Net Directional Connectedness Research Articles

How geopolitical risk drives spillover interconnectedness between crude oil and exchange rate markets: Evidence from the Russia-Ukraine war

This study examines the dynamics of spillover interconnectedness between oil and exchange rate market in the purview of the Russia-Ukraine war. The study employed the Time-Varying Parameters Vector-Autoregression (TVP-VAR) model to investigate the connectedness between the aforementioned markets in three segments: before, during and the full sample. The TVP-VAR results reveal two exciting findings: First, the market connectedness increased from pre-war to higher levels. Second, the pattern of risks and opportunities transmission across these markets can change in the outbreak of geopolitical conflict. Furthermore, the study employed causality-in-quantile and quantile regression methodologies to formally establish that geopolitical risk may drive market risks and opportunities spillover. The causality-in-quantile test suggests that geopolitical risk could predict the total and net directional spillover behaviour between the markets before and during the war. On the other hand, the quantile regression results revealed that geopolitical risks have varying and substantial relationships with the total and net directional connectedness of the oil and exchange rate markets before and during the war. These findings have important policy implications for policymakers and market participants.

Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities

This paper investigates the total and net directional connectedness of the energy market and currency market amid volatilities (local and international) of BRICS for the period May 7, 2012 to March 31, 2022. The Time-varying parameter Vector Autoregression (TVP-VAR) connectedness approach is specifically employed. We reveal that the average value of the total connectedness index (TCI) is 46.91%, for the specific network of energy commodities, currency rates, and volatilities. Also, from the averaged dynamic connectedness, the global energy commodity index demonstrated the most transmitter of shocks. Conversely, BRICS currency markets (except for Brazilian Rubble) and most implied energy volatilities and realised exchange rate volatilities were net receivers of shocks. Moreover, the total connectivity indices were seen to vary significantly during the study sample period with strong susceptibility to crisis periods, especially, the COVID-19 pandemic. We advocate that most volatilities were consistent net transmitters across time as indicated by the net directional connectedness. The findings imply that in a network of energy commodities, exchange rate, and volatilities, risk minimisation is elated to boost investors’ confidence across time.

INVESTMENT DYNAMICS OF SINGAPORE STOCK AND REAL ESTATE MARKETS

This paper examines investment dynamics of six major Singapore asset markets (general stock, property stock, residential, office, retail and industrial) over the last 45 years by focusing on their dynamic correlations, varying spillover-connectedness, Granger causal dependence and selective frequency return connectedness to understand better the changing market relationships among the six markets, as well as the wealth effects between the stock and housing markets. We find that the six asset markets have not become more correlated over time. The 2007–2009 global financial crisis has created the most severe contagion among the markets and was followed by Singapore economic recession. Although these six markets were quite moderately connected in their returns and risk, the return and risk connectedness index measures reached their respective low levels in recent years. The net directional connectedness of the six markets varies in different periods of domestic economic development, external financial crisis and domestic economic recession. Moreover, the housing market leads significant causal interactive roles (linear and nonlinear) over other property and stock markets. On the other hand, the stock market is a strong return transmitter for most of the research periods. The long-term horizon was the most important in contributing to the leadership position in return connectedness of housing market during the Asian financial crisis. Finally, a key message derived from this “long-period” study is that an in-depth understanding of the various investment dynamics is crucial to help maximize mixed portfolio diversification benefits and managing risk in Singapore stock and property markets in the long run.

Who are the influencers in the commodity markets during COVID-19?

Price volatility caused by the pandemic has caused serious concern in global commodity markets. The quantile connectedness method is used to investigate the net receiving/transmitting role of energy, shipping, metals and commodity markets. The results show dynamic quantile connectedness in the short run in the pre-pandemic. The net directional connectedness result explores that oil prices and commodity markets roles change between transmitting to receiving in the medium to upper quantiles. However, the receiving role is found for both the shipping industry and metals markets in upper quantiles. Similarly, the results of the dynamic connectedness during the COVID-19 display strong connectedness for higher volatility. The net directional connectedness outcomes show that oil prices, shipping and commodity markets have a transmitting/receiving role in the higher quantiles. The net transmitting period is seen more actively than the receiving one during the COVID-19. The policymakers are in need of planning policies while considering the heterogeneous impact of the international oil market on these commodity markets.

