Multivariate GARCH Analysis Research Articles

Are Indian markets insulated from the impact of cryptocurrencies? Unveiling the volatility linkages through multi‐index dynamic multivariate GARCH analysis

AbstractThis paper investigates the dynamic relationships between the volatility of Bitcoin and major Indian stock market indices. Employing a dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) model, we explore how volatility shocks and information flow influence the correlations between these asset classes. Our findings reveal a key characteristic: volatility spillovers tend to be short‐lived, indicated by a relatively low DCC‐GARCH parameter (dcca1). This suggests that while a surge in volatility in one market might lead to a temporary increase in correlation with the other, this heightened correlation is unlikely to persist for extended periods. However, the model also highlights a high DCC‐GARCH parameter (dccb1), signifying that the correlations themselves are responsive to new information. This implies that volatility linkages can adjust rapidly in response to market events or economic data releases. To enhance accessibility for a broad audience, we translate these findings into economic intuitions. We illustrate how the model can be interpreted through real‐world examples, such as the impact of sudden policy changes in India or global market flash crashes. By understanding the short‐lived nature of volatility spillovers and the responsiveness of correlations, investors in the Indian markets can make more informed decisions when considering the potential influence of Bitcoin's volatility while contributing to a deeper understanding of the dynamic interactions between cryptocurrency and traditional financial markets in the Indian context.

Contagion effect of migration fear in pre and European refugee’s crisis period: evidence from multivariate GARCH and wavelet empirical analysis

To test the contagion effect of fear migration between countries, and to show its causality direction, our paper contributes to the economic literature by providing a new study based on migration fear indices quarterly data of France, Germany, United Kingdom and United States spanning period 1990–2019. Our empirical strategy is based on dynamic conditional correlation GARCH model and continuous wavelet transform analysis. Our results show a significant contagion effect of fear migration between the selected countries in pre and at the European Refugees crisis. The main findings of this work are changes level of conditional correlation in the two subsample periods, and changes in the arrow’s directions in red space of the phase difference between each two fear migration series. These findings indicate that European Refugees crisis changes the relationship between European Union countries and USA, and the Brexit changes the European people behavior towards migrants and refugees. Our findings offer a new directions and tracks in the international relations to the policy makers, moreover it calls into question the various studies examining economic interdependence and the contagion effect of financial crises and policies events on the different markets.

Multivariate Garch Analysis of Selected Nigerian Economic Data

Aims: The aim of this study is to examine multivariate GARCH modeling of selected Nigerian economic data.
 Study Design: The study used monthly data of Nigerian crude oil prices (dollar Per Barrel), consumer price Index rural, maximum lending rate and prime lending rate.
 Methodology: This work covers time series data on crude oil prices, consumer price Index rural, maximum lending rate and prime lending rate extracted from Central Bank of Nigeria (CBN) from 2000 to 2019. In attempt to achieve the aim of the study, quadrivariate VECH and DCC model were applied. 
 Results: The results confirmed that returns on economic data were correlated. Also, diagonal multivariate VECH model confirmed one of the properties that it must be ‘positive semi-definite’,
 And the DCC confirmed also the positive-definite conditional-variance.
 Conclusion: From the results obtained, it was confirmed that there exists a strong confirmation of a time-varying conditional covariance and interdependence among Nigeria economic data. As for cross-volatility effects, past innovations in crude oil price have utmost control on future volatility of returns on economic data. It was also confirmed that time varying covariance displays among these economic data and lower degree of persistence and based on Model selection criteria using the Akaike information criteria (AIC) has 17.485 for diagonal VECH while for DCC has 17.509 AIC which makes VECH model better fitted.

Volatility Modelling and Dynamic Linkages between Pakistani and Leading Foreign Stock Markets: A Multivariate GARCH Analysis

It is essential for financial institutions and academicians to understand volatility spillover and financial market returns. However, previous studies examined the effects of direct spillover only and ignored those of the newly emerging stock markets. Therefore, this study attempts to estimate the time-varying volatility of Pakistani and leading foreign stock markets. It also tries to explore the direct and indirect volatility spillover effect between Pakistani and eight leading foreign stock markets. Daily data were used from nine international equity markets (KSE 100, NIKKEI 225, HIS, S&P 500, NASDAQ 100, DOW JONES, GADXI, FTSE 350 and DFMGI) for the period between 2005 and 2016. The univariate GARCH and GJR models were employed for analysing volatility, and the multivariate GARCH Diagonal BEKK model was used to explore direct and indirect volatility spillover effects. In order to analyse the volatility spillover effect during and after the global financial crisis period, the data were categorised into two periods: between 2005 and 2009 and between 2010 and 2016. The Chow break-point test was also employed to identify structural breaks in return series due to global financial crises. Direct and indirect spillover effects were found between KSE100, S&P 500, NASDAQ 100, DOW JONES and DFMGI. Keywords: Volatility, Spillover, Equity Market, Financial Crisis and GARCH

