Co-movement between GCC stock markets and the US stock markets: A wavelet coherence analysis

Matar, Ali; Al-Rdaydeh, Mahmoud; Ghazalat, Anas; Eneizan, Bilal Article Co-movement between GCC stock markets and the US stock markets: A wavelet coherence analysis Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Matar, Ali; Al-Rdaydeh, Mahmoud; Ghazalat, Anas; Eneizan, Bilal (2021) : Comovement between GCC stock markets and the US stock markets: A wavelet coherence analysis, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 8, Iss. 1, pp. 1-22, https://doi.org/10.1080/23311975.2021.1948658 This Version is available at: https://hdl.handle.net/10419/245088 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oabm20 Cogent Business & Management ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/oabm20 Co-movement between GCC stock markets and the US stock markets: A wavelet coherence analysis Ali Matar, Mahmoud Al-Rdaydeh, Anas Ghazalat & Bilal Eneizan | To cite this article: Ali Matar, Mahmoud Al-Rdaydeh, Anas Ghazalat & Bilal Eneizan | (2021) Comovement between GCC stock markets and the US stock markets: A wavelet coherence analysis, Cogent Business & Management, 8:1, 1948658, DOI: 10.1080/23311975.2021.1948658 To link to this article: https://doi.org/10.1080/23311975.2021.1948658 © 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Published online: 04 Aug 2021. Submit your article to this journal Article views: 441 View related articles View Crossmark data BANKING & FINANCE | RESEARCH ARTICLE Co-movement between GCC stock markets and the US stock markets: A wavelet coherence analysis Ali Matar 1 , Mahmoud Al-Rdaydeh 2 *, Anas Ghazalat 3 and Bilal Eneizan 4 Abstract: In this article, the co-movement between GCC and US stock market returns was investigated using the wavelet coherence method. The Dynamic Conditional Correlation GARCH (DCC-GARCH) modelling is then applied on timevarying components in order to provide a point of comparison with the results extracted from wavelet analysis. The investigation was conducted on the weekly stock index prices of two USA stock markets, namely Dow Jones and S&P 500 and six GCC stock markets, namely the United Arab Emirates, Saudi Arabia, Qatar, Oman, Kuwait, and Bahrain. The data were retrieved from Thomson Reuters’s data stream and the sample duration was from 7 January 2007 to 24 June 2018. As a result, a definite co-movement between several GCC stock markets and those of the US stock markets for a long term was found. Moreover, the results also displayed signs of the significant disparity between the co-movements of the stock markets throughout the scales of time during economic decline. This phenomenon was possibly expected during the economic decline, where a significant divergence occurred as opposed to co-movement. The implications of the findings for global investors were considerable due to the indication from long-term co-movement that these investors would not be capable of gaining simultaneous profit from time and portfolio being diversified. In fact, the results showed the major difference in the opportunities for international portfolio diversification throughout these markets in terms of scale and time. ABOUT THE AUTHORS Ali Matar is an Associate professor in Financial Economic and currently he is the Dean of Scientific Research at Jadara University, Irbid, Jordan. [email protected] Mahmoud Al-Rdaydeh is an assistant professor of finance at Ibn Rushd College for Management Sciences, Abha, Saudi Arabia. m. [email protected] Anas Ghazalat is an assistant professor of Accounting at Arab Open University, Amman, [email protected] Bilal Eneizan is an assistant professor at Business School, Jadara University, Irbid, Jordan. [email protected] PUBLIC INTEREST STATEMENT Despite the differences among countries, financiers have effectively started to use the trade financial instruments of the same standard and similar networks around the world. Hence, financial markets across the world have demonstrated a higher tendency to build “one single market” without borders. Therefore, it is necessary for investors to pay high attention to the evaluation of this co-movement due to the superior method of evaluating portfolio risk. The current study aims to scrutinize the dynamic co-movement between the stock market returns for the developing stock markets of the gulf cooperation council (GCC) and those of the US. This evaluation aims to provide helpful insights not only to local GCC investors but also to arbitrageurs who are interested in venturing into subjects related to GCC. Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 1 of 22 Received: 27 August 2020 Accepted: 22 June 2021 *Corresponding author: Mahmoud Al- Rdaydeh, Ibn Rushd College for Management Sciences, King Abdul Aziz Road, P.O. Box 447, Abha 61411, Saudi Arabia E-mail: [email protected] Reviewing editor: David McMillan, University of Stirling, Stirling, UK Additional information is available at the end of the article © 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Subjects: International Finance; Corporate Finance; Investment & Securities Keywords: Stock markets; Co-movement; GCC; USA; wavelet coherence 1. Introduction As a result of increasing globalization, the financial markets across the world have demonstrated a higher tendency to build “one single market” without borders. Despite the differences among countries, financiers have effectively started to speak the same language, and use the trade financial instruments of the same standard and similar networks around the world (Basdas, 2012). It could be said that the importance of this interdependence among stock markets is a result of its dominant role in the decision-making process of various parties. While considerable benefits have been provided by the interconnected market, such as lower costs, higher flexibility, and more choices, more naïve market participants are reluctant to invest due to its fragile structure. Another observation gained on the interconnected market is that prominent economies are places that gain the attention of portfolio capital and investors. Additionally, the low cost of a transaction is one of the advantages of this global assimilation and secure economic relation between countries. These elements would definitely contribute to positive impacts on stock market activities in the long run. Alternatively, this assimilation would possibly result in economic fragility over time. It is an impact that may be detrimental to stock markets on the global level, making it a disadvantage (Çelik & Baydan, 2015). There is no doubt that the co-movements between stock market indices pose crucial effects on the evaluation of portfolio risk and the implementation of financial policy and investment decisions. In respect of risk management, Rua and Nunes (2009) highlighted that lower gains stem from a stronger co-movement between the assets of a portfolio. Therefore, it is necessary for investors to pay high attention to the evaluation of this co-movement due to the superior method of evaluating portfolio risk. Naturally, policy-makers believe that the value of such co-movements between stock markets is dependent on the level of cooperation between the authorities involved in these markets. In other words, whenever stock markets are closely interconnected, there is a higher risk of unprecedented spread of market to others (e.g., Birău & Trivedi, 2013; Răileanu- Szeles & Albu, 2015; Samarakoon, 2011; Siminică & Birău, 2014). On the other hand, the investigation on the independence and co-movement between stock markets also proved the significant indirect beneficial effects acquired from countries which unite, especially the effects on US market and other developing markets (Choudhry, 2004). Co-movement was evaluated in previous studies by examining the non-overlapping sample durations or the correlation coefficient of rolling window (e.g., Brooks & Del Negro, 2004; Lin et al., 1994). Alternatively, several studies used a wavelet squared coherency, therefore, the significant international co-movement of stock returns between the developed markets was demonstrated (e.g., Rua & Nunes, 2009). Generally, whether the growing and arising financial markets are able to contribute to financial and economic development has become the topic of in-depth argument in the works of finance literature. Furthermore, economic development and financial growth were found to be positively related to each other. Samarakoon (2011) argued that US financial shocks pose the impact of driving interdependence, while the emerging markets lead to contagion to the US. Subsequently, there are three current standard classifications of stock markets according to the MSCI global index, namely the frontier, emerging, and developed markets. To be specific, Saudi Arabia, Qatar, and the UAE are the emerging markets, while Oman, Bahrain, and Kuwait are classified as frontier markets. Naturally, the emerging stock markets are considered as less productive compared to the developed markets due to several factors, such as their long-term structural uncertainties, frequent rounds of significant decline and growth, informational frictions, asymmetric volatility, and extreme functional fluctuations. Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 2 of 22 In recent decades, the reformation of global stock markets has been structural in nature. It is based on cross-border contracts, exchange control, derivatives, lack of restrictions on investment policy, the diversification of international portfolios, and the general liberalization of financial operations (Birău & Trivedi, 2013). Any study of the integration of global stock markets usually focuses on various economic and financial theories. Keynes (1936) highlighted the impacts of stock markets on the cost of equity, concluding that the interrelationship between stock markets and equity cost was enhanced. Therefore, it could be concluded that economic development was positively related to financial growth. For this reason, it was indicated that with positive economic performance, the same performance would be displayed by the stock market in the aspect of returns and profits (De Gregorio & Guidotti, 1995; Kirman, 1992). Notably, it is believed that the empirical information developed in studies lead to potential improvements in conditional volatility estimates. The improvements hold value in particular financial applications, such as option pricing, value