An intra-cryptocurrency analysis of volatility connectedness and its determinants: Evidence from mining coins, non-mining coins and tokens

This paper analysis the dynamic of the volatility connectedness between three main categories of the cryptocurrency market (mineable coins, non-mineable coins and tokens).11The list four mining coins considered in this study contains Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC) and DASH (DASH), the four non-mining coins are Ripple (XRP), EOS (EOS), Binance coin (BNB), and Stellar (XLM)), and the list of four tokens includes Maker (MKR), Basic Attention (BAT), Chainlink (LINK), Augur (REP)). Furthermore, it investigates factors (internal and external) that can help to predict the net directional and total volatility connectedness indices. We find that the CC market is highly connected where mining coins dominate the CC market and are typically net transmitter of shocks. For the non-mining coins, a low connectedness with all mining coins and tokens versus a high connectedness with Stellar are highlighted. The results show also that, unlike previous studies, Ethereum is the dominant contributor to volatility spillover and the only CC net pairwise transmitter in our sample. Interestingly, we find that most of the tokens are highly connected with their platform (Ethereum) rather than bitcoin. Finally, we find that both financial and macroeconomic indicators play an important role in explaining the total and net directional connectedness, a result that can significantly help cryptocurrency market participants and investors improve their risk management and the benefits from diversification.

Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent

The first Yuan (RMB) denominated crude oil futures contract, SC, was launched in the Shanghai International Energy Exchange (INE) on 26 March 2018, which is extremely meaningful for China and other Asian countries by offering a new option of oil price risk management. To identify the information connectedness among this emerging contract and those mature WTI and Brent oil futures, we provide return and volatility directional connectedness evidence among them in both the time and frequency domains. The empirical results show that, firstly the three oil futures of SC, WTI, and Brent present high degree of total connectedness in the return and volatility series, implying tight information transfer among them. Secondly, the net directional connectedness results suggest that the SC can provide competitive information on oil returns and is a net and powerful contributor to volatility shocks. In addition, from a frequency-specific perspective, we find that the SC appears to be not only a net transmitter of return shocks on the medium- and long-term frequencies but also a net transmitter of volatility shocks consistently across the whole frequency ranges. The overall evidence suggests that China's new oil futures is an active participant in the international oil futures market, and may become an important product in information transmission across international crude oil futures markets by providing effective hedging instrument for crude oil producers, refiners, consumers, and investors, especially those in Asia.

Total and Net-Directional Connectedness of Cryptocurrencies During the Pre- and Post-COVID-19 Pandemic

This paper presents how volatility propagates through the cryptocurrency market. Our paper provides evidence for volatility connectedness on cryptocurrencies. The different econometric techniques, including the stochastic volatility (SVOL) model and time-varying parameter VAR models using a quasi-Bayesian local likelihood (QBLL), are applied to measure the volatility of the cryptocurrency market. Using high-frequency, intra-day data of the largest cryptocurrencies over 2018–2021, we detect the great volatility of the cryptocurrency market are the beginning of 2019, the beginning of 2020, and throughout the year of 2021. The total connectedness values suggest that the cryptocurrency market becomes volatile as the new strains of the COVID-19 appear at the end of 2021. However, by using directional connectedness, we reveal that there are negative and positive spillovers from a specific cryptocurrency to other cryptocurrencies. The great fluctuations in the period before the COVID-19 health crisis stem from the positive resonance (symmetric) between the volatility of each cryptocurrency, while this health crisis leads to substantially positive and negative spillovers (asymmetric) of cryptocurrencies, and this makes market volatility weaker than it actually is.

