scholarly journals Volatility spillover from the united states and Japanese stock markets to the Vietnamese stock market: A frequency domain approach

2020 ◽  
pp. 3-3
Author(s):  
Le Nghi ◽  
Nguyen Kieu
Keyword(s):  
United States ◽  
Stock Market ◽  
Frequency Domain ◽  
Stock Markets ◽  
The United States ◽  
Frequency Domain Analysis ◽  
Volatility Spillover ◽  
Causality Test ◽  
Daily Data ◽  
Frequency Domain Approach

Using frequency domain analysis, this paper examines the volatility spillover from the United States and Japanese stock markets to the Vietnamese stock market. Daily data of S&P 500, Nikkei 225 and VN-Index from January 01, 2012 to May 31, 2016 is used. In terms of estimation, the GARCH model is used to estimate volatilities in these stock markets; the Granger Causality Test is used to examine volatility spillover; and the test for causality in the frequency domain by Jorg Breitung and Bertrand Candelon (2006) is used to examine the volatility spillover at different frequencies. The empirical results provide two main contributions: (i) there is a significant volatility spillover from the United States to the Vietnamese stock markets, but the evidence of volatility spillover from the Japanese to the Vietnamese stock market is not found; and (ii) the volatility spillover may vary across frequency spectrum bands. To our best understanding, volatility spillover analysis using frequency domain approach was not previously reported in literature.

Do Global Financial, Oil and Gold Volatility Shocks Affect the GCC Stock Markets?

2019 ◽  
Vol 5 (2) ◽  
pp. 157-175 ◽  
Author(s):  
Abdullah Alqahtani
Keyword(s):  
Saudi Arabia ◽  
Stock Market ◽  
Stock Markets ◽  
Structural Var ◽  
Causality Test ◽  
Data Set ◽  
Financial Volatility ◽  
Daily Data ◽  
Positive Shock ◽  
The Impact

This study employed the non-structural VAR econometrics approach to examine the impact of Global Oil (OVX), Financial (VIX), and Gold (GVZ) volatility indices on GCC stock markets using a daily data set spanning from January 5, 2009 to August 16, 2018. From the VAR result obtained, disequilibrium in the global financial volatility (VIX) was able to significantly transmit negative shock to Bahrain and Kuwait stock markets and positive shock on GVZ. While the global Gold volatility was capable of transmitting fairly positive shock to the UAE and VIX market. The OLS also revealed more to the result obtained from VAR as it shows that OVX and VIX can have impact on the GCC stock markets. The causality test revealed that there is a unidirectional causality running from Qatar and UAE to OVX; none of the variables was able to granger cause VIX, while unidirectional causality exist from VIX and UAE to GVZ and VIX and Qatar to Bahrain. VIX and Qatar can granger cause Kuwait stock market, and only Saudi Arabia and Oman have bidirectional causality. Unidirectional causality exists from Saudi Arabia to Qatar, and Qatar is the only stock market capable of causing UAE unidirectionally. Hence, the study concludes that VIX and GVZ are capable of transmitting shocks to three of the six GCC stock markets—(Bahrain, Kuwait and The UAE) negatively (Bahrain and Kuwait) and positively (The UAE). And on this note, the study recommends that appropriate financial and gold transaction policies should be institutionalized so as to mitigate the transmission of shocks into the markets. Also, financial and gold experts who regulate the stock and gold markets especially in Bahrain and Kuwait should watch for any abnormality changes in the volatility movement of the financial and gold markets.

Volatility spillover between the US, Chinese and Australian stock markets

2017 ◽  
Vol 43 (2) ◽  
pp. 263-285 ◽  
Author(s):  
Emawtee Bissoondoyal-Bheenick ◽  
Robert Brooks ◽  
Wei Chi ◽  
Hung Xuan Do
Keyword(s):  
United States ◽  
Financial Services ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
The United States ◽  
Jel Classification ◽  
Volatility Spillover ◽  
Stock Market Volatility ◽  
Index Level ◽  
The Global Financial Crisis

We assess the stock market volatility spillover between three closely related countries, the United States, China and Australia. This study considers industry data and hence provides a clear idea of the channels through which volatility is transmitted across these countries. We find that there is significant bilateral causality between the countries at the market index level and across most of the industries for the full sample period from July 2007 to May 2016. There is one-way volatility spillover from the United States to China in the financial services, industrials, consumer discretionary and utilities industry. There is insignificant volatility spillover from the Australian to Chinese stock markets in financial services, telecommunications and energy industries. Once we remove the effect of the global financial crisis (GFC), we find significant bilateral relationship across all of the industries across the three countries. JEL Classification: G15