at risk, portfolio optimisation, and optimal hedging (Awartani & Maghyereh, 2013). This research would assist global investors through the diversification of their portfolios, which are related to Markowitz modern portfolio theory in 1952. The contribution is added with a clearer understanding of the development of markets and institutions, effective price discovery, and further information on investment and economic progress, which lead to higher savings. Furthermore, Markowitz’s portfolio optimization theory was applied particularly in the investor’s decisions of asset allocation in the past. In this case, the investor decides to invest in assets, which could either be stocks, bonds or real estate. Aiming to solve optimization problems, the investor needs to utilize quantitative data to construct the stock portfolio. Additionally, the capital assets pricing model (CAPM) can be appraised to elaborate on the integration among stock markets (Sharpe (1964), Lintner (1965), and Mossin (1966)). This study mainly aims to scrutinize the dynamic co-movement between the stock market returns for the developing stock markets of the gulf cooperation council (GCC) and those of the US. This evaluation aims to provide helpful insights not only to local GCC investors but also to arbitrageurs who are interested in venturing into subjects related to GCC. Wavelet coherence analysis was applied as this technique enabled investors, particularly arbitrageurs, to obtain useful information regarding markets in the relevant regions. Due to the importance of obtaining new and detailed comprehension regarding the degree of global stock market assimilation, a threedimensional analysis of wavelet coherency was implemented. With this analysis, it was possible to determine the particular regions in a unified time interval-frequency band space where the diversification of two stock markets was present simultaneously. Additionally, a relatively low gain of portfolio diversification was present. The contents of this article are organised as follows: the second section comprises the review of literature, while the research methodology is presented in the third section. In the fourth section, an analysis of data is presented, followed by empirical findings in the fifth section. Lastly, this article ends with the sixth section which presents the implications of policy. 2. Literature review It is commonly known that a stock market movement within a country is influenced by the movement of either other stocks in other regions or countries, as proven in the empirical evidence presented in the literature (Alagidede & Mensah, 2016; Jiang & Yoon, 2020). In fact, a wide range of co-movements of stock markets between various countries was proven in several works of research (R. Ali et al., 2020; Meng & Huang, 2019; Mensi, 2019). Hyeongwoo et al. (2015) studied the spillover effects resulted from the economic decline of the US on developing Asian countries. Meanwhile, it was proposed in Alagidede and Mensah (2016) research on Africa’s emerging stock market that there was a diverse degree of interdependence throughout the time. Besides, the interdependence was low in African markets. On the other hand, K. Wang et al. (2011) found that the Chinese market had a high level of interdependence with the Japanese and Pacific markets. Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 3 of 22 It was also concluded in the previous studies by G. Lee and Jeong (2016) on the co-movement between Southeast Asian countries that five ASEAN founding countries exhibited a high cointegration degree. Therefore, they were capable of maintaining a higher degree of short-term interdependence when a negative shock, such as an economic decline, ended. Furthermore, the co-movement of 14 stock markets, namely TSEC, SSMI, SSE, RTS, NIKKI, NASDAQ, MXX, KSE (Korea), KSE, JKSE, Hang Seng, FTSE -100, BSE, and BVSP was investigated by Patel (2017). As a result, it was shown in the correlation analysis that the BSE had a constant positive relation with Hang Seng (0.45), FTSE-100 (0.32), MXX (0.27), NASDAQ (0.24), and BVSP (0.23). Moreover, it was found from a Granger causality test that the returns for BSE were influenced by BVSP, FTSE-100, and MXX only. The Johansen cointegration test also showed that a long-term association was present between several stock markets. Majid and Shabri (2018) employed the Granger causalities based on Vector Error Correction Model (VECM) to investigate the main Islamic stock markets of Indonesia, Japan, the UK, and the US. As a result, all of these markets were found to progress towards closer integration. It was also evident that the Japanese Islamic stock market affected the Indonesian Islamic stock market as a co-mover in comparison with the stock markets of the UK and the Islamic stock markets in the US in the multivariate and bivariate frameworks. Yao et al. (2018) used a normalized index to examine the effects of China’s financial liberalization policies on the assimilation of its stock market, specifically its impact on the rest of the world during from the year 2000 to 2015. As a result, their study proved a closer integration of the Chinese markets with global markets. Despite major fluctuations, QFII, QDII, and