Analysing time varying comovements among the US and BRICS stock markets

2022 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Lakshmi P ◽  
S. Visalakshmi ◽  
Jeevananthan Manickavasagam
Keyword(s):  
Stock Markets ◽  
Time Varying ◽  
The Us

Measuring Dependence Between the USA and the Asian Economies: A Time-varying Copula Approach

2019 ◽  
Vol 20 (4) ◽  
pp. 962-980 ◽  
Author(s):  
Shegorika Rajwani ◽  
Dilip Kumar
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Financial Markets ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Tail Dependence ◽  
Time Varying ◽  
The Us ◽  
Asian Economies ◽  
Copula Approach

During the past few years, many of the financial markets have gone through devastating effects due to the crisis in one or the other economy of the world. The recent global financial crisis has triggered dramatic movements in various stock markets which may arise from interdependence or contagion between the markets. This article attempts to measure the contagion between the equity markets of Asia and the US stock market. The countries considered in the Asian group are China, India, Indonesia, South Korea, Taiwan, Hong Kong, Malaysia and Japan. Most of the Asian economies have experienced drastic higher volatility and uncertainty in the financial markets. If the markets are contagious, then the investors will be unable to reap benefits through international diversification of the portfolio. In such a case, the policymakers will further frame policies so that they can insulate themselves from inflicting heavy damage from various crises. To achieve our goal, we make use of the time-varying copula approach which helps us to study the joint behaviour of the series based on their marginal distribution. Time-varying copula approach can also capture the non-linear dependence in the series and exhibits a rich pattern of tail behaviour. Our findings support the contagion between the Asian stock markets and the US stock market during the global financial crisis. This article also highlights that the increased tail dependence is an important factor for the contagion between the Asian stock markets and the US market.

scholarly journals Testing the conditional correlations and volatility spillovers between US and ASEAN Islamic stock markets: A Multivariate GARCH Analysis

2015 ◽  
Vol 2 (1) ◽  
pp. 029
Author(s):  
Muhammad Rizky Prima Sakti
Keyword(s):  
Stock Markets ◽  
Multivariate Garch ◽  
Garch Models ◽  
Time Varying ◽  
Foreign Investors ◽  
Volatility Spillovers ◽  
The Us ◽  
Conditional Correlations ◽  
Multivariate Garch Models ◽  
Empirical Design

This study examines the conditional correlations and volatility spillovers between the US and ASEAN Islamic stock markets. The empirical design uses MSCI (Morgan Stanley Capital International) Islamic indexes as it adopted stringent restriction to include companies in sharia list. By using a three multivariate GARCH models (BEKK, diagonal VECH, and CCC model), we find evidence of returns and volatility spillovers from the US to the ASEAN Islamic stock markets. However, as the estimated time-varying conditional correlations and volatilities indicate there is still a room for diversification benefits, particularly in the single markets. The Islamic MSCI of Thailand, Indonesia, and Singapore are less correlate to the US MSCI Islamic index. The implication is that foreign investors may benefit from the reduction of risk by adding the Islamic stocks in those countries.

scholarly journals The Effects of the COVID-19 Pandemic on Stock Markets, CDS and Economic Activity: Time-Varying Evidence from the US and Europe

2021 ◽  
Author(s):  
Guglielmo Maria Caporale ◽  
Abdurrahman Nazif Catik ◽  
Mohamad Husam Helmi ◽  
Coskun Akdeniz ◽  
Ali Ilhan
Keyword(s):  
Stock Markets ◽  
Economic Activity ◽  
Time Varying ◽  
Activity Time ◽  
The Us

scholarly journals Predicting Contagion from the US Financial Crisis to International Stock Markets Using Dynamic Copula with Google Trends

Mathematics ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 1032 ◽  
Author(s):  
Maneejuk ◽  
Yamaka
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Stock Markets ◽  
Google Trends ◽  
Time Varying ◽  
International Stock Markets ◽  
Leading Indicator ◽  
Dynamic Copula ◽  
The Us ◽  
Us Financial Crisis

The accuracy of contagion prediction has been one of the most widely investigated and challenging problems in economic research. Much effort has been devoted to investigating the key determinant of contagion and enhancing more powerful prediction models. In this study, we aim to improve the prediction of the contagion effect from the US stock market to the international stock markets by utilizing Google Trends as a new leading indicator for predicting contagion. To improve this contagion prediction, the dynamic copula models are used to investigate the structure of dependence between international markets and the US market, before, during, and after the occurrence of the US financial crisis in 2008. We also incorporate the Google Trends data as the exogenous variables in the time-varying copula equation. Thus, the ARMAX process is introduced. To investigate the predictive power of Google Trends, we employ the likelihood ratio test. Our empirical findings support that Google Trends is a significant leading indicator for predicting contagion in seven out of 10 cases: SP-FTSE, SP-TSX, SP-DAX, SP-Nikkei, SP-BVSP, SP-SSEC, and SP-BSESN pairs. Our Google-based models seem to predict particularly well the effect of the US crisis in 2008. In addition, we find that the contribution of Google Trends to contagion prediction varies among the different stock market pairs. This finding leads to our observation that the more volatile the market time-varying correlation, the more useful Google Trends.

scholarly journals Do the Determinants of Non-Performing Loans Have a Different Effect over Time? A Conditional Correlation Approach

2021 ◽  
Vol 14 (1) ◽  
pp. 21
Author(s):  
Mariagrazia Fallanca ◽  
Antonio Fabio Forgione ◽  
Edoardo Otranto
Keyword(s):  
Correlation Coefficients ◽  
Bank Loan ◽  
Time Varying ◽  
Conditional Correlation ◽  
Subprime Mortgage ◽  
Macroeconomic Variables ◽  
Correlation Models ◽  
Mortgage Crisis ◽  
The Us ◽  
Macroeconomic Indicators

Several studies have explored the linkage between non-performing loans and major macroeconomic indicators, using a wide variety of methodologies, sometimes with different results. This occurs, we argue, because these relationships are generally derived in terms of correlation coefficients evaluated in certain time spans, which represent a sort of average level of correlations. However, such correlations are necessarily time-varying, because the relationships between bank loan indicators and macroeconomic variables could be stronger during particular periods or in correspondence with important economic events. We propose an empirical exercise using dynamic conditional correlation models, with constant and time-varying parameters. Applying these models to quarterly delinquency rates and an array of macroeconomic variables for the US, for the period 1985–2019, we find that the correlation is often negligible in this period except during periods of economic crises, in particular the early 1990 crisis and the subprime mortgage crisis.

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