An empirical analysis of stock market interdependence and volatility spillover in the stock markets of Africa and Middle East region

2019 ◽  
Vol 10 (3) ◽  
pp. 314-335 ◽  
Author(s):  
Ajaya Kumar Panda ◽  
Swagatika Nanda ◽  
Rashmi Ranjan Paital
Keyword(s):  
Middle East ◽  
Stock Market ◽  
Stock Markets ◽  
Volatility Spillover ◽  
Causality Test ◽  
Content Type ◽  
East Region ◽  
Long Run ◽  
International Investors ◽  
Middle East Region

Purpose The purpose of this paper is to examine the short-term and long-term interdependence among the stock markets of Africa and Middle East region. It also attempts to analyze the pattern of volatility spillover among the regional stock markets. Design/methodology/approach The study has used Granger causality test, variance decomposition test of vector auto-regression (VAR) model, vector error correction model (VECM), multivariate generalized conditional heteroskedasticity (MGARCH-BEKK) models and Johansen and Juselius multivariate cointegration techniques. Findings The study finds that the interlinkages of the stock markets are not uniform across all the countries of the region. The stock market of Israel, South Africa and Jordan are found to be highly connected stock market of the region followed by Egypt and Botswana. The study also finds significant spillover of lagged standardized volatility across the stock markets of the region. But the magnitude of the response of volatility spillover and its persistence is very minimum. However, the stock markets are found to be co-integrated and expected to share long-run equilibrium relationships among each other. Research limitations/implications The study has the scope to be extended to capture the time-varying integration of market returns with transmission of monetary policy and exchange rate changes within the region. The results obtained from this study may assist the firm managers and international investors to understand the key drivers of market connectedness. Originality/value Empirically investigating the pattern of stock market connectedness in Africa and Middle East region with advanced methodology over a long study period is the originality of this study.

Spillover effects between energies, gold, and stock: the United States versus China

2020 ◽  
Vol 31 (8) ◽  
pp. 1416-1447 ◽  
Author(s):  
Xie He ◽  
Tetsuya Takiguchi ◽  
Tadahiro Nakajima ◽  
Shigeyuki Hamori
Keyword(s):  
United States ◽  
Stock Market ◽  
Crude Oil ◽  
Spillover Effect ◽  
The United States ◽  
Commodity Markets ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
The Us ◽  
Volatility Spillover Effect

This study investigates the time–frequency dynamics of return and volatility spillovers between the stock market and three commodity markets: natural gas, crude oil, and gold via a comparative analysis between the United States and China is conducted with the help of new empirical methods. Our findings are as follows. First, in terms of time, return spillovers between crude oil and the stock market are strongest in two of the three commodity markets. Crude oil emits a net negative return spillover to the US stock market, and a net positive return spillover to the Chinese stock market. By contrast, the strongest volatility spillover effect is transmitted to the stock markets of both countries through gold. However, gold has a net positive volatility spillover effect on the US stock market and a net negative effect on the Chinese stock market. In the frequency domain, most of the return spillover is produced in the short term, and most of the volatility spillover occurs in the long term. In addition, the moving-window method reveals the dynamic nature of the spillover effect. Some extreme events can have a dramatic effect on the spillover index. Conversely, the spillover effect differs significantly between the two countries and is characterized by time variation and frequency dependence.

Stock Market Integration and Trade: A Study on India and its Major Trading Partners

2021 ◽  
pp. 097226292110344
Author(s):  
Samiran Jana
Keyword(s):  
United States ◽  
Time Series ◽  
Stock Market ◽  
Stock Markets ◽  
The United States ◽  
Asia Pacific ◽  
Panel Regression ◽  
Conditional Correlation ◽  
Trading Partners ◽  
Indian Stock Market

