scholarly journals Volatility spillovers and dynamic correlations among foreign exchange rates and bond markets of emerging economies

2020 ◽  
pp. 20-20
Author(s):  
Resul Aydemir ◽  
Bulent Guloglu ◽  
Ercan Saridogan
Keyword(s):  
Exchange Rates ◽  
Foreign Exchange ◽  
Global Financial Crisis ◽  
Multivariate Garch ◽  
Bond Markets ◽  
Impulse Response Functions ◽  
Dynamic Interactions ◽  
Volatility Spillovers ◽  
Dynamic Correlations ◽  
Multivariate Garch Model

In this paper, we first examine how important historical shocks during and after the 2007-2008 global financial crisis affect the size and the persistence of volatilities among exchange rates and the ten-year bond rates of the Fragile Five countries (i.e., Brazil, India, Indonesia, South Africa and Turkey). We then investigate separately the dynamic interactions between exchange rates and the ten-year bond rates of the Fragile Five. We utilize a multivariate GARCH model (FIAPARCH-DCC model) and volatility impulse response functions to achieve these objectives. The results suggest that shocks? positive impacts on expected conditional variances of the variables are largely market-specific and different. Shocks have a more significant impact on bond markets than on foreign exchange markets. We also find that the dynamic conditional correlation series of bonds exhibit much lower correlations than those associated with exchange rate returns.

Returns and volatility spillover between stock prices and exchange rates

2013 ◽  
Vol 8 (2) ◽  
pp. 108-128 ◽  
Author(s):  
Manish Kumar
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Stock Prices ◽  
Multivariate Garch ◽  
Foreign Exchange Markets ◽  
Volatility Spillover ◽  
Content Type ◽  
Volatility Spillovers ◽  
Exchange Markets

PurposeThe purpose of this paper is to analyze the nature of returns and volatility spillovers between exchange rates and stock price in the IBSA nations (India, Brazil, South Africa).Design/methodology/approachThe study uses VAR framework and the recently proposed Spillover measure of Diebold and Yilmaz to examine the returns and volatility spillover between exchange rates and stock prices of IBSA nations. In addition, multivariate GARCH with time varying variance‐covariance BEKK model is used as a benchmark against the spillover methodology proposed by Diebold and Yilmaz.FindingsThe results of multivariate GARCH model suggests the integration between stock and foreign exchange markets and indicates the existence of bi‐directional volatility spillover between stock and foreign exchange markets in the IBSA countries. Spillover results using the Diebold Yilmaz model suggest the bi‐directional contribution between stock and foreign exchange market, in terms of both returns and volatility spillovers. Overall, results confirm the presence of returns and volatility spillovers within the IBSA nations and, in particular, the stock markets play a relatively more important role than foreign exchange markets in the first and second moment interactions and spillovers.Practical implicationsThe market participants may consider the relationship between the exchange rate and stock index to predict the future movement of each other effectively. Multinational companies interested in exchange rate forecasting may consider the stock market as an important attribute. There is an interesting implication for portfolio managers too because of the spillover stock and foreign exchange markets. This knowledge would help to create a fund which performs well. Moreover, the paper can help regulators and policy makers in IBSA nations to understand the structure of the market in a better way and then design their policies.Originality/valueThe study contributes to the literature by extending the existing studies on the spillover between stock price and exchange rate by investigating the issue for three emerging economies, India, Brazil and South Africa. Unlike most studies in the literature which focus on multivariate GARCH model, this is the first study which explores the issue of returns and volatility spillover between the stock prices and the exchange rates using spillover measure of Diebold and Yilmaz and much longer and recent daily data. Moreover, multivariate GARCH with time varying variance‐covariance BEKK model is used as a benchmark against the spillover methodology proposed by Diebold and Yilmaz.

An Empirical Investigation of Factors Affecting Stock Prices in Vietnam

2014 ◽  
pp. 74-89 ◽  
Author(s):  
Vinh Vo Xuan
Keyword(s):  
Exchange Rates ◽  
Crude Oil ◽  
Foreign Exchange ◽  
Stock Prices ◽  
Global Financial Crisis ◽  
Oil Prices ◽  
Foreign Exchange Rates ◽  
Factors Affecting ◽  
Crude Oil Prices ◽  
Before And After

This paper investigates factors affecting Vietnam’s stock prices including US stock prices, foreign exchange rates, gold prices and crude oil prices. Using the daily data from 2005 to 2012, the results indicate that Vietnam’s stock prices are influenced by crude oil prices. In addition, Vietnam’s stock prices are also affected significantly by US stock prices, and foreign exchange rates over the period before the 2008 Global Financial Crisis. There is evidence that Vietnam’s stock prices are highly correlated with US stock prices, foreign exchange rates and gold prices for the same period. Furthermore, Vietnam’s stock prices were cointegrated with US stock prices both before and after the crisis, and with foreign exchange rates, gold prices and crude oil prices only during and after the crisis.