RQFII were particularly found to have constant beneficial influences on market integration. However, certain other policy reforms posed negative effects. Some de jure policy reforms, such as the RMB exchange rate liberalisation, posed fluctuating effects based on market conditions. Ghosh and Kanjilal (2016) examined the non-linear co-integration between international crude oil prices and the Indian stock market in a multivariate framework. Long-run equilibrium relationships between the variables were rejected for the entire data span. To further investigate this cointegration, threshold cointegration tests were conducted on three sub-phases, namely prior phase (phase I), post phase (phase III), and the most uneven phase (phase II). The tests were taken from 2 July 2007 to 29 December 2008. As a result, cointegration only occurred in phase III. Additionally, the Toda–Yamamoto version of the Granger causality tests indicated that the movements of international crude oil prices clearly had an effect on the stock market of India in phases II and III without any impacts of feedback. The test results also exogenously identified the cost of global crude oil. 2.1. Co-movement globally with wavelet approach R. Ali et al. (2020) investigated the co-movement between the Canadian credit default swaps market, the Stock market and volatility index (TSX 60 Index); the study employed the wavelet approach to present results in short-term, medium-term, long-term, and very long time. The wavelet co-movement results in the short-term and long-term were negative, while this relationship in the medium-term and very long-term period was strongly positive. Meng and Huang (2019) investigated the co-movement characteristics of effective exchange rates across frequencies and over time, the wavelet approach was employ to analyze the daily data from four Asian economies. Rua and Nunes (2009) investigated the international co-movement of stock market returns by employing wavelet analysis. Using the same method, Graham and Nikkinen (2011) observed this co-movement in the Finnish and international stock markets. In respect of the spillover effects in diverse time-scales, Fernandez (2005) examined the markets from the year 1990 to 2002 in the Pacific region, North America, G7 countries, Latin America, the developing Far East and Asia regions, Eastern Europe and the Middle East, and Western Europe. Meanwhile, spillover effects were found from the G7 countries to other sample countries, and an insignificant association was present in other regions with G7 countries in various scales of time. Furthermore, Gallegati (2012) employed wavelet analysis to the indices of the stock market of G7 countries, namely Brazil and Hong Kong. It was predictable that the contagion across global markets was present during the subprime crisis in the US. Gallegati concluded that although this impact of financial contagion is Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 4 of 22 usually scale-dependent, it is not homogenous across the scales. Moreover, Jiang et al. (2017a) implemented a novel approach in their study of the fluctuation of co-movement and volatility between the stock markets in the Association of Southeast Asian Nations (ASEAN) countries. Three-dimensional continuous wavelet transforms (CWT) was applied on the daily stock market returns which took place from 2009 to 2016. This included the estimates of the degree of interdependence and lag-lead association among the participants of the ASEAN trading link. As a result, stronger interdependence in these markets could be seen in the short term, which was predicted especially after external shocks. It was found from the Variational Modes Decomposition (VMD)-based copula estimation that the effects of an economic shock on the stock markets’ degree of co-movement lasted within a short term, with a reduction for over two years. This effect was also applied to the ASEAN trading link establishment. Notably, a strong basic interdependence was only present in Indonesia and Malaysia. It could be constantly seen from the CWT and Copula methods that in comparison with other members of ASEAN trading link, the interdependence degree was the lowest in Vietnam, while this degree was the highest in Indonesia. This result was in contrast to the empirical evidence which was previously obtained through conventional approaches. After a contagion and interdependence investigation was conducted on the Asia-Pacific region’s major equity market using wavelet decomposition, Dewandaru et al. (2016) found that shocks were usually transferred through fundamental connections. This approach had simultaneous impacts on equity markets. The highlights of their analysis revealed that fundamental contagion appeared through negative external shocks, such as the subprime crisis. In a similar study, Shahzad et al. (2017) examined contagion and interdependence in the equity markets of Greek and Europe. As a result, a rapid rise in the stock market co-movement could be seen through the short-run dependency during the global economic decline. Furthermore, the same authors (2016) implemented wavelet squared coherence analysis to investigate interdependence and contagion among the industry-level