Volatility Co-movements Research Articles

The influential impacts of international dynamic spillovers in forming investor preferences: a quantile-VAR and GDCC-GARCH perspective

ABSTRACT This study investigates whether representative sectoral stock indices, gold, oil, Bitcoin, and wheat can mitigate risk and improve portfolio performance during normal times versus crises. The cutting-edge Quantile Vector Autoregressive model and the Generalized Dynamic Conditional Correlations (Generalized-DCC) framework are adopted covering from 9 January 2017 until 30 August 2022. Econometric findings by the Q-VAR reveal that oil presents the strongest connection with commodities and stock indices and that Bitcoin and wheat despite their significant linkages with financial markets fail to act as safe havens. Moreover, GDCC-GARCH indicates that the returns of sectoral indices are weakly related but display powerful volatility co-movements. Gold serves efficiently as a hedger and oil follows and both act as better shelters during crises. Nevertheless, Bitcoin partly abides by conventional markets in stressed periods. Notably, wheat reliably works as a hedger overall but does not become a safe haven during crises.

Is there a time-varying nexus between stock market liquidity and informational efficiency? – A cross-regional evidence

PurposeThis study aims to measure the degree of volatility comovement between stock market liquidity and informational efficiency across Asia, Europe, North-South America, Africa, and the Pacific Ocean over three decades. In particular, the authors analyze the extent of the time-varying nexus between different aspects of stock market liquidity and multifractal scaling properties of the stock return series across various regions and diversified market conditions. This study further investigates several factors altering the degree of dynamic conditional correlations (DCCs) between the efficiency and liquidity of the domestic stock markets.Design/methodology/approachThe study measures five aspects of stock market liquidity – tightness, depth, breadth, immediacy, and adjusted immediacy. The authors evaluate the multifractal scaling properties of the stock return series to measure the level of stock market efficiency across the regions and diversified market conditions. The study uses the dynamic conditional correlation-multivariate generalized autoregressive conditional heteroscedasticity framework to quantify the degree of volatility comovement between liquidity and efficiency over the period.FindingsThe study finds the presence of stronger volatility comovement between inefficiency and illiquidity due to the price impact characteristics of the stock markets irrespective of different regions and diversified market conditions. The extent of time-variation increased following the shock periods, indicating the significant role of the financial crisis in increasing the volatility comovement between inefficiency and illiquidity. The highest degree of time-varying correlation is observed in the developed stock markets of Northwestern and Northern Europe compared to the regional and emerging counterparts. On the other hand, weak DCCs are observed in the emerging stock markets of Europe.Originality/valueThe output of the present study assists investors in identifying diversification opportunities across the regions. Additionally, the study has significant implications for market regulators, aiding in predicting future troughs and peaks. The prediction, in turn, helps formulate capital market development plans during dynamic economic situations.

The factor structure of exchange rates volatility: global and intermittent factors

In this paper, we consider a fractionally integrated multi-level dynamic factor model (FI-ML-DFM) to represent commonalities in the hourly evolution of realized volatilities of several international exchange rates. The FI-ML-DFM assumes common global factors active during the 24 h of the day, accompanied by intermittent factors, which are active at mutually exclusive times. We propose determining the number of global factors using a distance among the intermittent loadings. We show that although the bulk of common dynamics of exchange rates realized volatilities can be attributed to global factors, there are non-negligible effects of intermittent factors. The effect of the COVID-19 on the realized volatility comovements is stronger on the first global-in-time factor, which shows a permanent increase in the level. The effects on the second global factor and on the intermittent factors active when the EU, UK and US markets are operating are transitory lasting for approximately a year after the pandemic starts. Finally, there seems to be no effect of the pandemic neither on the third global factor nor on the intermittent factor active when the markets in Asia are operating.

SPILLOVER EFFECTS OF THE FUTURES CONTRACT PRICES OF THE NYMEX CRUDE OIL: A MULTIVARIATE GARCH APPROACH

The main aim of this paper is to investigate spillover effects of the futures contracts prices of the Nymex Crude Oil. Tse and Tsui (2002) multivariate generalized autoregressive conditional heteroscedasticity model is used and a two-step MGARCH estimation of the two crude oil futures contracts prices of the New York Mercantile Exchange (NYMEX) is carried out. The results revealed of conditional volatility correlations between crude oil futures contract-3 and futures contract-4 of the NYMEX. The economic implication of this results is that a volatility of futures contract-4 could affect the volatility of futures contract-3 and vice-versa, which suggests that investment uncertainties associated with one of the contracts could foster investment uncertainties in the other contract which might raise the level of risks in the market and affect portfolio allocations of investors as well as firms' investment plans on the market. Therefore, the high level of volatility co-movements between the two series suggests that during the sample period there was high degree of volatility correlations between the two futures prices, which indicates that the forces driving the two futures prices of the NYMEX might be similar. Based on the finding of the study, the paper recommends that, authority concern should come up with appropriate policy that will reduce volatility correlations between crude oil future contracts.