Which one is more informative in determining price movements of hedging assets? Evidence from Bitcoin, gold and crude oil markets

In this paper, we aim to identify which one is more informative in determining the price fluctuations in a system consisting of three commonly used hedging assets, i.e. Bitcoin, gold and crude oil. Multifractal detrended cross-correlation analysis (MF-DCCA), multivariate GARCH (MVGARCH) and information share (IS) analysis are utilized to achieve this purpose. The empirical results show that, firstly the MF-DCCA suggests that obvious multifractality exists in the cross-correlations among the three hedging assets and Bitcoin is more susceptible to price fluctuations from gold and crude oil markets. Secondly the results from DCC-MVGARCH model indicate that, although significant volatility spillovers are detected among the three assets, the spillover effects from gold and crude oil markets to Bitcoin market are much stronger than other spillovers. Additionally, the dynamic correlations between gold and crude oil markets are almost positive, while those between Bitcoin and gold, and those between Bitcoin and oil markets are nearly negative during the whole sample periods. Finally, the information share analysis further confirms that gold market dominates crude oil and Bitcoin markets in absorbing new information and contributes more explanatory power in price movements/variance of the hedging assets system.

Volatility in frontier markets: a Multivariate GARCH analysis

PurposeThe purpose of this paper is to analyze the existence of volatility spillover effect in frontier markets. This study also examines whether any linkages exist among these markets or not.Design/methodology/approachMonthly data of regional frontier markets, from 2009 to 2016, are analyzed using Multivariate GARCH (BEKK and Dynamic Conditional Correlation (DCC)) models.FindingsThe result of cointegration test shows that the sample frontier markets are not linked in long run, and Granger causality test reveals that the markets under consideration do not cause each other even in the short run. BEKK test says that the effect of the arrival of shock from the own market does not last for longer, whereas shock from other markets lasts with the stronger persistence, and according to DCC test, the volatility spillover exists for all the markets.Practical implicationsThe results of present study suggest that the frontier markets are not cointegrated in the long run as well as in the short run, which opens the doors for long-term investments in these markets in future, which may lead to decent returns. Long-term investors may draw the benefits from including the financial assets in their portfolios from these non-integrated frontier markets; nevertheless, they have to consider and implement diversification and hedging strategies during the period of financial turmoil, so as to protect themselves against economic and financial distress.Originality/valueSignificant work has been done on developed, developing and emerging markets but frontier markets are not explored much so far. This paper is an attempt to see the status of frontier stock markets as potential financial markets for diversification benefits.

Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis

This study investigates the presence of return and volatility spillover across EAGLEs stock markets, namely China, India, Indonesia, Russia, Brazil, Turkey and Mexico. A multivariate GARCH DCC and BEKK frameworks are employed by classifying the total sample (i.e. from January 2002 to February 2017) into three sub-periods according to the 2008 Global financial crisis. The result shows a significant and positive spillover effect among stock markets in the pre-crisis and post-crisis periods. The transmission of spillover from external markets intensely influenced by US stock market. Furthermore, strong inter-connection and channel of spread observed among EAGLEs stock market during the post-crisis period.

Financial integration between sukuk and bond indices of emerging markets: Insights from wavelet coherence and multivariate-GARCH analysis

Some investors strive for capital appreciation while others may follow capital preservation strategies in terms of investment. In relation to that, Islamic finance receives a lot of attention from institutional investors and asset managers in the search for higher returns, lower correlation and growth potentiality. Therefore, it would be meaningful to investigate whether sukuk can offer any advantage in terms of global diversification. In such context, we have examined the volatilities and correlations of bond indices of emerging counties such as South Korea, Singapore, China, India, Indonesia, and Malaysia with Thomson Reuters BPA Malaysia Sukuk Index by applying wavelet coherence and Multivariate GARCH analyses. The data covers the period January 2010 to December 2015. We conclude that the sukuk market offers effective portfolio diversification opportunities for fixed income investors of the mentioned sample countries. Global and regional investors can avail the benefits of portfolio diversification through investment in sukuk markets but portfolio diversification is not feasible domestically. As a practical implication to the finance industry, the outcome of this research provides a framework for investigating sukuk market integration of several emerging bond markets which serve as an important platform for conducting further research.