Direct real estate, securitized real estate, and equity market dynamic connectedness

ABSTRACT The paper’s objective is to scrutinize the dynamics of connectedness across returns of three markets, including direct real estate, securitized real estate, and stock markets. Through the connectedness index approach, the results indicate a significant degree of connectedness, which increases sharply during the recent global financial crisis. The net directional connectedness is volatile and time-dependent, yet the dominant shock transmitting role of the securitized real estate is pronounced during the GFC. While the direct real estate market plays as a dominant shock information receiver from the markets of securitized real estate and stocks in Australia, Canada, France, and the UK, it appears to shape other markets in the context of the US. Given the fact that the securitized real state is considered as the hybrid of the conventional real estate market and the stock market, we further note that the securitized real estate is more linked with its underlying market. Several implications for investors and policymakers are discussed.

On interdependence structure of China's commodity market

This paper aims to provide insight into the interdependence structure of a set of commodity sectors in China. Using daily data of China's commodities from August 2004 to April 2019, we explore the cross-sector connectedness as well as contemporaneous causal relationship of China's commodity market at the sector level. The results indicate that a large proportion of the fluctuations in China's commodities is attributed to the cross-sector connectedness. However, the patterns of connectedness behave differently across sectors in the commodity market. In particular, the net connectedness indices enable us to assess whether each sector is a transmitter (receiver) of the shocks. In addition to a large variation of connectedness over time, the spillover effects across sectors increase during unstable periods. When examining the time-varying net directional connectedness, we demonstrate that most sectors frequently switch between a net transmitting and receiving role depending on sector-specific effects over time. Moreover, the paper provides novel evidence of the contemporaneous structure of causal relationship among China's commodities, while the roles in the shock transmission in contemporaneous time differ greatly across sectors. Our findings have significant implications for diversification as well as economic policymaking.

Time Connectedness of Fear

This paper examines the interconnection between four implied volatility indices representative of the investors' consensus view of expected stock market volatility at different maturities during the period January 3, 2011-May 4, 2018. To this end, we first perform a static analysis to measure the total volatility connectedness in the entire period using a framework proposed by Diebold and Yilmaz (2014). Second, we apply a dynamic analysis to evaluate both the net directional connectedness for each market using the TVP-VAR connectedness approach developed by Antonakakis and Gabauer (2017). Our results suggest that a 72.27%, of the total variance of the forecast errors is explained by shocks across the examined investor time horizons, indicating that the remainder 27.73% of the variation is due to idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability. Finally, we also document a superior performance of the TVP-VAR approach to connectedness respect to the original one proposed by Diebold and Yilmaz (2014).

Volatility transmission between stock and foreign exchange markets: a connectedness analysis

ABSTRACTThis paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to May 2018. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.

Cross-regional connectedness in the Korean housing market

This paper investigates the network topology of the Korean housing market using the connectedness methodology. The basic finding is that, among various combinations of regional housing markets, Seoul has been the most influential market in Korea. We also present evidence that other metropolitan cities affect only the neighboring regions. As for the results from the rolling-sample analysis, the net directional connectedness of Seoul appears to have declined over the sample period. Although Seoul still remains the center of the Korean housing market, neighboring regions have become increasingly more influential in affecting other regional markets. These findings suggest that the policy for balanced national development might have changed the transmission mechanisms in the Korean housing market.

Network connectedness and net spillover between financial and commodity markets

We extend the prior literature on market connectedness and spillover by quantifying the size of return connectedness across markets (assets). Applying the network spillover methodology, we perform both static and dynamic analyses to quantify the net spillover shock transmission from one market to another market (stock, bond, currency, and commodities) from December 1999 to June 2016. Thus, we measure the net pairwise spillover and assess the net directional connectedness for each market (asset class). Finally, our visual depiction of a network connectedness framework provides specific information on portfolio strategies for cross-border portfolio managers.

