Asymmetric Dynamic Conditional Correlation Research Articles

The Impact of COVID-19 Epidemic on the Hedging Islamic and Conventional Stock Markets with Financial Assets

This study investigates optimal hedging ratios for Islamic and conventional stock markets during the COVID-19 pandemic using the DCC (Dynamic Conditional Correlation), ADCC (Asymmetric Dynamic Conditional Correlation), and GO-GARCH (Generalized Orthogonal GARCH) models. The effectiveness of various financial assets as hedges is evaluated, and findings indicate that the DJCOM (Dow Jones Commodity), VISTOXX (Euro STOXX 50 Volatility Index), and VIX (Chicago Board Options Exchange Volatility Index) indices exhibit superior effectiveness across both market types, particularly DJCOM showing exceptional performance during the COVID-19 period. The hedging analysis indicates that the hedge ratios vary and depend upon the hedge instrument included in the portfolio. Furthermore, the empirical results indicate that the global impact of the pandemic diminishes the viability of one of the six assets as a safe haven instrument. In conclusion, these findings provide valuable insights for investors and portfolio managers aiming to utilize Gold, Brent, VISTOXX, VIX, CDS (Credit Default Swap), and DJCOM for portfolio rebalancing to mitigate risks associated with volatile Islamic and conventional stock returns. These conclusions contribute significantly to helping investors adjust their investment strategies more effectively and adapt to changing market conditions.

Downside risk in Dow Jones equity markets: hedging and portfolio management during COVID-19 pandemic and the Russia–Ukraine war

PurposeThis paper aims to examine the dynamic conditional correlation (DCC) and hedging ratios between Dow Jones markets and oil, gold and bitcoin. Using daily data, including the COVID-19 pandemic and the Russia–Ukraine war. We employ the DCC-generalized autoregressive conditional heteroskedasticity (GARCH) and asymmetric DCC (ADCC)-GARCH models.Design/methodology/approachDCC-GARCH and ADCC-GARCH models.FindingsThe most of DCCs among market pairs are positive during COVID-19 period, implying the existence of volatility spillovers (Contagion-effects). This implies the lack of additional economic gains of diversification. So, COVID-19 represents a systematic risk that resists diversification. However, during the Russia–Ukraine war the DCCs are negative for most pairs that include Oil and Gold, implying investors may benefit from portfolio-diversification. Our hedging analysis carries significant implications for investors seeking higher returns while hedging their Dow Jones portfolios: keeping their portfolios unhedged is better than hedging them. This is because Islamic stocks have the ability to mitigate risks.Originality/valueOur paper may make a valuable contribution to the existing literature by examining the hedging of financial assets, including both conventional and Islamic assets, during periods of stability and crisis, such as the COVID-19 pandemic and the Russia–Ukraine war.

The impact of dividend payout policies on real estate market diversification

AbstractAn asymmetric DCC – GJR – GARCH model is applied to the Turkish and US REIT markets in order to estimate the time‐varying correlations between the REIT and stock markets. Using these estimated correlations, we investigate the impact of dividend payouts on the diversification potential of REITs for stock market investors. Our choice of the Turkish REIT market is based on its unique REIT dividend policy, while US data provide a benchmark for comparison. This study has a number of motivations and contributions that make it a worthwhile undertaking. First, we document that REIT dividend policy is related to the correlation between REIT and stock markets. Dividend paying REITs have lower correlations with stock markets, which makes the REIT market a viable portfolio diversifier. Second, we confirm that REITs and stock prices cointegrated more closely due to the 2008 global financial crisis. We additionally document that a similar effect was also present in the correlation during the global Covid‐19 pandemic crisis. It appears that REIT and stock markets become more correlated during times of financial turmoil and diversification opportunities are diminished. Finally, we document that there is a long‐term trend in the time‐varying correlations between REIT and stock markets. Türkiye has been experiencing a negative trend in this regard, while the US has been experiencing a positive trend.

İki Dinamik Koşullu Korelasyon (DCC) Modeli Arasındaki Tahmin Doğruluğunun Karşılaştırılması

This study compares two commonly used DCC-family models to predict the linkage between the US equity and REIT markets within a global minimum-variance portfolio. Equity and REIT portfolios are constructed using variance-covariance matrices, which represent forward-looking covariance information. These matrices are constructed out-of-sample with ex-ante forecasting. By assessing the predictive precision of each model, the study aims to determine which one produces the lowest forecasting errors and performs better economically. According to a statistical comparison, ex-ante correlation forecasts based on the Asymmetric DCC model were more accurate than those based on the standard DCC model. An empirical comparison of the economic performance of these two models in a dynamic portfolio allocation framework reveals that, despite its complexity, the Asymmetric DCC model exhibits similar economic performance characteristics to the standard DCC model. Despite the lack of emphasis on the economic overperformance of the Asymmetric DCC model, investors who recalibrate their portfolios weekly will benefit from reduced forecast errors and the ability to create more efficient portfolios by using an asymmetric model instead of a standard model.

