Degree Of Co-movement Research Articles

From black gold to financial fallout: Analyzing extreme risk spillovers in oil-exporting nations

Considering various critical periods including the COVID-19 pandemic and the ongoing Russian–Ukraine war, this paper investigates the dynamics of extreme spillover effects from the crude oil market to the financial markets of major oil-exporting countries. With the increased integration of global financial systems, oil market fluctuations can have far-reaching implications for economies that are heavily reliant on oil exports. We employ a wavelet approach to explore the co-movement and lead–lag relationships between the oil market and the financial markets of the considered countries. Next, we follow the newly introduced frequency-based connectedness approach of Hanif et al. (2023) to explore the dynamic connectedness and risk transmission among these markets. First, results from the wavelet coherency technique show that the degree of co-movement during the Russia–Ukraine war was significantly lower than it was under both the pre-crises and COVID-19 pandemic periods as shown by fewer regions with warmer colors (red), which show significant dependence at the 5% level, especially for Canada. Secondly, the dynamic connectedness of these markets was largely driven by long-term dynamics during the Russia–Ukraine crisis period, unlike the short-term driven connectedness observed during the COVID-19 pandemic. The average degree of connectedness at high frequencies (short-term) forms a smaller proportion of the average level of connectedness at low frequencies (long-term), indicating a stronger long-term influence of the crisis on the interconnectedness of these markets. Additionally, we find that Canada and the United States were the major net transmitters of shocks to the network during the conflict period, while Iraq exhibited the strongest level of idiosyncratic shocks. Interestingly, the crude oil market was observed to send stronger shocks to the network at the onset of the war, with the impact gradually diminishing as the conflict progressed. Our study provides valuable insights for policymakers and investors as a guide towards more informed decision-making and appropriate risk management strategies in the face of oil price volatility in these regions.

International co-movements of inflation, 1851–1913

Abstract We study inflation in a group of 15 countries before and during the classical Gold Standard using annual data spanning 1851–1913. The degree of co-movements between domestic and international inflation depends on geographical remoteness and openness to trade. Furthermore, international inflation acts as an ‘attractor’ for domestic inflation. Sub-sample estimates reveal little evidence of instability implying that international inflation was an important influence on domestic inflation throughout this time period.

Dynamic relations between housing Markets, stock Markets, and uncertainty in global Cities: A Time-Frequency approach

This paper considers the dynamic features of housing prices in metropolises that are characterised by a high degree of internationalisation. Using the wavelet coherency procedure, the degree of co-movement and causality between housing, stock markets, and macroeconomic uncertainty are investigated. In addition, the existence of volatility spillover across housing markets is assessed in the time–frequency domain using a novel procedure that involves combining the wavelet decomposition with a time varying parameter vector autoregression model. The results highlight that the clustering of global business in a limited number of metropolises that act as “global hubs” leaves the local housing markets exposed to international shocks and volatility spillover. The empirical analysis suggests that the correlations between real estate and stock markets from one side, and real estates and uncertainty on the other side, intensify during the turmoil periods. Causality and co-movement relationships appear predominately in the medium and long run periods. The evidence presented in this paper suggests that policymakers cannot ignore the possibility that international shocks to housing markets may affect the domestic markets. In this respect, macroprudential policy tools may target tapering off the unintended effects of housing market globalisation such as house price shock synchronisation, especially when these shocks take place in cities that are also major financial centres.