Does Islamic equity investment provide diversification benefits to conventional investors? Evidence from the multivariate GARCH analysis

PurposeThe purpose of this paper is to quantify the extent to which the Malaysia-based equity investors can benefit from diversifying their portfolio into the conventional and Islamic Southeast Asian region and the world’s top ten largest equity indices (China, Japan, Hong Kong, India, the UK, the USA, Canada, France, Germany and Switzerland).Design/methodology/approachThe multivariate GARCH-dynamic conditional correlation is deployed to estimate the time-varying linkages of the selected conventional and Islamic Asian and international stock index returns with the Malaysian stock index returns, covering approximately eight years daily starting from 29 June 2007 to 30 June 2016.FindingsIn general, in terms of volatility, the results indicate that both Asian and international Islamic stock indices are more or less volatile than its conventional counterparts. From the correlation analysis, we can see that both the conventional and Islamic MSCI indices of Japan provide more diversification benefits compared to Southeast Asian region, China, Hong Kong and India. Meanwhile, in terms of international portfolio diversification, the results tend to suggest that both the conventional and Islamic MSCI indices of the USA provide more diversification benefits compared to the UK, Canada, France, Germany and Switzerland.Originality/valueThe findings of this paper may have several significant implications for the Malaysia-based equity investors and fund managers who seek for the understanding of return correlations between the Malaysian stock index and the world’s largest stock market indices in order to gain higher risk-adjusted returns through portfolio diversification. With regard to policy implications, the findings on market shocks and the extent of the interdependence of the Malaysian market with cross-border markets may provide some useful insights in formulating effective macroeconomic stabilization policies in the efforts of preventing contagion effect from deteriorating the domestic economy.

Commodity-price volatility and macroeconomic spillovers: Evidence from nine emerging markets

The recent decade has witnessed wild swings in global commodity prices, with large increases preceding the Global Financial Crisis and steep declines following the crash. Many emerging markets find themselves destabilized by these fluctuations, not only when price increases lead to currency appreciations and reduced competitiveness, but also when price decreases cause capital outflows and deteriorations in the balance of payments. This study examines the volatility processes of six major commodity prices, before applying Multivariate GARCH analysis to examine spillovers among important commodity prices and output, exchange rates, interest rates and inflation in major emerging markets. While each commodity and each country behaves differently, we find that Chile is most closely tied to the copper price, and Indonesia to oil and tin, while neighbors such as Brazil and the Philippines are less affected. Perhaps surprisingly, Russia is found to be highly insulated from fluctuations in world oil prices.

The Short-Run Pricing Behavior of Closed-End Funds: Bond vs. Equity Funds

This paper investigates the short-run relationship between closed-end fund prices and their net asset values. In particular, we document three systematic differences between the short-run pricing behaviors for stock and bonds funds. For equity funds, we show that returns processes for both prices and asset values have characteristics of a random walk, while bond funds returns are more predictable. Similarly, multivariate GARCH analysis establishes the existence of stronger news and volatility spillover effects between the fund price and the net asset value for bond funds than for stock funds. Finally, we find significantly weaker dynamic conditional correlations between the fund price and its fundamental value for bond funds after the Lehman Brothers failure, whereas no such evidence is found for stock funds. To explain these findings, we propose a mechanism based on bond market illiquidity.

A Multivariate GARCH Analysis on International Stock Market Integration: Korean Market Case

Financial integration is a phenomenon in which global financial markets are closely connected with each other. This article investigates the integration of Korean stock market with other stock markets using a multivariate GARCH analysis. We chose total seven countries including Korea for this paper based on the amount of export and then we chose major stock indices which can be thought as representative stock markets of those countries. The empirical analysis has shown that countries’ financial integration.

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

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.

Transfer of Risk in Emerging Eastern European Stock Markets: A Sectoral Perspective

This paper studies the market integration of Poland, Hungary and the Czech Republic by utilizing the multivariate GARCH analysis of Engle and Kroner (1995) for which a BEKK representation is adopted. We investigate the transmission of the US subprime crisis across Poland, Hungary and the Czech Republic in a sectoral setting. In addition, we attempt to identify whether the three emerging Eastern European countries have become more integrated after their EU accessions in 2004, in a regional setting. Our results clearly indicate the existence of direct linkages between different stock market sectors with respect to returns and volatilities. We found that the transmission of equity shocks between markets has increased after the EU accession in 2004. Notably, the intra-industry contagion in emerging Europe has increased after this accession. Our findings have significant implications for asset pricing and portfolio selection for international financial institutions and financial managers.

