• International Area Studies Review
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• v.21 no.4
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• pp.223-245
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• 2017

This study is examined interaction between carbon market with stock market using a multivariate GARCH(DCC) model. Carbon market is EU ETS EUA price, stock market is the iron and cement stock price which has relatively energy intensive and massive carbon emissions sector in the industrial sector. It also analyzed changes in the correlation between the markets through an analysis of correlation coefficients. Moreover, it checked whether there was marketability expansion(or expansion of carbon emissions reduction) through the analysis above. As a result of empirical tests, it showed that the price spillover effect was insignificant. In addition, it represented that there was a weak correlation between the two markets since the volatility spillover effect disappeared in the second phase by an external shock(a financial crisis). Moreover, it was revealed that there were no significant changes although there was a weak upward trend in terms of the correlation between the carbon market and the stock market. This implies that emission rights could not expand marketability to financial market as a commodity(or did not play its natural role of the reduction of carbon emission).

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.1-9
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• 2022

The study examines stock prices (LOGKSE) and exchange rate (LOGPK)-Pakistani Rupee vis-à-vis US Dollar- interactions in Pakistan. This study employs a multivariate VAR-GARCH model using monthly data from January 2012 to October 2020. The results of the Johansen cointegration test show that there is no relationship between Foreign Exchange Market and Stock Market in the long run. In the short-run, stock exchange returns are affected slightly negatively by the changes in the foreign exchange market, but the foreign exchange market does not seem to be affected by the ups and downs of the stock exchange. The VAR model and Granger Causality show that both markets are strongly influenced by their own lagged values rather than by the lagged values of one another and show weak or no correlation between the two markets. Volatility persistence is observed in both the stock and foreign exchange markets, implying that shocks and past period volatility are major drivers of future volatility in both markets. Thus greater uncertainties today will induce panic and consequently generate higher volatility in the future period. This phenomenon has been observed many times on Pakistan Stock Exchange especially. The results have important implications for local international investors in portfolio diversification decisions and risk hedging strategies.

• Journal of Korea Trade
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• v.27 no.1
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• pp.139-158
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• 2023

Purpose - The study of co-movements between stock markets is a crucial area of finance and has recently received much interest in a variety of studies, especially in international finance. Stock market co-movements are a major phenomenon in financial markets, but they are not necessarily independent of the real market. Several studies support the idea that bilateral trade linkages significantly impact stock market correlations. Motivated by this perspective, this study investigates whether real market integration due to trade agreements brings about financial market integration in terms of stock market co-movement. Design/methodology - Over the 10 free trade agreements (FTAs) signed by the United States, using a dynamic conditional correlations (DCC) multivariate GARCH (MGRACH) model, we empirically measure the degree of integration by finding DCCs between the US market and the partner country's market. We then track how these correlations evolve over time and compare the results before and after trade agreements. Findings - According to the empirical results, there are positive return spillover effects from the US market to eight counterpart equity markets, except Jordan, Morocco, and Singapore. Especially Mexico, Canada, and Chile have large return spillover effects at the 1% significance level. All partner countries of FTAs generally have positive correlations with the US over the entire period, but the size and variance are somewhat different by country. Meanwhile, not all countries that signed trade agreements with the United States showed the same pattern of stock market co-movement after the agreement. Korea, Mexico, Chile, Colombia, Peru, and Singapore show increasing DCC patterns after trade agreements with the US. However, Canada, Australia, Bahrain, Jordan, and Morocco do not show different patterns before and after trade agreements in DCCs. These countries generally have the characteristic of relatively lower or higher co-movements in stock markets with the US before the signing of the FTAs. Originality/value - To our knowledge, few studies have directly examined the linkages between trade agreements and stock markets. Our approach is novel as it considers the problem of conditional heteroscedasticity and visualizes the change of correlations with time variations. Moreover, analyzing several trade agreements based on the United States enables the results of cross-country pairs to be compared. Hence, this study provides information on the degree of stock market integration with countries with which the United States has trade agreements, while simultaneously allowing us to track whether there have been changes in stock market integration patterns before and after trade agreements.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.13-28
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• 2022

The growth of the Islamic finance sector has been well-documented. One of the most booming sectors has been Sukuk. According to several past studies, non-Islamic investors' interest in Sukuk is due, at least in part, to the diversification benefits that Sukuk provides in the context of a fixed-income portfolio. This paper compares a pair between Sukuk and Bonds in the Malaysian market issued by the same issuer to have an unbiased comparison. Using unconditional correlation methodology provides an initial examination of the relationship between the matched pairs. In addition, this paper adopts the standard GARCH-DCC approach of Engle (2002). This is a generalization of the Bollserslev (1990) GARCH model, allowing for the conditional correlation matrices to be time-varying. The findings reveal that the correlation between bonds and Sukuk is similar to that of bonds, making Sukuk a less appealing type of bond from a diversification standpoint. There are no significant differences between Sukuk and bonds. These finding questions the previously considered differences among different types of Sukuk and supports the argument that some Sukuk might not be compliant with Islamic rules and their structure, as contracts have the same risks for Sukuk holders regardless of the type of Sukuk.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.597-607
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• 2011

Value at Risk(VaR) is being widely used as a simple tool for measuring financial risk. Although VaR has a few weak points, it is used as a basic risk measure due to its simplicity and easiness of understanding. However, it becomes very difficult to estimate the volatility of the portfolio (essential to compute its VaR) when the number of assets in the portfolio is large. In this case, we can consider the application of a dimension reduction technique; however, the ordinary factor analysis cannot be applied directly to financial data due to autocorrelation. In this paper, we suggest a dimension reduction method that uses the time-series factor analysis and DCC(Dynamic Conditional Correlation) GARCH model. We also compare the method using time-series factor analysis with the existing method using ordinary factor analysis by backtesting the VaR of real data from the Korean stock market.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.465-471
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• 2021

The study investigates the dynamic correlation of cryptocurrencies and equity in Vietnam and tests the safe-haven property of them from the perspective of the stock market in Vietnam during the pandemic crisis by applying the dynamic conditional correlation (DCC) GARCH model and regression with a dummy variable, respectively. This study employs time series data on the daily dataset from September 2014 to September 2021 with the focus on the two most popular cryptocurrencies - Bitcoin and Litecoin. The results show that the dynamic conditional correlations between cryptocurrencies and equity in Vietnam increased during the pandemic, however, in most periods, positive dynamic correlations often dominate. Besides, the regression results also indicate that Bitcoin and Litecoin act as weak safe-haven investments for stocks in Vietnam during the COVID-19 turmoil. They are more suitable for diversification purposes although the dynamic correlations between them and the stock index in Vietnam vary stronger during the pandemic crisis than before. The findings of this study suggest that in the period of pandemic crisis, cryptocurrencies are not concerned as effective safe-haven assets for stock in Vietnam. Instead, cryptocurrencies are only playing a potential role in diversification benefit in this economy.