Network Analysis of Price Comovements Among Corn Futures and Cash Prices

Abstract Due to significant implications for resource and food sectors that directly influence social well-being, commodity price comovements represent an important issue in agricultural economics. In this study, we approach this issue by concentrating on daily prices of the corn futures market and 496 cash markets from 16 states in the United States for the period of July 2006 – February 2011 through correlation based hierarchical analysis and synchronization analysis, which allow for determining interactions and interdependence among these prices, heterogeneities in price synchronization, and their changing patterns over time. As the first study of the issue focusing on prices of the futures and hundreds of spatially dispersed cash markets for a commodity of indubitable economic significance, empirical findings show that the degree of comovements is generally higher after March 2008 but no persistent increase is observed. Different groups of cash markets are identified, each of which has its members exhibit relatively stable price synchronization over time that is generally at a higher level than the synchronization among the futures and all of the 496 cash markets. The futures is not found to show stable price synchronization with any cash market. Certain cash markets have potential of serving as cash price leaders. Results here benefit resource and food policy analysis and design for economic welfare. The empirical framework has potential of being adapted to network analysis of prices of different commodities.

Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models

The returns of cryptocurrencies tend to co-move, with their degree of co-movement being contingent on the (bullish- or bearish-) states. Given this, we use standard factor models and regime-switching factor loadings to forecast the returns of a specific cryptocurrency based on its lagged information and informational contents of 14 other cryptocurrencies, with these 15 together constituting 65% of the market capitalization. Considering top five cryptocurrencies namely, Bitcoin, Ethereum, Ripple, Dogecoin, and Litecoin, we find significant forecastability and evidence that factor models, in general, outperform the benchmark random-walk model, with the regime-switching versions standing out in the majority of the cases.

Exchange Rate Synchronization for a Set of Currencies from Different Monetary Areas

The degree of co-movement between currencies remains an important subject for international trade and monetary integration across countries. However, the economic literature has given limited answers about the directional relationships among currencies, and whether they have a leader or a driver. Using the Hodrick-Prescott filter and the wavelet methodology, this paper analyzes exchange rate synchronization for a set of twelve currencies belonging to different monetary areas covering the period between January 1980 and July 2020. The empirical results reveal that: i) the U.S. dollar still plays an essential role as a foreign exchange anchor; ii) the euro shows an out-of-phase relationship with the vast majority of currencies, including with the other European currencies; iii) the British pound seems to have departed significantly from the European single currency; iv) the Brazilian real leads the Chinese yuan for most of the sample, and both currencies record great dissimilarities with the other currencies; v) in the absence of short-term foreign exchange market frictions, average bilateral distances between currencies are smaller, and vi) during the international financial crisis, exchange rates became more synchronized.

Dynamic Interdependence of Systematic Risks in Emerging Markets Economies: A Recursive-Based Frequency-Domain Approach

We examine the interdependence of systematic risk in twenty emerging market economies. The interdependence structures are performed for subregional and regional categorizations of emerging markets, which have demonstrated financial openness over the years. Hence, the Kalman filter-based wavelet approach is adopted to execute the purpose of this study. The outcome from the contemporaneous correlations demonstrates that the degree of comovements among the equity betas varies. Moreover, from the wavelet multiple cross-correlations, Qatar, Brazil, Indonesia, and Czech Republic led for most timescales. Conversely, the equity betas of United Arab Emirates (Africa and Middle East), Argentina (Americas), China (Asia), and Russia (Europe) exhibit low degrees of integration with other systematic risk returns from each subregion. The low correlations, especially in the short term, of these countries within their respective regions signify less risk transmission and should be included in a portfolio of assets in determining investment risks. Generally, we find significant integration among systematic risks in emerging markets in the long term. We institute that the nature of interdependence in systematic risk has been heterogeneous across time. Accordingly, the equity betas increase with scale for most subregions and the emerging markets as a whole, implying that market interconnections heighten as the investment horizon is prolonged, revealing saturated markets with shocks. It is recommended that prudent liquidity policies are implemented to augment resilience to systematic risks susceptibilities in the long term. The findings present pertinent implications for portfolio diversification, policy decisions, investing risk, and risk management schemes.