Indian stock market is increasingly integrated with other markets of the world after economic liberalization. This linkage of Indian stock market reduces the scope of risk minimization of portfolio by diversifying between stock markets of India and its integrated partners. Researchers indicate that economic variables influence the integration of stock markets. Trade is one of the major parameters. In this study effort has been made to find how Indian stock market integration varies with amount of trade with its trading partners. Hence 21 years’ weekly data from 1 January 1999 to 31 December 2019 have been collected for 15 countries, which belong to the list of top 25 trading partners of India since 1999. Total sample of 15 countries have been divided into two groups—Asia Pacific and European group along with United States, to check whether integration increase with trade. Johansen Cointegration test has been used between stock markets of India and two groups of countries. To confirm the result of Johansen cointegration test, the same test was ran on joint index for each group and Sensex of India. It also helped to check the effect of geographical proximity on this integration. Conditional correlation was found using asymmetric generalized dynamic conditional correlation (AGDCC) GARCH model, between Sensex and each of the 15 countries, to observe the time varying nature of correlation. Twenty one year’s data has helped to find the impact of global financial crisis (GFC) of 2008 on these interlinkages. Lending rate differential and inflation rate differential can cover many economic parameters, hence used as control variable. Time series regression has been used to find the impact of trade, interest rate and inflation differential on correlation between Indian stock market index and index of any other countries. Pooled panel regression has been used to check the same relationship on all countries in every group. Nine Asian countries together contribute higher amount of trade with India since 2004 than jointly five European countries and the United States. Trade difference is very low, hence this study analysed both the groups. Asia Pacific group of countries is more integrated with India than European group and the United States. None of the joint index is integrated with Indian stock market index. Conditional correlation between Indian index and each of the country has changed over time. Time series regression implies that except very few cases, trade and other economic factors cannot influence the integration. As expected, the interest rate differential and inflation differential have negative and positive impacts on the correlation respectively but these impacts are not significant in many cases. Pooled panel regression shows that trade and GFC have positive and significant impact on correlation between India and Asia Pacific countries but not with the same between India and European countries and United States. International investors will not be able to reduce their portfolio risk by diversifying between India and any other of the 15 countries in the sample because all of them are integrated with Indian stock market. Trade of India with Asian countries has increased in recent years and integration has also increased. Although time series and pooled panel regression do not prove it’s significant impact on conditional correlation between India and the sampled countries. But trade between two countries definitely bear a role in integration.

scholarly journals The Integration of Islamic Stock Markets of OIC Countries in China Stock Market Crisis and US-China Trade War

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Deri Siswara
Keyword(s):  
United States ◽  
Stock Market ◽  
Stock Markets ◽  
The United States ◽  
Distributed Lag ◽  
China Trade ◽  
The Us ◽  
China Stock Market ◽  
Trade War

The purpose of this study is to analyze the integration and response of the Islamic stock market of the OIC countries before the crisis and during the China stock market crisis also during the United States-China trade war with the Autoregressive Distributed Lag (ARDL) method. The results showed that there was no cointegration in the period before the China stock market crisis. However, during the period of the China stock market crisis and the United States-China trade war, the cointegration was more common. The Islamic stock market of Qatar, Saudi Arabia and the UAE experienced a domino effect from fluctuations in crude oil prices. Then, the Indonesia Islamic stock market in the two crisis periods had a long-term relationship with the US and China stock markets. Whereas the Malaysian and Bangladesh Islamic stock markets have only a long-term relationship with the US stock market. In terms of the benefits of portfolio diversification for investors, there is relevance of dominant economic, geographical, and trade relations in influencing the integration of the Islamic stock market.

The Impact of Monetary and Fiscal Policies on the Stock Market in the United States (U.S); Evidence from Linear ARDL Framework

2020 ◽  
Vol 11 (1) ◽  
pp. 132-132
Author(s):  
Aref Emamian
Keyword(s):  
United States ◽  
Stock Market ◽  
The United States ◽  
Real Effective Exchange Rate ◽  
Annual Data ◽  
Fiscal Policies ◽  
Long Run ◽  
The Us ◽  
Short Run ◽  
The Impact

This study examines the impact of monetary and fiscal policies on the stock market in the United States (US), were used. By employing the method of Autoregressive Distributed Lags (ARDL) developed by Pesaran et al. (2001). Annual data from the Federal Reserve, World Bank, and International Monetary Fund, from 1986 to 2017 pertaining to the American economy, the results show that both policies play a significant role in the stock market. We find a significant positive effect of real Gross Domestic Product and the interest rate on the US stock market in the long run and significant negative relationship effect of Consumer Price Index (CPI) and broad money on the US stock market both in the short run and long run. On the other hand, this study only could support the significant positive impact of tax revenue and significant negative impact of real effective exchange rate on the US stock market in the short run while in the long run are insignificant. Keywords: ARDL, monetary policy, fiscal policy, stock market, United States

Sign in / Sign up

Export Citation Format

Share Document