and Edwards and Susmel (2003) investigated the volatility dependence and contagion in equity
and interest rate respectively in emerging markets. Balasubramanyan and Premaratne (2003) and
Balasubramanyan (2004) provided the evidence of volatility comovement and spillover from Asian markets.
Yang (2005) used a DCC anaylsis to examine the role of Japan on the Asian Four Tigers, finding that stock
market correlations fluctuate widely over time and volatilities are contagious across markets. Kuper and Lestano
(2007) analyzed the financial market interdependence of Thailand and Indonesia. See Andersen, Bollerslev,
Christoffersen, and Diebold (2005) for a review of volatility and correlation modeling for financial markets.
Little or no work has been done on dollar-Naira exchange rate together with the exchange rates of the major
currencies in the world particularly using Multivariate GARCH family models. The exchange rate volatility has
implications for many issues in the area of finance and economics. Such issues include impact of foreign
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exchange rate volatility on derivative pricing, global trade patterns, countries balance of payments position,
government policy making decisions and international capital budgeting.
III. MATERIALS AND METHODS
Data: We use the daily exchange rates returns of Nigerian Naira together with eight measure currencies in the
world (i. e. Euro, Great Britain Pound (GBP), Singapore Dollars, South African Rand, Malaysian Ringgit,
Japanese Yen, Chinese Yuan and Canadian Dollars). The data covers the period from January 4, 1999 to
February 21, 2014 which consists of 3950 observations obtained from the Federal Reserve Bank of Louis,
U.S.A. The return on exchange rate is defined as:
1
logt
t
t
e
r
e
1
Where et is the exchange rate at time t and et-1 represent exchange rate at time t-1. The rt of equation (1) will be
used in observing the volatility of the exchange rate between the selected currencies over the period 1999-2014.
Multivariate GARCH Representations
The Diagonal VECH Representation :Let’s have a quick glance at the VECH representation before diagonal
VECH for crystal clear. Applying the VECH operator to a symmetric matrix stacks the lower triangular
elements into a column. Since Ht is a symmetric matrix, in specifying the multivariate GARCH model we can
employ the VECH transformation of Ht. consider the following specification:
/
0
1 1
q p
t i t i t i i t i
i i
vech H vech A Avech Bvech H
2
where
/
1 2, ,...,t Ntt t are the error terms associated with the conditional mean equations for 1ty to
Nty , 0A is an N N positive definite matrix of parameters and iA and iB are
1 / 2 1 / 2N N N N
matrices of parameters. In the case two variables 2N
and 1p q , the multivariate GARCH representation given by (2) can be written out in full as:
0 2
1111. 11. 11. 111 12 13 11 12 13
0
12. 12 21 22 23 1. 1 2. 1 21 22 23 12. 1
0 2
31 32 33 31 32 3322. 22. 122 2. 1
t tt
t t t t
t tt
ah ha a a b b b
h a a a a b b b h
a a a b b bh ha
3
where 11.th is the conditional variance of the error associated with 1ty , 22.th is the conditional variance of the
error associated with 2ty and 12.th is the conditional covariance between the errors.
In the diagonal representation (due to Bollerslev, Engle and Woodridge. 1988) iA and iB in (2) are diagonal
matrices. This assumption forces the individual conditional variances to have GARCH (p, q) form and the
covariances to have a GARCH (p, q) form. As an example, consider the diagonal representation of Vech (Ht) in
the case of two variables (N = 2) and p = q = 1:
0 2
1111. 11. 11. 111 11
0
12. 12 22 1. 1 2. 1 22 12. 1
0 2
33 3322. 22. 122 2. 1
0 0 0 0
0 0 0 0
0 0 0 0
t tt
t t t t
t tt
ah ha b
h a a b h
a bh ha
4
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The BEKK Representation
The BEKK representation (due to Baba et al. 1990) assumes the following model for Ht:
* / */ * */
0
1 1
q p
t i t i t i i i t i i
i i
H A A A B H B
5
Where
*
iA and
*
iB are N N matrices of parameters and 0A is defined as before, writing out (5) for
2N and 1p q gives:
20 0 * * * *
1. 1 1. 1 2. 111 12 11 12 11 2111. 12.
20 0 * * * *
21. 22. 1. 1 2. 1 2. 112 22 21 22 12 22
t t tt t
t t t t t
a a a a a ah h
h h a a a a a a
* * * *
11 12 11 2111. 1 12. 1
* * * *
21. 1 22. 121 22 12 22
t t
t t
b b b bh h
h hb b b b
6
The Constant Conditional Correlation Representation
In the past years, a new class of multivariate GARCH models has been developed.