NETWORK ANALYSIS OF HOUSING PRICE COMOVEMENTS OF A HUNDRED CHINESE CITIES

Housing price comovements are an important issue in economics. This study focuses on monthly housing prices of 99 major cities in China for the years 2010–2019 by using correlation-based hierarchical analysis and synchronisation analysis, through which one could determine interactions and interdependence among the prices, heterogeneous patterns in price synchronisations and their changing paths over time. Empirical results show that the degree of comovements is slightly lower after March 2017 but no persistent drop is found. Several groups of cities are identified, each of which has its members showing relatively strong but volatile price synchronisations. Certain cities show potential of serving as price leaders within a group. Results here could be useful to policy analysis regarding housing price comovements.

Safe-haven investments against stock returns in Pakistan: a role of real estate, gold, oil and US dollar

PurposeThis study aims to compare the safe-haven properties of different asset markets such as gold, dollar, oil and disaggregated real estate sector (house, plot and residential) against equity returns in Pakistan over the monthly period of January 2011–December 2020.Design/methodology/approachThe authors use wavelet coherence to encapsulate the overall dependence and correlation of asset classes. Further, the authors also study the potential of diversification at the tail of returns distribution by applying the wavelet value-at-risk (VaR) framework.FindingsThe results of wavelet coherence show that the dependence is weaker (stronger) in the short (long)-term investment horizon. Moreover, the findings of wavelet VaR reveal that the degree of co-movement between gold and equity returns greatly affects the portfolio risk followed by residential property and oil.Practical implicationsThe findings are beneficial for the individual investor, fund managers and financial advisors looking for the optimal portfolio combination that hedges the excessive negative movements in equity returns subject to the heterogeneity in the investment horizon.Originality/valueThis is a primary effort to estimate safe-haven investments opportunities at a large spectrum, including disaggregated real estate sector against stock returns in Pakistan. Moreover, this study uses wavelet coherence and wavelet VaR which have an advantage over traditional analysis for diversification.

Network analysis of corn cash price comovements

Commodity price comovements are an important issue in economics given their significant implications for food and resource sectors that directly influence social well-being. This study approaches this issue by focusing on daily cash prices of 182 corn markets from the seven largest harvest states in the United States for 2006–2011 by using correlation based hierarchical analysis and synchronization analysis, through which we can determine interactions and interdependence among these prices, heterogeneities in price synchronization, and their changing patterns over time. As the first study of the issue concentrating on prices of hundreds of spatially dispersed markets for a commodity of indubitable economic significance, empirical findings show that the degree of comovements is generally higher after November 2006 but no persistent increase is observed. Different groups of markets are identified, each of which has its members exhibit similar price dynamics. Certain markets show potential of serving as price leaders. Results here benefit food and resource policy analysis and design for economic welfare. The empirical framework has potential of being adapted to network analysis of prices of different commodities.

The Regime-Switching Behaviour of Exchange Rates and Frontier Stock Market Prices in Sub-Saharan Africa

Frontier markets have become increasingly investible, providing diversification opportunities; however, there is very little research (with conflicting results) on the relationship between Foreign Exchange (FX) and frontier stock markets. Understanding this relationship is important for both international investor and policymakers. The Markov-switching Vector Auto Regressive (VAR) model is used to examine the relationship between FX and frontier stock markets. There are two distinct regimes in both the frontier stock market and the FX market: a low-volatility and a high-volatility regime. In contrast with emerging markets characterised by “high volatility/low return”, frontier stock markets provide high (positive) returns in the high-volatility regime. The high-volatility regime is less persistent than the low-volatility regime, contrary to conventional wisdom. The Markov Switching VAR model indicates that the relationship between the FX market and the stock market is regime-dependent. Changes in the stock market have a significant impact on the FX market during both normal (calm) and crisis (turbulent) periods. However, the reverse effect is weak or nonexistent. The stock-oriented model is the prevalent model for Sub-Saharan African (SSA) countries. Irrespective of the regime, there is no relationship between the stock market and the FX market in Cote d’Ivoire. Our results are robust in model selection and degree of comovement.