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.

A-DCC GARCH모형을 이용한 주식, 채권 및 외환시장의 변동성 간의 동적 관계

Purpose - This research aims to analyze the interrelationship among the volatility of stock price, interest rate, and exchange rate in Korea. The main topics are volatility spillovers and the asymmetric behaviors of each market’s volatility and correlation.
 Design/Methodology/Approach - This research adopts Engle et al.’s (2006) asymmetric dynamic conditional correlation (A-DCC) GARCH models with student t error distribution. The models are a GJR GARCH model with spillovers and a revised Koutmos (1996) EGARCH model. The full sample is divided into four sub-sample periods, including the global financial crisis and the COVID-19 pandemic.
 Findings - The results show no volatility spillovers among the returns of stock price, interest rate, and exchange rate. However, there are unidirectional spillovers originating from the exchange rate in the global crisis period, and from stock price to exchange rate in the COVID-19 period. Volatility asymmetry is consistently shown in stock price, while the others vary by period. Finally, the asymmetric correlation effects are found only in recent times.
 Research Implications - In the long-run, the volatility spillovers among financial markets are not shown. However, there is also evidence that volatility spillovers are time-varying, intensifying in times of stress. In the global financial crisis period, the exchange rate influences other markets, while in recent the COVID-19 period stock price seems to play that role. Asymmetric volatility is also time-varying, except in stock price, and recently correlation asymmetry is shown very significantly.

Is the Evergrande crisis spilling beyond China?

This study investigates whether Evergrande transmits shocks to regional and global equity markets using the vector autoregressive (VAR), asymmetric dynamic conditional correlation (ADCC), and exponential generalised autoregressive conditional heteroskedasticity (EGARCH) models. The results show that Evergrande has caused notable and enduring shocks to both domestic and foreign equities markets. The spillover test further supports the idea that the Evergrande crisis has spread to important markets. The findings have practical implications for regulators, sovereign wealth managers, institutional and retail investors, and policymakers trying to come up with ways to deal with external shocks.

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.

Volatility in tanker freight markets

Baltic tanker index studies have become vital for the crude oil and petroleum product trade. Volatility has constantly pressured vessel owners and charterers to reduce costs and decide on new ship-building orders. This study attempts to find volatility in the Baltic Dirty Tanker Index and Baltic Clean Tanker Index prices, which are sub-indices of the Baltic Tanker Index. The asymmetric corrected dynamic conditional correlation GARCH model is deployed to find the spillovers and volatility in both time series. The results indicate the strong presence of spillovers at regular intervals. This study helps vessel owners and charterers make appropriate decisions in tanker markets.

Dynamic Correlation between the Chinese and the US Financial Markets: From Global Financial Crisis to COVID-19 Pandemic

As China’s economy and the U.S. economy have shown a definite interaction, there is considerable interest in studying the correlation between the Chinese stock market and the US financial markets. This paper uses an Asymmetric Dynamic Conditional Correlation (ADCC)-GARCH to investigate the correlation between the Shanghai Composite Index (SHCI) and the U.S. financial markets, including SP500, NASDAQ, and US dollar indexes. The empirical results show that the time-varying daily and the lag-one correlation between China and the US stock markets have different performances during global events and national events. Compared with the complicated effect of negative events on the correlation of the stock market, SHCI and USD are negatively correlated with higher negative correlation during the global negative events. In addition, we found Chinese investors are more contagious to the news than American investors, indicating that the Chinese government’s policy are more indicated to Chinese investors. Finally, some policy suggestions are provided, and are beneficial to risk prevention and control, and investment.

Dissecting hedge funds' strategies

This paper dissects the dynamics of the hedge fund industry with four financial markets, including the equity market, commodities, currencies, and debt market by employing a large number of assets from these markets. We employ four main representative hedge fund strategy indices, and a cap-weighted global index to estimate an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model using daily data from April 2003 to May 2021. We break down the performance, riskiness, investing style, volatility, dynamic correlations, and shock transmissions of each hedge fund strategy thoroughly. Further, the impact of commodity futures basis on hedge funds' return is analyzed. Comparing the dynamic correlations during the 2008 global financial crisis (GFC) with COVID-19 pandemic reveals changing patterns in hedge funds' investing styles. There are strong and pervasive shock spillovers from hedge fund industry to other financial markets, especially to futures commodities. An increase in the futures basis of several commodities drives up hedge funds' performance. While hedge fund industry underperforms compared to equity market and commodities, the risk-reward measures show that hedge funds are superior to other markets, and safer than the bond market.

