Asymmetric Dynamic Conditional Correlation Model Research Articles

AI companies' strategies with traditional vs. digital assets amid geopolitical and banking crises

The financial industry evolves rapidly, offering numerous opportunities but also introducing inherent risks that require careful navigation by institutions. This paper explores the performance of traditional and digital assets as tools for hedging, diversification, and safe-haven strategies during the Russian-Ukrainian crisis and the Silicon Valley Bank (SVB) collapse. Utilizing daily data from April 30, 2021, to September 15, 2023, and employing the Asymmetric Dynamic Conditional Correlation (ADCC) model, which combines four Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models and two residual distributions, we conduct a comprehensive analysis. The results indicate that Bitcoin's role as a safe haven is limited during the geopolitical crisis, impacting specific stocks, while gold's effectiveness varies. Digix Gold (DGX) demonstrates robust safe-haven properties, and Paxos Gold (PAXG) proves notably effective for certain stocks. Before the SVB crisis, gold primarily acts as a diversifier but later emerges as a significant safe haven during the banking crisis. These findings provide valuable insights to portfolio managers, emphasizing the importance of adaptive asset allocation in addressing financial uncertainties.

Time-Varying Correlations between JSE.JO Stock Market and Its Partners Using Symmetric and Asymmetric Dynamic Conditional Correlation Models

Time-Varying Correlations between JSE.JO Stock Market and Its Partners Using Symmetric and Asymmetric Dynamic Conditional Correlation Models

VOLATILITY AND CONDITIONAL MARKET CORRELATIONS IN PERIODS OF CRISIS

The study analyzed co-movements and contagions in Latin American stock markets, testing the benefits of diversification in times of crisis. The period investigated was from January 2000 to December 2018, testing the correlations through Asymmetric Dynamic Conditional Correlation models. The results indicate that correlations increase in periods of crisis in all markets and sectors, thus reducing the benefits of portfolio diversification. It was also possible to observe that the increase in correlations during an internal crisis is of smaller magnitude than the increase in correlations during external crises, such as Subprime.

Analyzing commodity futures and stock market indices: Hedging strategies using asymmetric dynamic conditional correlation models

The focus of this paper is on analyzing the behavior of commodity futures indices and stock market indices in terms of price volatility and hedging. Specifically, we explore the weekly hedging strategies generated by two types of asymmetric dynamic conditional correlation (DCC) processes: return-based and range-based. We evaluate the effectiveness of these strategies for both short and long hedgers, using measures such as semi-variance, low partial moment, and conditional value-at-risk. Our findings reveal that, in general, the range-based DCC model is more effective than the return-based DCC model for hedging purposes.

Dynamic connectedness and optimal hedging strategy among commodities and financial indices

This study looks at the best portfolio strategy for mitigating the risk associated with the MSCI ACWI & Frontier Markets Index, as well as the volatility spillovers between commodity markets and certain financial markets. Therefore, we empirically explore the connectedness among three financial indicators and five product groups using the framework of Diebold and Yilmaz (2012), which is based on a vector autoregressive process and variance decomposition of prediction errors, between 31 May 2002 and 30 July 2021. We also investigate the best hedging instrument(s) for the MSCI ACWI & Frontier Markets Global Index by combining the Asymmetric Dynamic Conditional Correlation (ADCC) model with the risk reduction index and the hedging ratios. Our empirical findings highlight the importance of volatility spillover effects across financial markets, which is not the case for commodity markets with low volatility externalities. Furthermore, the first markets appear to be net transmitters of volatility, whereas the second markets appear to be net receivers. Using the approach of Kroner and Sultan (1993), we show that the least risk portfolio is a portfolio that combines the MSCI ACWI & Frontier Markets Global Index with financial indices related to socially responsible and irresponsible investing.