They focus on the parameterization of the conditional correlation matrix. Such models have the flexibility of
univariate GARCH models with respect to the conditional variances. They need simple conditions to ensure the
positive definiteness of Ht and the estimation is much easier than the usual MARCH models. The constant
conditional correlation (CCC) model of Bollerslev (1990) is a fruitful endeavor to explore the MGARCH model
indirectly in the correlation direction instead of modeling the variance covariance matrix Ht directly. CCC
model has several advantages mentioned above. Now we define the structure of the constant conditional
correlation matrix R and the variance covariance matrix Ht as follows:
1
1
1
1
N
N
R
7
where
ij is the correlation coefficient measuring the correlation of variable i with variable j. He then defines
the conditional variance matrix Ht as:
/
t t tH D RD
8
Where
1 2, ,..., .t t t NtD diag
The basic idea is that every variance–covariance matrix can be decomposed in the above way. Therefore, we can
characterize the dynamics in the following way.
2
1 12, 1 ,
2
12, 2 ,2
2
1 , 2 , ...
t t N t
t N tt
t
N t N t Nt
H
9
2 2 2
, , , ,
1 1
q p
it i i j i t j i j i t j
j j
w
1,...,i n
10
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,ij t ij it jt , 1,..., ,i j n i j
11
The usual conditions to ensure the positivity of the variances and the stationarity hold:
, ,0, 0, 0i j i jiw and , ,
1 1
1
q p
i j i j
j j
. The total number of parameters is
1
1
2
N N
p q N
, when 1, 2p q N 7 parameters need to be estimated, which is not so
many but still lack parsimony. Positive definiteness of the variance covariance matrix is controlled by the
correlation matrix, while only the usual requirements of positivity constraints for GARCH model suffice. In
order to obtain the parameters, maximum likelihood estimation method can be used. (Xiaojun Song, 2009)
IV. DATA ANALYSIS:
In this chapter, we shall focus on the analysis of data and econometric interpretation which is typically
the case in financial application. The aim is to examine the volatility spillover (own or cross) of the local
currencies of the selected countries against the U.S dollars simultaneously via MGARCH models. Note that
“Own–volatility spillovers” is used to indicate a one–way causal relationship between past volatility shocks and
current volatility in the same market. “Cross–volatility spillovers” is used to indicate a one–way causal
relationship between past volatility shocks in one market and current volatility in another market. The argument
is straightforward and easily understood as these nine countries have been historically closely interlinked due to
their economic advancements, their popularity in their sub-continents (region) and more importantly the
globalization. The researcher(s) have seldom investigated the nine markets together. We applied log-difference
transformation to convert the data into continuously compounded returns, because the return (log values) of both
currencies is not stationary (see figure 4.1) and are stationary when they are first differenced (see figure 4.2).
Fig 4.1: Graphical Representation of Exchange Rates of the nine selected currencies:
100
110
120
130
140
150
160
00 02 04 06 08 10 12
NAIRA
0.8
1.0
1.2
1.4
1.6
1.8
00 02 04 06 08 10 12
EURO
0
4,000
8,000
12,000
16,000
20,000
00 02 04 06 08 10 12
U.K
6.0
6.5
7.0
7.5
8.0
8.5
00 02 04 06 08 10 12
CHINA
4
6
8
10
12
14
00 02 04 06 08 10 12
S/AFRICA
2.8
3.0
3.2
3.4
3.6
3.8
4.0
00 02 04 06 08 10 12
MALAY SIA
60
80
100
120
140
00 02 04 06 08 10 12
JAPAN
1.0
1.2
1.4
1.6
1.8
2.0
00 02 04 06 08 10 12
SINGAPORE
0.8
1.0
1.2
1.4
1.6
1.8
00 02 04 06 08 10 12
CANADA
Figure 4.1 indicates that all the series are not stationary as they contain a trend components which should be
remove before modeling. These trend components have been taken care of, as explained above which can be
seen in figure 4.2.
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Fig 4.2: Graphical Representation of the First Difference of the Logarithms of Daily Exchange rates of
the nine selected currencies:
-.15
-.10
-.05
.00
.05
.10
.15
00 02 04 06 08 10 12
DLOG(NAIRA) Residuals
-.06
-.04
-.02
.00
.02
.04
.06
00 02 04 06 08 10 12
DLOG(EURO) Residuals
-10
-5
0
5
10
00 02 04 06 08 10 12
DLOG(GBP) Residuals
-.04
-.02
.00
.02
.04
00 02 04 06 08 10 12
DLOG(CHINA) Residuals
-.2
-.1
.0
.1
.2
00 02 04 06 08 10 12
DLOG(S_AFRICA) Residuals
-.10
-.05
.00
.05
.10
00 02 04 06 08 10 12
DLOG(MALAYSIA) Residuals
-.10
-.05
.00
.05
.10
00 02 04 06 08 10 12
DLOG(JAPAN) Residuals
-.03
-.02
-.01
.00
.01
.02
.03
00 02 04 06 08 10 12
DLOG(SINGAPORE) Residuals
-.10
-.05
.00
.05
.10
00 02 04 06 08 10 12
DLOG(CANADA) Residuals
Figure 4.2 shows that some periods are riskier than the others. Also, the risky periods are scattered randomly
and there is some degree of autocorrelation in the riskiness of financial returns (i.e. large changes (of either sign)
tend to be followed by large changes and small changes (of either sign) tend to be followed by small changes,
this is termed as volatility clustering (Mendelbret, 1963) and is one f the stylized facts of volatility of financial
time series. We also observed that the clustering of periods of volatility that is large movements being followed
by further large movements; the variance of exchange rate returns of these countries (with the exception of the
Great Britain) is not constant over time. This is an indication of shock persistence. (International journal of
academic research, 2011) which is another stylized fact of volatility f financial time series.