Fear connectedness among asset classes

ABSTRACTThis study investigates the interconnection between five implied volatility indices representative of different financial markets during the period 1 August 2008–29 December 2017. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz. Second, we make use of a dynamic analysis to evaluate both the net directional connectedness for each market and all net pairwise directional connectedness. Our results suggest that a 38.99%, of the total variance of the forecast errors is explained by shocks across markets, indicating that the remainder 61.01% of the variation is due to idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability. Finally, we also document frequently switch between a net volatility transmitter and a net volatility receiver role in the five markets under study.

Interconnectedness and Contagion in International Real Estate Investment Trusts

This paper investigates interconnectedness and contagion effects of the US global financial crisis and the European debt crisis across eight longest-established real estate investment trust markets in the US, Canada, Australia, Japan, Singapore, France, Belgium and Netherlands over the period from October 2003 to December 2016. Using the connectedness indexes developed by Diebold and Yilmaz (2012, 2014 and 2016) and supplementing with selected net directional pairwise network graphs, we find their volatility connectedness was less strong than that of stock markets. Additionally, the volatility connectedness experienced a decrease of over 10% over the full sample period, implying that their slower globalization progress and lower financial integration level, as well as have different patterns of volatility connectedness from the corresponding stock markets. Volatility market connectedness was mainly caused by the cross-market contagion during unstable periods. The rolling sample analysis confirms significant market contagion effects during crises, such as Lehman Brothers Bankruptcy (GFC) and looming financial crisis in Europe (EDC), though the effects varied widely among the REIT markets. Finally, the net directional connectedness was time varying and experienced a shit in terms of net volatility shock transmitters and receivers for the markets due to different nature of crises. Our study reveals fresh evidence of interconnectedness and contagion effects across international REIT markets and indicate the importance of policy countermeasure in reacting to economic and financial crisis.

Fear Connectedness Among Asset Classes

This study investigates the interconnection between five implied volatility indices representative of different financial markets during the period August 1, 2008-September 9, 2015. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate both the net directional connectedness for each market and all net pair-wise directional connectedness. Our results suggest that slightly more than only 38.22%, of the total variance of the forecast errors is explained by shocks across markets, indicating that the remainder 61.78% of the variation is due to idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.

Volatility Transmission between Stock and Exchange-Rate Markets: A Connectedness Analysis

This paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to January 2015. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.

Using connectedness analysis to assess financial stress transmission in EMU sovereign bond market volatility

We measure the connectedness in EMU sovereign market volatility between April 1999 and January 2014, monitoring stress transmission and identifing episodes of intensive spillovers from one country to the others. We first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period using a framework recently proposed by Diebold and Yilmaz (2014). Second, we use a dynamic analysis to evaluate the net directional connectedness for each country and apply panel model techniques to investigate its determinants. Finally, we examine the time-varying behaviour of net pair-wise directional connectedness at different stages of the recent sovereign debt crisis.

Connectedness of Stress in EMU Bank and Sovereign CDS: The Role Policy Measures 2008-2014

This paper measures the connectedness in European Economic and Monetary Union (EMU) sovereign and bank CDS between April 2008 and December 2014, in order to understand the transmission of stress during the euro crisis. To this end, we perform a connectedness analysis using the framework proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each country and bank. Finally, we interpret the policy conclusions that stem from the results. We find that core countries' contribution to stability was particularly significant since Draghi's 'whatever it takes' speech. Bank risk played a role in enhancing sovereign risk. However, the systemic impact of banks changes rapidly once a crisis strikes, rendering the ex-ante determination of which banks are systemic and which banks will have a higher impact on the sovereign difficult.

Financial Stress Transmission in EMU Sovereign Bond Market Volatility: A Connectedness Analysis

This paper measures the connectedness in EMU sovereign market volatility between April 1999 and January 2014, in order to monitor stress transmission and to identify episodes of intensive spillovers from one country to the others. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each country and apply panel model techniques to investigate its determinants. Finally, to gain further insights, we examine the time varying behaviour of net pair-wise directional connectedness at different stages of the recent sovereign debt crisis.