Stock Return and Exchange Rate Risk: Evidence from Asian Stock Markets Based on A Bivariate GARCH Model (original) (raw)

Interactions between stock prices and exchange rates: An application of multivariate Var-Garch model

Cogent Economics & Finance

The study examined stock prices and exchange rate interactions with multivariate VAR-GARCH model using monthly data from January 2000 to October 2014. The results of the E-G and Johansen cointegration test show that there is stable long-term relationship between stock prices and exchange rate. The empirical evidence of the VAR-GARCH model shows a significant mean spillover running from stock market to exchange market but not a mean spillover from exchange market to stock market. The variance equation results indicated the existence of bi-directional volatility transmission effect between stock prices and exchange rates, indicating the past innovations in stock market have the great effect on future volatility in foreign exchange market, and vice versa. The results have important implications for international portfolio managers in the portfolio diversification decisions and risk hedging strategies.

Interest and Exchange Rate Risk and Stock Returns: A Multivariate Garch-M Modelling Approach

2000

In this paper we examine the sensitivity of stock returns to market, interest rate, and exchange rate risk in three financial sectors (Banking, Financial Services and Insurance) in 16 countries, including various European economies, the US and Japan. We also test for the presence of causality-in-mean and volatility spillovers. The econometric framework is a four- variate GARCH-in-mean model, which incorporates

Investigating the intertemporal risk–return relation in international stock markets with the component GARCH model

Economics Letters, 2008

We revisit the risk-return relation using the component GARCH model and international daily MSCI stock market data. In contrast with the previous evidence obtained from weekly and monthly data, daily data show that the relation is positive in almost all markets and often statistically significant. Likelihood ratio tests reject the standard GARCH model in favor of the component GARCH model, which strengthens the evidence for a positive risk-return tradeoff.

A multivariate GARCH analysis of equity returns and volatility in Asian equity markets: Discussion Paper No 89

This paper examines the transmission of equity returns and volatility among Asian equity markets and investigates the differences that exist in this regard between the developed and emerging markets. Three developed markets (Hong Kong, Japan and Singapore) and six emerging markets (Indonesia, Korea, Malaysia, the Philippines, Taiwan and Thailand) are included in the analysis. A multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model is used to identify the source and magnitude of spillovers. The results generally indicate the presence of large and predominantly positive mean and volatility spillovers. Nevertheless, mean spillovers from the developed to the emerging markets are not homogenous across the emerging markets, and own-volatility spillovers are generally higher than cross-volatility spillovers for all markets, but especially for the emerging markets.

A multivariate GARCH analysis of equity returns and volatility in Asian equity markets

2001

This paper examines the transmission of equity returns and volatility among Asian equity markets and investigates the differences that exist in this regard between the developed and emerging markets. Three developed markets (Hong Kong, Japan and Singapore) and six emerging markets (Indonesia, Korea, Malaysia, the Philippines, Taiwan and Thailand) are included in the analysis. A multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model is used to identify the source and magnitude of spillovers. The results generally indicate the presence of large and predominantly positive mean and volatility spillovers. Nevertheless, mean spillovers from the developed to the emerging markets are not homogenous across the emerging markets, and own-volatility spillovers are generally higher than cross-volatility spillovers for all markets, but especially for the emerging markets.

Stock returns in emerging markets and the use of GARCH models

Applied Economics Letters, 2011

We use the Hinich portmanteau bicorrelation test to detect for the adequacy of using GARCH (Generalized Autoregressive Conditional Heteroscedasticity) as the data-generating process to model conditional volatility of stock market index rates of return in 13 emerging economies. We find that a GARCH formulation or any of its variants fail to provide an adequate characterization for the underlying process of the 13 emerging stock market indices. We also study whether there exist evidence of ARCH effects, over windows of 200, 400 and 800 observations, using Engle's LM (Lagrange Multiplier) test, and find that there exist long periods of time with no evidence of ARCH effects. The results suggest that policymakers should use caution when using autoregressive models for policy analysis and forecast because the inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolio selection and risk management. Specially, measures of spillover effects and output volatility may not be accurate when using GARCH models to evaluate economic policy.