The role of uncertainty in forecasting volatility comovements across stock markets

Earlier studies found that uncertainty is important in forecasting the financial market covolatilities. However, it is not clear how uncertainty affects the covariance matrix dynamics across different market and economic conditions. To fill this gap, we specify the dynamic relationship between stock market covolatilities and uncertainty in a nonlinear framework, and we analyze the relevance of uncertainty measures in anticipating the transition of conditional covariances between different regimes. Specifically, we propose alternative transformations of the realized covariance matrix which we model by means of the Vector Logistic Smooth Transition Autoregressive (VLSTAR) model. Empirical results indicate that uncertainty measures used as transition variables help to detect covolatilities changes; moreover, the VLSTAR exhibits a significantly better forecast performance compared to alternative linear and multivariate GARCH models. Finally, our results show that the evidence on the role of macroeconomic and financial predictors is mixed, depending on the specification of the realized covariance dynamics.

Simulation of Arbitrage-Free Implied Volatility Surfaces

We present a computationally tractable method for simulating arbitrage-free implied volatility surfaces. We illustrate how our method may be combined with a data-driven model based on historical SPX implied volatility data to generate dynamic scenarios for arbitrage-free implied volatility surfaces. Our approach conciliates static arbitrage constraints with a realistic representation of statistical properties of implied volatility co-movements.

Spillover effects of the unconventional monetary policy of the European Central Bank

We analyze the effects of the European Central Bank’s (ECB) unconventional monetary policy spillovers on the inflation-targeting Central Eastern European (CEE) countries using daily panel data from 2000 to 2019. We perform an exercise to identify these spillovers on the monetary market, calculate instantaneous short rates and term spreads, and use both Bayesian averaging panel and time-series approaches. Overall, we find that the spillovers from the unconventional ECB policy are not different from the conventional spillovers and are generally insignificant. While we find a significant reaction to inflation and an insignificant reaction to the output gap, we find that none of our ECB policy measures affect the instantaneous short interest rate nor the long-run term spreads. Our main result is that the international spillovers manifest themselves through the risk-taking channel, not the bond/interest rate channel, and have the form of volatility co-movement.

Assessing oil price volatility co-movement with stock market volatility through quantile regression approach

In times of financial crisis as well as during the COVID-19 era, gold and crude oil are the two commodities that have the most influence on global stock markets and the real economy. But research has mostly focused on the effects of these commodities' prices on their own, and the volatility of these commodities' prices as a whole hasn't gotten much attention. This research paper evaluates the impacts of crude oil prices volatility on shares marketplaces. This research examines the impact of crude oil uncertainty on the overall market returns in several economic sectors (China, Japan, the USA, France, and Germany) between 2000 and 2020 using the importance of the crude oil prices volatility index by applying a Quantile-on-Quantile regression(Q-Q), including dynamic copula with Markov-Switching. The results depict that because the effect of the OVX changes crosswise every single quantile level of stock return, it is cumbersome to ascertain the changes within the adverse impacts under varied stock market circumstances. Equally, to derive a comprehensive understanding of the correlation between crude costs volatility and stock returns, we utilize twofold quantile regression and quantile-quantile regression methods. We interpret these different features' impacts by applying the quantile regression approximates. Our experiential findings show that crude costs uncertainty has lop-sided impacts on stock returns; more so, these disproportionate performances alternate based not merely on the level of shares returns nonetheless equally crude market circumstances. More so, greater values match a robust risk decrease. Further, we observed heterogenous hedging effectiveness among the varied United States stock sectors. The findings demonstrate that growing crude prices volatility obtains an adverse impact on stock returns when the dual crude costs volatility and stock returns are minimal. Nevertheless, when shares returns are greater plus crude prices, volatility is minimal; growing crude volatility increases stock returns.

European stock market volatility connectedness: The role of country and sector membership

The literature suggests that the country in which a company is listed, i.e., its country membership, is the main determinant of its price volatility co-movements in the global stock market but, at the same time, this body of literature also recognizes the relevance of industry sector membership for understanding risk transmission. Drawing on recent advances in time series analysis, we are able to define an extensive network structure for 645 ‘large-cap’ companies from 35 European countries, and to decompose the total market volatility connectedness into its respective country and sector membership contributions. Using the firm level as our unit of analysis, we find that traditional (more aggregate) approaches, which rely on market indices to study international connectedness, present an incomplete (and, biased) picture of risk transmission between international stock markets. We show that, in general, a company’s country membership is indeed a more significant determinant than that of its sector membership; however, from a risk management perspective, there are significant heterogeneities at the company level that need to be duly considered and quantified so as to better anticipate crucial dependencies in certain countries or sectors in periods of market distress, such as that resulting from the current conflict in Ukraine and the economic sanctions being imposed. We summarize the connectedness of individual companies in a network that international risk managers and investors can use to assess global financial market dependencies and to inform their risk management practices.