The study of co-movement risk in the context of the Belt and Road Initiative

This study examines the potential risks of the Belt and Road Initiative (BRI) on the comovements of international stock markets. Using stock markets of related countries as a case study, we implement an asymmetric dynamic conditional correlation model to estimate dynamic conditional correlations between the China stock market and related stock markets. The results of testing the structural changes show that the breakpoints of dynamic conditional correlations are within the announcement dates of BRI, documenting that the comovements between China's stock market and related stock markets significantly increase following BRI actions. The positive comovements lead to a stronger volatility spillover effect when China's stock market is more volatile. To investigate the downside risk of BRI actions, we evaluate the performance of portfolio strategies by introducing gold. The findings show that portfolios composed of gold and stock markets perform well. These results suggest that using gold as a hedge could effectively increase the diversification benefits and reduce downside risk.

MEASURING CONTAGION BETWEEN ENERGY AND STOCK MARKET DURING FINANCIAL CRISIS: ASYMMETRIC DYNAMICS IN THE CORRELATIONS

This paper deals with the study of the Asymmetric Dynamic Conditional Correlation (ADCC) model developed by Cappiello et al. (2006). The A-DCC models carry out better than the non-asymmetric ones. The methodological design is an appropriate multivariate vector and autoregressive exponential GARCH (M-VAR-EGARCH) process which investigate the nature of the volatility and return spillover mechanism across markets. This article examines the dynamic linkages between the stock market and oil price in the US and the Euro-Zone from January 2, 2004 to July 5, 2013. The findings support the existence of a contagion effect during the Greek debt crisis but not the subprime crisis. The correlations between oil prices and stock return of the financial market reveal a certain degree of interdependence among oil market that is lower during the debt crisis.

Hedge and safe haven properties during COVID-19: Evidence from Bitcoin and gold

The COVID-19 pandemic has caused an unprecedented human and health crisis. The measures taken to contain the damage caused a global economic slowdown. Investors face liquidity pressures resulting from the general downturn in the financial markets, and might change their risk appetite. This paper reassesses the safe haven property of gold as a traditional asset, and Bitcoin which is gradually imposing itself as a new class of asset with unique characteristics. The empirical results, applied on major world stock market indices and currencies, and based on the multivariate asymmetric dynamic conditional correlation model, show the effectiveness of Bitcoin and gold as hedging assets in reducing the risk of international portfolios. Moreover, the analysis provides evidence that during the COVID-19 pandemic, gold is a weak safe haven for the considered assets, while Bitcoin cannot provide shelter due to its increased variability.

The role of oil as a determinant of stock market interdependence: The case of the USA and GCC

This paper focuses on oil as a key determinant in US-GCC stock market interdependence. The analysis uses monthly data over the period from January 2003 to December 2019. The interdependence between the US and GCC is established using the Asymmetric Dynamic Conditional Correlation model. We then investigate the impact of both oil and a range of macroeconomic variables on the nature of the correlation. Our results find that oil returns and volatility significantly explain changes in the US-GCC correlation. Echoing the recent financialization of oil, sub-sample analysis reveals the increasing importance of oil in determining interdependence. Further, the effect of oil displays asymmetric tail dependence with the correlation, where the oil impact is more pronounced in the upper tail of the correlation's conditional distribution. Both oil and financial shocks coincide with structural breaks in the correlation series. A series of robustness tests, including alternative correlation and oil measures continue to support the results.

FLIGHT-TO-QUALITY OR CONTAGION DURING U.S. SUBPRIME CRISIS: EVIDENCE FROM VIETNAM’S FINANCIAL MARKETS

Abstract: This study investigates whether contagion or flight-to-quality occurred in Vietnam’s financial markets during the US subprime crisis in 2007. We apply the asymmetric dynamic conditional correlation model (ADCC-GARCH (1,1)) to daily stock-index and bond index returns of Vietnam’s and US stock markets. We test for contagion or flight-to-quality by using a test for difference in dynamic conditional correlation means. The results show a contagion between the US and Vietnam’s stock markets, confirming the widespread influence of the US stock market on a young market like Vietnam. This result suggests a low benefit from diversification for investors holding portfolios containing assets in Vietnam’s stock market and US stock market during the crisis. Moreover, the relationship between Vietnam’s stock and bond markets represents a flight-to-quality during the US subprime crisis. This finding shows that the investors tend to hold less risky assets, i.e., bonds, instead of stocks during this turbulent period in Vietnam.Keywords: international financial contagion, flight-to-quality, Vietnam, US subprime crisis, ADCC-GARCH