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.

Volatility spillover effects between oil and GCC stock markets: a wavelet-based asymmetric dynamic conditional correlation approach

Purpose This study aims to examine the spillover effects of the mean and volatility between oil prices and stock indices of six Gulf Cooperation Council (GCC) countries (UAE, Kuwait, Saudi Arabia, Qatar, Oman and Bahrain). Design/methodology/approach Over the period 2008–2019, a bivariate VARMA-GARCH-ADCC model was combined with the maximal overlap discrete wavelet transform technique filter to shed light on a wide range of possible spillover effects in the mean and variances of level prices at various time horizons. Findings The authors find that the spillover effects between oil prices and the GCC stock markets are time-varying and spread across various time horizons. Besides, oil prices and stock market indices are directly impacted by their own shocks and variations and indirectly influenced by other price volatilities and wavelet scales. The linkages in volatility spillovers between oil prices and the GCC stock markets occur in the short-term, midterm and long-term horizons. More specifically, the results also show that the asymmetric estimates are statistically significant for the associations between oil prices and each stock market in the GCC countries. This implies that negative shocks play a more vital role than positive shocks in driving the dynamic condition correlations between oil and stock markets under study. Practical implications The significant interrelatedness between oil prices and each stock market in the GCC countries has important implications for investors, portfolio managers, and other market participants. They can use the findings of this research to create the best oil-GCC stock portfolios and predict more precisely the volatility spillover patterns in constructing their hedging strategies. Originality/value In several ways, this study differs from previous research. First, while previous empirical studies of the dynamic link between oil prices and stock markets have focused primarily on developed or emerging markets, the focus of this is on six GCC countries. Second, the linkage between oil prices and stock markets is typically studied at the original data level in the time domain in relevant literature, while frequency information is overlooked. Therefore, the current study examines this relationship from a multiscale perspective. Third, in this paper, to capture a wide range of possible spillover effects in the mean and variance of level prices at multiple wavelet scales, the authors use a VARMA-GARCH-ADCC model in conjunction with wavelet multiresolution analysis. Additionally, this article also applies wavelet hedge ratio and wavelet hedge portfolio analysis at various time horizons.

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.

The dynamic connectedness and hedging opportunities of implied and realized volatility: Evidence from clean energy ETFs

This paper aims to examine dynamic connectedness and hedging opportunities between the realized volatilities of clean energy ETFs and energy implied volatilities through Time-Varying Parameter Vector Autoregression Model (TVP-VAR) and Asymmetric Dynamic Conditional Correlation (ADCC) GARCH models. TVP-VAR analysis results show that dynamic connectedness increases during turbulence periods. We also determine that clean energy ETFs such as PBW, QCLN, SMOG, and TAN are net volatility transmitters. Surprisingly, OVX is a net volatility receiver, especially with the developments after the Paris Agreement in 2016.As a result of the ADCC GARCH analysis, we determine that the conditional correlation between clean energy ETFs and implied volatility ETFs is asymmetric, and negative information shocks increase the conditional correlation. Although OVX is a cheap alternative for hedging long position risks in clean energy ETFs, VXXLE is more effective than OVX in terms of hedging effectiveness. These findings provide insight for individual and institutional investors, and portfolio managers on how negative and positive shocks change the conditional correlation between assets at different levels.

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.

Is Evergrande fiasco set newer ripples in world financial markets?

This paper applies the vector autoregressive (VAR) asymmetric dynamic conditional correlation (ADCC) generalized autoregressive conditional heteroskedasticity (GARCH) model to examine whether Evergrande transmits shocks to local and international equity markets. Our study finds a marked increase in the time-varying correlations between Evergrande and main (real) equity indices' returns. Shocks from Evergrande to local and international equity markets appear to be significant and persistent to the horizon of 10 days. The results have practical implications for retail and institutional investors, regulators, sovereign wealth managers, and policymakers to devise strategies to cope with external shocks.

Volatility spillovers in the dry bulk shipping markets

Baltic Dry Index over the years has witnessed volatility and been an enigma for ship owners and cargo owners. This study tries to investigate the volatility and spillovers in Dry Baltic sub-indices, namely Handymax, Supramax, Panamax and Capesize. The study uses daily data from August 2012 till July 2019 for seven years. The paper contributes to the literature by applying three different multivariate GARCH models, namely the DCC GARCH model, corrected DCC model, and asymmetric corrected DCC GARCH model. Hosking test is applied to find the best model fit and corrected DCC GARCH model is found to be the best fit. The results bring out many interesting spillovers between the Baltic sub-indices and various factors affecting the same are discussed. China trade factor emerges as the major contributor to various spillovers and volatility in the dry bulk market.