Modelling of Returns and Volatility Co-movements of Central European Currencies

Modelling of Returns and Volatility Co-movements of Central European Currencies

Examining the asymmetries between equity and commodity ETFs during COVID-19

Previous studies have neither examined the volatility co-movements across stock and commodity markets in terms of both time and frequency nor differentiated between bad and good volatility and the potential asymmetric effect. To address this gap, we computed 5-min price data, the positive and negative semivariances on five leading Exchange Traded Funds (ETFs) covering the US equity market, crude oil, natural gas, gold, and silver markets from January 2, 2019 to May 29, 2020, and then draw on the wavelet coherency methodology and the time-varying wavelet coherence measure. The results show that the negative realized volatility co-movements are stronger during the COVID-19 outbreak, especially at short and medium frequencies. The US stock market leads energy and precious metals in the short-run frequency. However, over the long-run, the lead-lag pattern mostly alternates over time for all cases. Notably, the realized volatilities of US equities and precious metals are shaped by the COVID-19 outbreak, reflecting the quest of investors for protection from the market volatilities by investing in gold and silver. This latest finding is confirmed by the wavelet coherence measure. Further results show asymmetric co-movements emanating especially from realized negative semivariance of equities and energy markets around the pandemic outbreak across short-time horizons. We also notice that the COVID-19 outbreak increases the procyclical movement of all ETFs in the short-term. The effect is more pronounced among the US equity and precious metals markets, whereas no significant countercyclical connectedness is observed among these markets. Our findings support previous evidence showing that gold and silver can serve as safe-haven assets due to their low coherence with risky assets.

Volatility Co-Movement between Bitcoin and Stablecoins: BEKK–GARCH and Copula–DCC–GARCH Approaches

This paper aims to investigate and measure Bitcoin and the five largest stablecoin market volatilities by incorporating various range-based volatility estimators to the BEKK- GARCH and Copula-DCC-GARCH models. Specifically, we further measure Bitcoins’ volatility related to five major stablecoins and examine the connectedness between Bitcoin and the stablecoins. Our empirical findings document that the connectedness between Bitcoin and stablecoin market volatility behaviors exhibits the presence of stable interconnection. This study is of particular importance since it is crucial for market participation in the ongoing crypto assets to be informed about both the volatility patterns of major cryptocurrencies and the relative volatility of Bitcoin against the stablecoin markets. Eventually, we find that there is no systematic evidence for the various parity deviations of the stablecoins that are profoundly impacted by Bitcoin volatility. Thus, Bitcoin and the largest stablecoin Tether could stabilize together. However, Bitcoin shall not be generalized to other stablecoins in terms of stability results.

Information from Implied Volatility Comovements and Insider Trades

Information from Implied Volatility Comovements and Insider Trades

On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis

This study aims to provide fresh time-frequency evidence on global equity and commodity market interdependencies, in terms of the first four moments of their respective return distributions (i.e., mean, variance, skewness, and kurtosis), using wavelet analysis techniques. The results indicate that the co-movement structure of the same-order moments of equity, gold, and energy returns tends to be both time-dependent and frequency-dependent. With respect to the equity-gold nexus, we detect substantial cross-volatility, cross-skewness, and cross-kurtosis effects at medium- and long-term time scales during the 2010–2014 turmoil, with the stock market leading the gold counterpart in most cases. From 2015 onwards, we observe a strong degree of coherence at high and medium frequencies for each of the four same-order moment pairs, but generally with zero-phase difference. The findings for the equity-energy nexus suggest significant mean and volatility co-movement over most of the sample period and across frequency bands. Additionally, cross-skewness and cross-kurtosis linkages are more pronounced at short- and medium-term horizons and, noticeably, in the wake of global downturns. Practical implications are deduced from the analysis.

The Role of Multilateralism of the WTO in International Trade Stability

AbstractWe look at the effect of the WTO on stabilizing international trade using both a fixed-effects and an event study approach. Our results show that WTO members experience lower trade volatilties in a predictable and integrated system. In addition, we focus on the trade volatility comovement among countries in a multilateral framework. Previous research has mainly focused on WTO membership in a bilateral trade framework, which only allows interactions between two trade partners without considering any possible influence from other countries. A bilateral trade framework does not fully capture the effect of WTO membership, nor does it investigate why the multilateral platform of the WTO should exist. With a unique setup estimating interactions among multiple trading dyads, we find strong evidence supporting positive correlation or comovement of trade volatilities across trading pairs. Such a comovement appears much stronger among WTO members than between WTO and non-WTO members. Due to the feedback mechanism among dyads in a multilateral framework, such as the WTO, bilateral trade stability may further stabilize the global trade. Our results remain robust to a battery of sensitivity checks.