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.

scholarly journals Modeling Exchange Rate and Nigerian Deposit Money Market Dynamics Using Trivariate form of Multivariate GARCH Model

2019 ◽  
pp. 1-18
Author(s):  
Deebom, Zorle Dum ◽  
Tuaneh, Godwin Lebari
Keyword(s):  
Exchange Rate ◽  
Garch Model ◽  
Money Market ◽  
Multivariate Garch ◽  
Market Dynamics ◽  
Volatility Clustering ◽  
Volatility Spillovers ◽  
Multivariate Garch Model ◽  
The Difference ◽  
Student’S T

The risks associated with exchange rate and money market indicators have drawn the attentions of econometricians, researchers, statisticians, and even investors in deposit money banks in Nigeria. The study targeted at modeling exchange rate and Nigerian deposit banks money market dynamics using trivariate form of multivariate GARCH model. Data for the period spanning from 1991 to 2017 on exchange rate (Naira/Dollar) and money market indicators (Maximum and prime lending rate) were sourced for from the central bank of Nigeria (CBN) online statistical database. The study specifically investigated; the dynamics of the variance and covariance of volatility returns between exchange rate and money market indicators in Nigeria were examine whether there exist a linkage in terms of returns and volatility transmission between exchange rate and money market indicators in Nigeria and compared the difference in Multivariate BEKK GARCH considering restrictive indefinite under the assumption of normality and that of student’s –t error distribution.  Preliminary time series checks were done on the data and the results revealed the present of volatility clustering. Results reveal the estimate of the maximum lag for exchange rate and money market indicators were 4 respectively. Also, the results confirmed that there were two co-integrating equations in the relationship between the returns on exchange rate and money market indicators.  The results of the diagonal MGARCH –BEKK estimation  confirmed  that diagonal MGARCH –BEKK in students’-t was  the best fitted and an appropriate model for modeling exchange rate and Nigerian deposit money market dynamics using trivariate form of multivariate GARCH model. Also, the study confirmed presence of two directional volatility spillovers between the two sets of variables.

scholarly journals Analysis of financial contagion in influential African stock markets

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Oluwatosin Mary Aderajo ◽  
Oladotun Daniel Olaniran
Keyword(s):  
Stock Prices ◽  
Variance Estimation ◽  
Global Financial Crisis ◽  
Multivariate Garch ◽  
Financial Contagion ◽  
African Countries ◽  
Crisis Period ◽  
Dynamic Correlation ◽  
Multivariate Garch Model ◽  
The Us

AbstractDrawing from the experience of the global financial crisis that sprang forth from the US stock market, an empirical assessment of the dynamic correlation analysis of financial contagion with evidence from (5) African countries (South African, Nigeria, Egypt, Kenya, Tunisia) is presented. Monthly stock prices indices from 2004 to 2018 was analyzed using the dynamic conditional correlation multivariate GARCH model to ascertain the contagious effect of the US to the selected African markets. By analyzing the correlation coefficient series, three phases of the crisis periods were identified {pre-crisis (2004–2007); crisis (2007–2009) and post-crisis (2009–2018), respectively}. The study revealed that a significant relationship exists between the returns of the US market and the African markets. The inspection of the pre-crisis, crisis, post-crisis mean and variance estimation shows that the crisis period is characterized by substantial increases in volatility, establishing that the shock experienced in the US posed a threat to the African markets being examined. Further, evidence revealed that in the crisis period, an increase in correlation (contagion) existed, while a continued correlation (herding) existed in the post-crisis period.

Interlinkages Between USD–INR, EUR–INR, GBP–INR and JPY–INR Exchange Rate Markets and the Impact of RBI Intervention

2019 ◽  
Vol 18 (1_suppl) ◽  
pp. S102-S136
Author(s):  
Pami Dua ◽  
Ritu Suri
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Jel Classification ◽  
The Other ◽  
Multivariate Garch ◽  
Vector Autoregressive ◽  
Volatility Spillovers ◽  
Exchange Rate Markets ◽  
The Impact

This article examines interlinkages between four major exchange rates, namely, USD–INR, EUR–INR, GBP–INR and JPY–INR in terms of returns and volatility spillovers using a vector autoregressive-multivariate GARCH–BEKK framework. In addition, we analyse the impact of RBI intervention on the returns, volatility and covariance of these exchange rates. The study finds significant bidirectional causality-in-mean and causality-in-variance between all four exchange rates. The estimation results suggest that RBI intervention in the form of net purchase of dollars leads to depreciation of INR vis-à-vis USD, EUR, GBP and JPY. Furthermore, we find that RBI intervention not only significantly affects the volatility of INR vis-à-vis USD, EUR and GBP but also explains significant amount of covariance between USD–INR and the other three exchange rates. JEL Classification: C32, G15, E58, F31

Sign in / Sign up

Export Citation Format

Share Document