Co-movements between the British pound, the euro and the Japanese yen: the Brexit impact

PurposeThe purpose of this paper is to analyze the Brexit effect – pre-Brexit and post-Brexit referendum periods – on the co-movements between the British pound (GBP), the euro (EUR) and the yen (JPY) against the US dollar (USD).Design/methodology/approachTo ascertain the asymmetric behavior of dynamic correlations, the authors use the dynamic conditional correlation (DCC) model, the asymmetric dynamic conditional correlation (A-DCC) model and the diagonal BEKK model assuming Gaussian and Student’stdistribution. Several dummy variables have been included in order to identify the main periods related to Brexit.FindingsFindings show a negative impact of the pre-Brexit referendum period on the correlation between GBP and EUR, while there is no significant effect on GBP–JPY and EUR–JPY pairs. The loss of correlation in the GBP–EUR pairing has not recovered during the post-Brexit referendum period, which could be attributed to the uncertainty about the final impact of Brexit on British and Eurozone economies.Practical implicationsThe loss of correlation in the GBP–EUR pair has important implications for individual investors, portfolio managers and traders with respect to hedging activities, international trading and investment strategies.Originality/valueThe results are the first to address how Brexit has impacted on the co-movements between exchange rates using different multivariate models that allow for correlations to change over time.

Asymetrie během finančních krizí: asymetrická volatilita převyšuje důležitost asymetrické korelace

We have tested the stability of parameters loading the asymmetric behaviour of the correlation and the importance of this behavior on the portfolio selection. In this paper, we have analyzed the following time series S&P index, gold and CME 5-Year Treasury Note Futures during the most important crisis from 1992 to 2009. The methodology is based on the dynamic conditional correlation model and its asymmetric volatility and asymmetric correlation extensions. The stability of parameters was tested by t-test applied on the rol ling windows data. The information importance of asymmetric volatility and correlation was tested by global minimum variance portfolio. The results suggest that the parameters loading the asymmetric behavior of the correlation are not stable for the analyzed time series during the financial crisis. With one exception we have found out that global minimum variance portfolio based on the dynamic conditional correlation model with asymmetric volatility is significantly less volatile than the global minimum variance portfolio based on the asymmetric dynamic conditional correlation model.

Financial illness and political virus: the case of contagious crises in the Eurozone

This paper investigates the volatility spillover effects from the southern to northern part of the Eurozone during the sovereign debt crisis. Focusing on different phases of the crises, we propose using the dynamic conditional correlation model and the BEKK model to identify possible linkages during the period of 2005–2015. The findings showed that both models behave satisfactorily and are flexible in presenting spillover effects. However, regarding conditional correlations, the asymmetric dynamic conditional correlation model seems to fit better. Additionally, Spain and Italy can significantly damage all strong northern economies, while Greece’s negative shocks are capable of co-moving the French index. Finally, France is the most correlated country within the southern Eurozone.

Dynamic correlations between BRIC and U.S. stock markets: The asymmetric impact of volatility expectations in oil, gold and financial markets

This study investigates the impacts of volatility expectations in oil, gold, currency and the U.S. stock markets on time-varying conditional correlations between BRIC and U.S. stock markets. We use asymmetric dynamic conditional correlation and dynamic conditional correlation models to derive the time-varying relationships. We then examine the dynamic conditional correlations using quantile regressions for a detailed analysis of dependence structure containing non-linear and asymmetric interactions. Our results show that the impacts of volatility expectations in U.S. stock, gold, and oil markets on the correlations are asymmetric based on the level of correlations. Depending on the level of correlations, interdependence between the markets is driven by risk perceptions in both financial and non-financial markets. Our findings have important implications for determining international investment strategies.