Autocorrelation Function (ACF):
Having discovered that the exchange rates series could be modeled as MGARCH, the next is to
examine the ACF to see the degree of correlation in the data points of the series. The one with higher degree of
correlation will be the right candidate to model with. We formally confirm the presence of the autocorrelation in
the exchange rates series by Portmanteau test.
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Table 4.1 System Residual Portmanteau Tests for
Autocorrelations
Null Hypothesis: no residual autocorrelations up to lag h
Included observations: 3949
Lags Q-Stat Prob. Adj Q-Stat Prob. df
1 2817.018 0.0000 2817.731 0.0000 81
2 2916.977 0.0000 2917.741 0.0000 162
3 3008.902 0.0000 3009.736 0.0000 243
4 3119.072 0.0000 3120.018 0.0000 324
5 3267.282 0.0000 3268.416 0.0000 405
6 3347.610 0.0000 3348.866 0.0000 486
7 3412.667 0.0000 3414.039 0.0000 567
8 3489.148 0.0000 3490.675 0.0000 648
9 3578.795 0.0000 3580.526 0.0000 729
df is degrees of freedom for (approximate) chi-square distribution
Table 4.1 reveals that the null hypothesis of no autocorrelation can be rejected in all cases. Hence, we concluded
that there are strong autocorrelations in the residuals of the returns.
Jarque Bera Test for Normality:To achieve the overall objective of the research, we examine the
characteristics of the unconditional distribution of the exchange rate. This will enable us to explore and explain
some stylized facts embedded in the financial time series. Jarque Bera normality test is used to demonstrate this
and the results are given in the table below:Note that the Jarque-Bera test is a goodness–of–fit measure of
departure from normality, based on the sample kurtosis and skewness. Under the null hypothesis of normality,
the statistic JB has an asymptotic chi-square distribution with two degrees of freedom.
Table 4.2 System Residual Normality Tests for the Nine Selected Currencies
Null Hypothesis: residuals are multivariate normal
Sample: 1/05/1999 2/21/2014
Included observations: 3949
Component Skewness Chi-sq df
1 0.879085 508.6246 1
2 0.026677 0.468376 1
3 44.88030 1325706. 1
4 7.105127 33226.11 1
5 0.398252 104.3885 1
6 9.862163 64014.78 1
7 0.283621 52.94355 1
8 0.026361 0.457350 1
9 0.429407 121.3596 1
Joint 1423735. 9
Component Kurtosis Chi-sq df
1 17.12798 32842.49 1
2 5.754510 1248.431 1
3 2521.141 1.04E+09 1
4 290.0217 13555179 1
5 8.287359 4599.953 1
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6 309.1061 15417714 1
7 9.123025 6168.904 1
8 9.596338 7159.483 1
9 12.89901 16123.49 1
Joint 1.07E+09 9
Component Jarque-Bera df Prob.
1 33351.11 2 0.0000
2 1248.899 2 0.0000
3 1.04E+09 2 0.0000
4 13588405 2 0.0000
5 4704.342 2 0.0000
6 15481729 2 0.0000
7 6221.848 2 0.0000
8 7159.941 2 0.0000
9 16244.85 2 0.0000
Joint 1.07E+09 18 0.0000
Table 4.2 indicated that the skewness is greater than zero (for the normal distribution), that is to say the
distribution is positively skewed which is an indication of a non symmetric series, meaning that there is an
asymmetric effects in these models (i.e. volatility is higher in a falling market than in a rising market) which is
another stylize fact of financial time series. The kurtosis is also greater than 3 (the kurtosis of a normal
distribution). Recall that; relatively large kurtosis suggests that the distribution of the exchange rate return series
is leptokurtic (i.e. exhibit fat tail) which is another stylize fact. Thereafter, Jarque Bera normality test statistic
indicates that, neither returns series has a normal distribution.