IFRS and stock exchange development in sub-Saharan Africa: a logistic model

This study examines the impact of International Financial Reporting Standards (IFRS) on the stock exchange development (SED) in sub-Saharan Africa (SSA). The essence is to offer suggestions on how the adoption of IFRS in the SSA region can benefit their SED. The study employed logistic regression analysis of data for 40 SSA countries for the period 2010–2018. Data were extracted from the World Bank’s World Development Index (WDI) database, sampled countries’ stock exchange websites, and the IFRS website. The dependent variable (SED) took two values: 1 – if a stock exchange is established in the observed country’s period, otherwise – 0. The model result was well fitted: p < 0.0001, correctly classified an overall SED accuracy up to 84.84% and excellent area predictive power at a receiver operator characteristic of 0.9347. The study observed that IFRS had high degree of co-movement with SED, and changes in IFRS had a strong positive impact on SED. Besides, changes in market size, ICT infrastructure, and public sector management and institution (PSMI) had a positive and significant impact on SED. The odd ratio of SED compared to non-SED is greatest with IFRS (40.67 times), and for the other variables, the ratios are: market size (4.02), ICT infrastructure (1.26), and PSMI (2.73), respectively. On a greater extent, SSA countries should allow the use of IFRS for financial reporting to expedite SED.

Is the GCC an optimum currency area (OCA)? Empirical answers from co-movements

Purpose This paper aims to investigate whether the Gulf Cooperation Council (GCC) is an optimum currency area in the wake of the global financial crisis and low oil prices using annual data from 2000 to 2016. Design/methodology/approach It applies the European Monetary Union as a reference point and co-movement methodology on key variables such as gross domestic product, inflation, terms of trade and current account balance. The findings revealed that all countries meet the macroeconomic convergence criteria and there is greater co-movement of these variables in the GCC. Findings Furthermore, the degree of co-movements increases during the financial crisis and recent low oil prices, which signifies the synchronization of shocks. However, labor is less mobile in the region and current account balance co-movement is relatively weak, but with the endogeneity of a monetary union, these constraints will evaporate as the zone enters monetary unification. The paper recommends that for the GCC monetary union to happen and be sustainable, there needs to be political will. The paper also recommended for the zone to have a common identification card so that nationals can move and work freely within the GCC region. Originality/value The study defers from the others in the following: this paper considered shock synchronization and co-movement methodology, which has not been applied in the region to assess its feasibility as an OCA.

Dynamic comovement among banks, systemic risk, and the macroeconomy

This paper develops a new measure of comovement in the banking sector that takes into account the dynamic nature of interlinkages in the return on assets (ROA) and net chargeoffs (NCO) among different bank holding corporations by using a dynamic factor model with time-varying parameters and stochastic volatility. We find that the degree of comovement in ROA and NCO peaked during the 2008–2009 financial crisis, suggesting a significant increase in sector-wide stress. Using the least absolute shrinkage and selection operator (LASSO) methodology, we show that comovement and risk measures derived from our approach perform well when compared to other widely used measures of systemic risk in explaining real economic activity.

Copula-based local dependence among energy, agriculture and metal commodities markets

This paper studies the extreme dependencies among energy, agriculture and metal commodities markets, with an emphasis on local co-movements. By applying a novel, copula-based, local Kendall’s tau approach to measure nonlinear local dependence in regions, we identified asymmetric co-movements in and between bull and bear markets, as well as the changing trend in the degree of co-movements. Starting from a non-parametric mixture copula, we found that commodities markets’ co-movements increase in extreme situations. In addition, we found a stronger dependence between energy and other commodities markets at lower tails. Therefore, we showed that the energy market can offer diversification solutions for risk management in the case of extreme bull market events.

Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis

In this study, we compare the safe-haven properties of Bitcoin, gold, and the commodity index against world, developed, emerging, USA, and Chinese stock market indices for the period 20 July 2010–22 February 2018. We apply the wavelet coherency approach and show that the overall dependence between Bitcoin/gold/commodities and the stock markets is not very strong at various time scales, with Bitcoin being the least dependent. We study the diversification potential at the tail of the return distribution through wavelet value-at-risk (VaR) and reveal that the degree of co-movement between gold and stock returns affects the portfolio’s VaR level. Specifically, the benefits of diversification vary in the time-frequency space, with Bitcoin exhibiting a superiority over both gold and commodities. Our findings are useful for investors and financial advisors searching for the best asset among Bitcoin, gold, and commodities to hedge extreme negative movements in stock market indices, while accounting for the heterogeneity in the horizons of investors.

Copula-Based Local Dependence Between Energy, Agriculture and Metal Commodity Markets

This paper studies the extreme dependencies among energy, agriculture and metal commodities markets, with an emphasis on local co-movements. By applying a novel, copula-based, local Kendall’s tau approach to measure nonlinear local dependence in regions, we identified asymmetric co-movements in and between bull and bear markets, as well as the changing trend in the degree of co-movements. Starting from a non-parametric mixture copula, we found that commodities markets’ co-movements increase in extreme situations. In addition, we found a stronger dependence between energy and other commodities markets at lower tails. Therefore, we showed that the energy market can offer diversification solutions for risk management in the case of extreme bull market events.

Comovement between commodity sectors

We aim to document the comovement between commodity sectors by using the three-dimensional continuous wavelet transform and copula method with the weekly dataset from January 1991 to December 2018. The dependence between commodity sectors varies across time and frequency. Precisely, Agriculture–Energy pair, Agriculture–Industrial metals pair, Energy–Industrial metals and Industrial metals–Precious metals pair show quite similar pattern in the lead–lag relationship and the degree of comovement is quite strong. In addition, Energy–Livestock pair, Energy–Precious metals pair and Industrial–Livestock pair do not show obvious periodic characteristics, however, they present strong comovement in the long term. Furthermore, we find the evidence of the robust strong relationship in the Agriculture–Industrial metals pair and Industrial metals–Precious metals pair. Investors who aim to make good portfolio management and policymakers who want to make effective macroeconomic policy should take these conclusions into account.

Dynamics in the co-movement of economic growth and stock return: comparison between the United States and China

The performance of the stock market is usually regarded as the barometer of economic growth and stock return and economic growth are, therefore, believed to co-move. However, the co-movement may exhibit different characteristics in various economic systems. This paper studies the co-movement of stock return and economic growth in two representative countries, the U.S. and China, with entirely different economic systems. The degree of co-movement is measured by the correlation of stock index return and G.D.P. growth rate and a time-varying copula model is applied to capture the dynamic characteristics of the co-movement. Empirical results show that the co-movement of stock return and economic growth is relatively strong but fluctuant in the U.S. and is relatively weak but stable in China. The differences in the co-movement can be interpreted by different economic growth modes in the U.S. and China.

Time-frequency domain causality of prime building cost and macroeconomic indicators in Ghana: implications for project selection

According to the Ghana Statistical Service, construction activity generated US$3.8 billion in 2014, representing about 12.7% of nominal GDP. A key factor that most investors in the construction sector consider in project selection is cost which has escalated over the years. Therefore, we examine the co-movements and causality in the time and frequency domains between the prime building cost index (PBCI) and its disaggregates on one hand and inflation and exchange rate on the other hand in Ghana. The findings revealed that the degree of co-movement between PBCI and inflation was significant at the 5% level and occurred over the long-run, indicating that construction cost drives inflation. The degree of co-movement between the prime build cost index and exchange rate occurred within the short term. These co-movements have policy implications for substituting inflation and exchange rates in project costing by investors in Ghana. The co-movement between the PBCI and inflation in the medium to higher frequencies suggests that inflation risk-averse investors should consider short-term projects. Again, the short to medium frequency co-movements between the PBCI and exchange rate indicates that investors should consider exchange rate risk in long-term projects.