credit markets in the US. As a result, in comparison with other industries, the highest degree of interdependence was seen in the basic materials (Utilities) industry credit market, while the utility industry credit market had the lowest degree of interdependence. The cyclical effect was transferred from this market to all other industries. The co-movement of stock markets in Africa’s stock markets on the regional and global level was tested by Boako and Alagidede (2017) using the three-dimensional continuous Morlet wavelet transform methodology. With this method, a segmental analysis was conducted on the comovements with global markets, bilateral rates of exchange in US dollars and euros, and Africa’s four regional markets. As a result, it was proven that stronger co-movements were significantly reduced to short-run fluctuations. Besides being diverse in time and not homogeneous, the comovements consisted of phase difference arrow vectors, indicating lead-lag associations. It was possible for the lead-lag impacts and significant co-movements at short-term fluctuations to result in arbitrage. They would also contribute to diversification outcomes for local and international investors who held long-term investment horizons. It was also shown in their research that several equity markets in Africa were resistant from the rapid changes of the euro and dollar exchange rates. This implied that international investors were recommended to add more variation to their portfolio investments across these markets with no concern regarding the impacts of the rapidly changing prices. Additionally, Saâdaoui et al. (2017) investigated the dynamic association between the Islamic and conventional stock markets by conducting causality, cross-correlation, and wavelet-assisted cross-spectral analyses. As a result, it was clearly demonstrated that conventional and Islamic indexes were highly dependent on each other at a low-frequency and instability. This dependence occurred in the finest frequencies across diverse time horizons of investment time. It also had a different appearance during the periods of crisis in comparison to the calm periods. In contrast, indexes had the highest correlation during many periods and frequencies in the developed markets. However, they had a less significant association with the developing markets, especially for short-term horizons. For this reason, investors were provided with various investment alternatives and chances for portfolio diversification. It was proposed in the pre- and post-crisis Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 5 of 22 causality investigations at the end of the research that a bidirectional association was present in most cases. With this, further perceptions of multivariate forecasting were offered. 2.2. Co-movement in the GCC with the wavelet approach Jiang and Yoon (2020) explored the dynamic co-movement between oil and six stock markets (China, India, Japan, Saudi Arabia, Russia, and Canada) by using two types of wavelet analysis (wavelet multi-scale decomposition and wavelet coherence). Mensi (2019) examines the portfolio risk management and dynamic co-movements between crude oil and Saudi sector stock markets using wavelet approach and a Value at Risk measure. The results show significant co-movements between crude oil and stock sectoral markets over time and across frequencies. In Masih et al. (2010) study on GCC stock markets, a wavelet tool was used to evaluate the systematic risk via the “beta parameter”. As a result, a multiscale tendency could be seen from the beta coefficients in all GCC markets on average. This finding was in agreement with the theoretical argument where stock market investors consist of diverse time horizons as their trading strategies are different, which could be indicated from the GCC market attributes. Akoum et al. (2012) conducted an analysis on the long- and short-term dependencies among OPEC basket oil returns and GCC markets which spanned from 2002 to 2011 through the wavelet squared coherence method. It was emphasised that there was no significant relationship between oil and stock returns. Besides, there was an increase in the market dependencies after 2007 and an improvement in the profits of portfolio diversification in the short-term chances provided for investors. Furthermore, Aloui and Hkiri (2014) investigated the stock market returns for the GCC countries in terms of long- and short-term dependencies. This investigation was according to wavelet squared coherence, enabling the evaluation of the movements in time-frequency spaces. It was shown from the results that there was an increase in the association between the GCC stock markets during the economic decline. Besides, in comparison with long-term investors who were challenged with decreased diversification benefits, an improvement was present in the portfolio benefits for short-term investors. In the analysis of co-movement between the sukuk in GCC countries and sharia-compliant stocks, the wavelet squared coherency approach was applied by Aloui et al. (2015) in daily data. With this approach, the GCC global, corporate and financial service sukuk indexes, and GCC sharia stocks were covered. Furthermore, it was clear that