Information linkages among emerging equity markets—an empirical study

In this paper, we examine the price discovery and volatility spillovers among equity markets of eight emerging market economies (EMEs)—Brazil, China, India, Indonesia, Mexico, Russia, South Africa and Turkey—from January 2003 to July 2014, covering the 2007–2009 global financial crisis (GFC). The analysis is conducted for pre-crisis, crisis and post-crisis periods. The results of price discovery indicate that Brazil leads in pre-crisis period while South Africa leads during crisis period. No single market is dominant in the post-crisis period and across the full sample period as well. Dynamic cointegration test largely confirms the findings from the static Johansen’s cointegration test. Employing asymmetric dynamic conditional correlation and BEKK-GARCH models, we find that volatility spillovers reduced among the sample markets over time. The empirical results suggest that the information linkages among the sample EMEs’ equity markets weakened during the GFC and did not revert to stable period levels after the crisis. The findings have implications for policy makers and investors.

Stock Market Integration in China: Evidence from the Asymmetric DCC Model and Copula Approach

We investigate the dynamic dependence structure between the daily stock returns of the A and B shares of the Shanghai and Shenzhen stock markets in China, using time-varying conditional copula and asymmetric dynamic conditional correlation models. We find that the Shanghai market’s A and B shares are more integrated than those of the Shenzhen market. Further, the dynamic dependences between the shares for both markets are asymmetric and lower-tailed, and an increasing correlation with the opening up of the B shares market to Chinese citizens around 2001 is evident.

Tail risk and the return-volatility relation

This article brings new insights on the time-varying leverage and feedback effects in equity markets. The lead–lag return-volatility relation is examined by resorting to time-varying asymmetric dynamic conditional correlation models that allows for asymmetry (ADCC) and spillovers (ADCCX) with tail risk lagged variables (SKEW, VVIX) from 1990 to 2014. Empirical findings reveal that the dynamic leverage effect is the most influential in driving equity markets. The volatility of volatility (VVIX) exhibits a significant influence on the dynamic feedback effect only.

PAIN AT THE PUMP: IS THERE AN ASYMMETRIC INFLUENCE OF OIL VOLATILITY ON GASOLINE VOLATILITY IN FRANCE?

We investigate, for the first time, the relationship between gasoline volatility and crude oil volatility. We aim to examine if the so-called asymmetric relationship between gasoline and crude oil prices holds for volatility. The approach employed is based on the asymmetric dynamic conditional correlation model as applied to the US WTI oil volatility and the French Super Carburant 95 gasoline volatility from 1990 to 2014.The results reveal that gasoline volatility tends to be overreactive to changes in crude oil volatility. Moreover, it appears that the government taxation policy might amplify the gasoline volatility

A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection

A Bayesian non-parametric approach for modeling the distribution of multiple returns is proposed. More specifically, an asymmetric dynamic conditional correlation (ADCC) model is considered to estimate the time-varying correlations of financial returns where the individual volatilities are driven by GJR-GARCH models. This composite model takes into consideration the asymmetries in individual assets’ volatilities, as well as in the correlations. The errors are modeled using a Dirichlet location–scale mixture of multivariate Normals allowing for a flexible return distribution in terms of skewness and kurtosis. This gives rise to a Bayesian non-parametric ADCC (BNP-ADCC) model, as opposed to a symmetric specification, called BNP-DCC. Then these two models are compared using a sample of Apple Inc. and NASDAQ Industrial index daily returns. The obtained results reveal that for this particular data set the BNP-ADCC outperforms the BNP-DCC model. Finally, an illustrative asset allocation exercise is presented.

Are global systematic risk and country-specific idiosyncratic risk priced in the integrated world markets?

Empirical evidence showing significant effects of local factors on international equity returns while failing to find significant effects from global systematic risk seems counter-intuitive in today's integrated world markets. This paper uses the conditional second moments estimated from an asymmetric dynamic conditional correlation model to measure the time-varying world beta and country-specific idiosyncratic risks, and tests the relationship between country-level index returns and world beta risk conditioned on positive and negative world market returns. The results show that the conditional dynamic world beta risks significantly predict the cross-country variation in expected index returns, while country-specific risk is not significantly priced.