Modeling of restricted BEKK, DVEC and CCC models in Multivariate version
Table 4.3, contains the number coefficients, log‐likelihood and information criteria for multivariate BEKK,
DVECH and CCC models. And the table is given below:
Table 4.3: Summary of the Estimated Parameters of Multivariate BEKK, DVEC and CCC models
BEKK DVECH CCC
No. of
C
o
e
f
f
i
c
i
e
n
t
s
Log likelihood
Avg. log
l
i
k
e
l
36
134658.4
3.788819
-68.18051
-68.12325
-68.16020
144
134779.9
3.792238
-68.18735
-67.95831
-68.10611
72
134572.7
3.786406
-68.11884
-68.00432
-68.07822
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i
h
o
o
d
AIC
SIC
HIC
We can observe (from table 4.3) that base on information criteria, the DVECH model despite its estimation
complexity due to large number of parameters needed to be estimated is found to be the best model because it
has maximum likelihood, lower AIC and BIC. Following the DVECH model is the BEKK model with only 36
parameters. But according to parsimonious principle (Robert E. (1984)) the BEKK model is regarded as the best
model because it has least number of parameters.
Now the next thing to do is to examine the correlations between the residuals (variances) of these models. These
correlations have been explored in the table below:
Table 4.4 conditional correlation between the selected currencies
We can see that the nature of the correlation between the selected currencies is not identical; some of the
markets are positively correlated while others are negatively correlated. For example, Naira, Rand, Singapore
dollars, Yen and Canadian dollars are positively correlated. Also most of the Asian markets are positively
correlated, e.g. Yuan, Singapore dollars, Yen and Ringgit. This is due to their closeness; their cultural and
geographical similarities among other factors which have been conform to the arguments in most of the
literatures.
V. SUMMARY AND CONCLUSION:
As stated earlier, an exchange rate is the current market price for which one currency can be exchanged
for another. Currency exchange rates are among the most analyzed and forecasted indicators in the world.
However, the exchange rate is determined by the level of supply and demand on the international markets.
Similarly, changes in foreign exchange market rate are often difficult to understand and predict because the
market is very large and volatile. So this research is aimed to establish the volatility model i.e. the Multivariate
Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) time series models to analyze the daily
dollar-Naira exchange rates together with eight major currencies in the world between the periods of 4th
January,
1999 and 21st
February, 2014 inclusive. And hence, to observe some stylize facts/common features of good
volatility modeling on financial time series (such as fat tails, volatility clustering, and etc.). To achieve the stated
objectives, we employed three multivariate volatility models (i.e. DVECH, BEKK and CCC) and the result
indicated that the restricted BEKK, DVECH and CCC results exhibit rather similar behavior for each
considering countries. We further observe that in all three models, the time of the greatest peak match with time
when the United States experienced serious financial meltdown. This shows that there is a serious
interdependence of measure world currencies on the United States Dollar. Similarly, the indicated that the
skewness is greater than zero (for the normal distribution), that is to say the distribution is positively skewed
which is an indication of a non symmetric series, meaning that there is an asymmetric effects in these models
(i.e. volatility is higher in a falling market than in a rising market)
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which is another stylize fact of financial time series. The kurtosis is also greater than 3 (the kurtosis of
a normal distribution). Recall that; relatively large kurtosis suggests that the distribution of the exchange rate
return series is leptokurtic (i.e. exhibit fat tail) which is another stylize fact. Thereafter, Jarque Bera normality
test statistic indicates that, neither returns series has a normal distribution.The results also indicated that the
nature of the correlation between the selected currencies is not identical; some of the markets are positively
correlated while others are negatively correlated. For example, Naira, Rand, Singapore dollars, Yen and
Canadian dollars are positively correlated. Also most of the Asian markets are positively correlated, e.g. Yuan,
Singapore dollars, Yen and Ringgit. This is due to their closeness; their cultural and geographical similarities
among other factors which have been conform to the arguments in most of the literatures. Conclusively, base on
information criteria, the DVECH model is found to be the best model because it has maximum likelihood and
lower Akaike information criteria (AIC) as well as lower Schwarz information criteria (SIC). But according to
parsimonious principle, the BEKK model is considered to be the best because it has least number of parameters.
RECOMMENDATIONS: The results of the analysis reveals that, the DVECH and BEKK models are
recommended to be the best models respectively because most of their variances/covariances are statistically
significant and they have maximum likelihood, lower Akaike information criteria (AIC) and lower Schwarz
information criteria (SIC). The research can serve as a step to observe the volatility modeling of the Naira
exchange rates with other currencies so as to re-identify some silence phenomena of the exchange rate. Data of
some specified periods can be tested by a feature researcher(s) by developing new and more models to capture
the effect and predictions of the volatility behavior of the Naira exchange rate.
VI. ACKNOWLEDGEMENT
We would like to thank the Board of Governors Federal Reserve Bank of Louis (U.S.A) for sharing the
data with public. However, we bare full responsibility for any error (s) in this paper.
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