Volatility Co-Movement in Stock Markets

The volatility and log-price collective movements among stocks of a given market are studied in this work using co-movement functions inspired by similar functions in the physics of many-body systems, where the collective motions are a signal of structural rearrangement. This methodology is aimed to identify the cause of coherent changes in volatility or price. The function is calculated using the product of the variations in volatility (or price) of a pair of stocks, averaged over all pair particles. In addition to the global volatility co-movement, its distribution according to the volatility of the stocks is also studied. We find that stocks with similar volatility tend to have a greater co-movement than stocks with dissimilar volatility, with a general decrease in co-movement with increasing volatility. On the other hand, when the average volatility (or log-price) is subtracted from the stock volatility (or log-price), the co-movement decreases notably and becomes almost zero. This result, interpreted within the background of many body physics, allows us to identify the index motion as the main source for the co-movement. Finally, we confirm that during crisis periods, the volatility and log-price co-movement are much higher than in calmer periods.

Risk Dynamics of Sectoral Stocks in BRICS Countries

This study attempts to contribute to the literature on risk exposures by investigating the dynamic volatility spillover transmissions and volatility co-movements between oil-risk factors and sectoral stocks in BRICS countries. A spillover index and DCC-GARCH estimation techniques are applied to identify the volatility transmission mechanism and co-movement among the series using daily data from 5th May 2007 to December 31st, 2016. To provide practical implications of the volatility transmissions, the estimated results are in turn used to compute and analyze the optimal weights and hedge ratios for oil-stock portfolio holdings. Our findings indicate the existence of significant volatility spillover interdependences and a time-varying volatility co-movement between oil-risk factors and sectoral stocks. However, the direction of spillover is shown to be somewhat unidirectional mainly from some selected sectors to oil-risk factors. Thus, we show that although volatility spillovers from oil-risk factors to sectors exist, the effect is at best, marginal. Finally, the optimal weights and hedge ratios show that oil-risk factors would be better suited as instruments for portfolio diversification rather than hedging to minimize oil price and portfolio risks which is important for risk management and diversification benefits.

Liner shipping industry and oil price volatility: Dynamic connectedness and portfolio diversification

Given the importance of the relationship between oil and liner shipping markets, this paper examines the volatility spillover and connectedness between oil and liner shipping markets. We employ dynamic conditional equicorrelations and spillover index approach to know volatility co-movement and spillover between oil prices and returns of liner shipping stocks, respectively. The volatility co-movement between oil and liner shipping companies’ stock returns increased during the 2007–09 global financial crisis, and 2010–12 Eurozone debt crisis. We extend our analysis by considering portfolio diversification strategies and utility gains across pre-crisis, crisis, and post-crisis periods. Our findings are useful to policymakers and investors.

Should central banks use the currency futures market to manage spot volatility? Evidence from India

The Reserve Bank of India has declared a policy of intervening in the retail currency futures market to manage volatility in the over-the-ounter (OTC) currency spot market, indicating its belief of underlying linkages between these two markets. This paper examines the dynamic interactions between volatility and volume across currency futures and spot markets in India. High-frequency five-minute level data for a year-long period are used to study the nonlinear symmetric and asymmetric causality (Kyrtsou–Labys, 2006) between volatility and volume within and across markets. The findings suggest that an increase (decrease) in volumes in either market causes a corresponding increase (decrease) in volatility in both markets. Specifically of interest is the observation that futures volume causes co-movement in spot market volatility. The study has implications for currency market participants, especially the Reserve Bank of India, in managing exchange rate volatility through the currency futures market.

RETURN AND VOLATILITY SPILLOVER EFFECTS IN LEADING CRYPTOCURRENCIES

As Cryptocurrencies are emerging as a new class of investment assets, understanding their price and volatility dynamics has begun to gather momentum, especially the volatility can influence investment decisions. Most of previous literature concentrates primarily on several aspects of Bitcoin and endeavoring to generalize them for the whole cryptocurrency markets. In this study, we attempted to examine the return and volatility spillover effects across a wide range of cryptocurrency markets, i.e. eight major cryptocurrencies (determined by market capitalization) using a Vector Error Correction approach and Diagonal BEKK Multivariate GARCH model. We found the evidence of interdependencies and volatility co-movements among the various pairs of cryptocurrency markets. However, the study suggests that there exists a limited window of opportunity for the short-term portfolio diversification benefits from the selected large-cap cryptocurrency markets.