Transmission Of The Subprime Crisis: Evidence From Industrial And Financial Sectors Of BRIC Countries

Although, there is an apparent consensus about the contagion effects of the current US subprime crisis. However, the transmission and repercussions of US subprime crisis, as well as the nature of the transformation suffered by different economic sectors between the US and other markets are such empirical questions that have not been dealt with comprehensively, yet. In this paper, by utilizing the multivariate GARCH analysis of Engle and Kroner (1995) for which a BEKK representation is adopted, we examine the transmission of the US subprime crisis across BRIC financial markets. Moreover, to identify the extent of contagion, we also inspect the diffusion of US subprime crisis to BRIC equity markets financial and industrial sectors. We found interesting evidence of volatility spillovers from US financial sector to all the BRIC markets financial sectors both in the full sample and crisis period. Similarly, except Chinese industrial sector, we observe contagion effects from US to Brazilian, Russian and Indian equity markets industrial sectors. Our results exhibit direct linkage for both returns and volatility between the US equity market and the BRIC markets. Equity markets of Russia and India, however, were found hardly hit during the crisis period among the BRIC countries. Finally, we found no support for the decoupling view while investigating the fastest growing emerging markets, the BRIC countries.

Multivariate GARCH analysis of Fannie Mae, Freddie Mac, and American International Group: Did the short-selling ban reduce systemic return-risk?

This paper uses a multivariate GARCH framework to examine how the 2008 moratorium on short-selling affected the systemic return-risk across three firms at the center of the subprime mortgage crises: Fannie Mae and Freddie Mac, the two largest buyers of US home mortgages; and American International Group, a major insurer of mortgage-backed securities. Wald coefficient tests indicate shocks in prior day returns manifest less systemic return-risk under the short-selling ban, thus coinciding with the regulatory intentions of the United States Securities and Exchange Commission (SEC), to “moderate the sudden and excessive fluctuations in securities prices.” The findings also agree with prior work in observing abnormal-negative returns for heavily shorted firms, and diminished negative skewness and kurtosis under binding short-selling constraints.

Wavelet-based multi-resolution GARCH model for financial spillover effects

Abstract This study proposes a wavelet-based multi-resolution BEKK-GARCH model to investigate spillover effects across financial markets. Compared with traditional multivariate GARCH analysis, the proposed model can identify or decompose cross-market spillovers on multiple resolutions. Taking two highly correlated indices, the NASDAQ (U.S.) and TWSI (Taiwan composite stock index) for analysis, the empirical results show that the NASDAQ returns strongly predict the movements of TWSI on the raw data level, but via wavelet-based multi-resolution analysis we find that the prediction power unevenly spreads over each time scale, and the spillover patterns are totally different as that revealed on the raw data level. The direction and magnitude of return and volatility spillovers significantly vary with their time scales. Considering the fact that heterogeneous groups of investors trade on different time horizons, the results of this study help investors to uncover the complex pattern of return and volatility spillovers on their own horizon, and make a good hedge on their risk.

Multivariate GARCH Analysis of Fannie Mae, Freddie Mac, and American International Group: Did the Short-Selling Ban Reduce Their Systemic Risk?

Multivariate GARCH Analysis of Fannie Mae, Freddie Mac, and American International Group: Did the Short-Selling Ban Reduce Their Systemic Risk?

Money growth, uncertainty and macroeconomic activity: a multivariate GARCH analysis

The impact uncertainty has on money growth has received much attention in recent years and is an issue of critical importance to central banks, particularly for those, such as the European Central Bank (ECB), which place a strong emphasis on monetary analysis in monetary policy formulation. Some recent papers examining this issue use ad hoc estimates and measure variability rather than uncertainty. We employ a multivariate GARCH model, which measures uncertainty by the conditional variance of the data series, to investigate whether macroeconomic uncertainty and monetary uncertainty Granger-cause changes in real money. The estimated model also allows us to investigate how monetary uncertainty impacts economic activity. We find that macroeconomic uncertainty impacts positively on US real M2 growth over a two-year horizon but that monetary uncertainty does not cause changes in real M2. Instead, our results indicate that real money growth causes monetary uncertainty. Monetary uncertainty is found to have a negative effect on real economic activity and on macroeconomic uncertainty. We conclude by discussing the implications of these results and the methodological approach used for institutions such as the ECB that give monetary analysis a prominent role in their monetary policy strategy.

Dynamic Interactive Cycles during the 2008 Financial Crisis

This paper focuses on the analysis of the 2008 financial crisis and how it affects the global financial markets. We analyze three major markets (US, UK, and ASIA) that are represented by the levels of three broad stock indices S&P 500, FTSE 100 and Hang Seng respectively. Our methodology is based on cointegration analysis and Granger causality test in order to examine the interaction between the markets (information flows). Additionally, we study the volatility transmission based on multivariate GARCH analysis. We find significant changes in information flows before and during the financial crisis.