A double-threshold GARCH model of stock market and currency shocks on stock returns

Mathematics and Computers in Simulation, 2008

International integration of financial markets provides a channel for currency movements to affect stock prices. This paper applies a four-regime double-threshold GARCH (DTGARCH) model of stock market returns to investigate empirically the effects of daily currency movements on five stock market returns, namely in Taiwan, Singapore, South Korea, Japan and the USA. The asymmetric reactions of the mean and volatility stock returns in five markets to stock market and foreign exchange news are investigated using linear and nonlinear models. We discuss a four-regime DTGARCH model, which allows for asymmetry in both the conditional mean and conditional variance simultaneously by using two threshold variables to analyze stock market reactions to different types of information (that is, positive and negative news) that are generated from stock and foreign exchange markets. By applying the four-regime DTGARCH model, this paper finds that the interactions between the information of stock and foreign exchange markets lead to asymmetric reactions of stock returns and their associated variability. The empirical results show that international fund managers who invest in newly emerging stock markets need to evaluate the value and stability of domestic currencies as part of their stock market investment decisions.

Exchange Rate Pass through to Stock Prices: A Multi GARCH Approach

2020

This paper analytically examines the impact of exchange rate volatility on stock prices in Nigeria via both symmetric and asymmetric GARCH models. At the onset the descriptive statistics reveals that both series are non-normally distributed as indicated by the Jacque-Bera statistic, also the standard deviation implied that the stock price series is more volatile than the exchange rate. Furthermore both series are reported to be negatively skewed also reference to the kurtosis statistics presented it is observed that both series are leptokurtic distribution. Further the result obtained from the estimated model GARCH models reveals that the PGARCH gives the better fit of the stock prices volatility model given its minimum AIC value. In the symmetric models {GARCH (1, 1) and GARCH-in-Mean} the shocks on stock returns volatility are found to be mean reverting whilst in the asymmetric GARCH models {TGARCH, EGARCH and PGARCH} only EGARCH was found to be non-mean reverting. Further, the as...

The Effect of External Markets on Domestic Markets in India: ARCH-GARCH Estimation of the Causal Relationship between Exchange Rate and Stock Returns Volatility

Journal of Risk and Financial Studies, 3(2), 95-112 , 2022

As global investors diversify their portfolios across currencies and national stock markets, the exchange rate risk and its association with the local stock market is an important component of the overall portfolio risk. This paper empirically analyses the effect of exchange rate volatility on stock market return volatility from India's perspective, applying ARCH and GARCH estimation on daily data of the BSE SENSEX stock market index and the exchange rate of US dollar/rupee, British pound/rupee, Euros/rupee for six years from January 2010 to December 2015. The estimates reveal that the volatility of the Euro/rupee exchange rate has a significant positive effect on BSE SENSEX return volatility while the effect of the volatility of the US dollar/rupee and British pound/rupee exchange rates are insignificantly negative. The larger GARCH parameter over the ARCH term implies that the volatility of stock returns is more sensitive to its own lagged values than to its new surprises. There exists a highly persistent effect of shocks to the BSE SENSEX stock returns and the response to volatility decays at a slower rate.

Correlation and Volatility Transmission across International Stock Markets: A Bivariate GARCH Analysis

International Journal of Economics and Finance, 2012

The study empirically examines correlation and volatility transmission across international stock markets by employing Bivariate GARCH model. The study uses weekly data for five major stock indices such as S&P 500(USA), BSE 30 sensex (India), FTSE 100(U.K), Nikkei 225(Japan) and Ordinary Share Price Index (Australia) from 30 th January, 1998 to 30 th July, 2011. Long run and short run integrations are investigated through Johansen cointegration and vector error correction models respectively. The results of Johansen test show that long run co-integration is found across international stock indices prices. Further, results suggest that the arrival of external news is simultaneously received by US and Japan stock markets and then transmitted to other Asian and European stock markets. The results of bivariate GARCH model reveal that there is a bidirectional volatility spillover between US and Indian stock markets. This is due to fact that these two economies are strongly integrated through international trade and investment. Finally, results show that a unidirectional volatility spillover from Japan and United Kingdom to India.