sharia stocks and sukuk indexes were highly dependent on each other. However, a fluctuation in the level of strength of this co-movement occurred throughout frequency and time. Notably, the fluctuation was the most significant in the long term. Alaoui et al. (2015) examined the dynamics of co-movement on various scales of time or horizons of the Islamic Dubai Financial Market (DFM-UAE) index returns. This investigation involved their counterpart regional Islamic index returns, including Global Sukuk, Emerging Countries index, Developing Countries index, ASEAN index, and the GCC index. Additionally, an investigation was also conducted on the effects of the LIBOR on Islamic DFM-UAE returns. As a result, the DFM_UAE and GCC and Saudi markets were intersected with a similar degree of rapid changes and risk as to the Global Sukuk index. A significant non-homogeneous relationship was present between the scales for diverse durations. A contagion impact with a higher relation and interdependence within a delayed duration was present in closer markets. In fact, a flight to the Sukuk market with lower risks was evident mainly during the final phase of the economic decline. There was a tendency for the lead-lag analysis to imply that the GCC led to DFM-UAE, which resulted in Sukuk. Notably, this research emphasised the significance of the overnight LIBOR when the Islamic stock indices returned. Besides being the case, which took place in major transitions or shocks, policy implications for the variation of the portfolio among international investors were implied. Aloui et al. (2018) also investigated the relationship between the index of sharia stock and three Islamic bond yields in the GCC Islamic financial markets. Currently, this research involved the wavelet multiple-wavelet cohesion, cross-correlation, and correlation. As a result, a marked fluctuating pattern was present in the dynamic association between sharia stocks and Islamic bond Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 6 of 22 yields in the aspect of time-frequency. Besides, the short horizons, which were proven to have a significant positive relation to a negative linkage, were determined for larger time-scales. Nasreen et al. (2020) this study examines the connectedness between the sukuk- and shariahcompliant stock indices in the GCC financial markets, bivariate and multivariate wavelet approaches are applied. The sukuk bond–shariah stock index returns in the GCC at a multiscale level makes it easier for financial agents dealing with heterogeneous trading horizons to assess the benefits of diversifications. Based on the previous section in literature, most of previous GCC studies focus on the association between the GCC stock markets only without any linkage with global markets. Due to the importance of obtaining new and detailed comprehension regarding the degree of global stock market assimilation. This study respond to the integration of global stock markets focuses on various economic and financial theories by examining the dynamic co-movement between the stock market returns for the developing stock markets of the GCC and those of the US stock markets. 3. Methodology Various approaches were applied to examine the co-movement between stock markets. These approaches were performed by modelling the integration, co-movement, and contagions among financial markets in an equilibrium framework using VAR and Causality model (Awartani & Maghyereh, 2013; Bekhet & Matar, 2013a). However, an alternative branch of studies had modelled this relationship in the form of a single equation model (Bekhet & Matar, 2013b, 2013c; Boutabba, 2014; Lau et al., 2014; Matar & Bekhet, 2015; Matar, 2016). The wavelet coherence method had been implemented in a number of studies to analyse the economic and financial series of time. To be specific, a formal and thorough elaboration of this approach was made in the research conducted by Torrence and Compo (1998), Ramsey and Lampart (1998), Grinsted et al. (2004), and Rua and Nunes (2009). Furthermore, the theories of market integration were used in other works of research (Bekaert & Harvey, 1995; Black, 1974; Cooper & Kaplanis, 2000; Errunza & Losq, 1985; Eun & Janakiramanan, 1986; Hardouvelis et al., 2006; Stulz, 1981) so that the potential timescale-dependency to the procedures of integration could be introduced. This was due to the investor’s portfolio, which comprised assets with different time of investment. It was clear that the overall portfolio return referred to the amount of these individual elements in total (Lehkonen & Heimonen, 2014). In the current study, the co-movements between the GCC time series of stock market indices and the US index were investigated according to the wavelet approach. The Dynamic Conditional Correlation GARCH (DCC-GARCH) modelling is then applied on time-varying components to comprehend the dynamic correlation among the stock markets returns. The study employed the DCCGARCH technique in order to provide a point of comparison with the results extracted from wavelet analysis. 3.1. Wavelet coherence With a wavelet analysis, a time series could be separated into frequency elements. While the Fourier analysis has a full ability of representation and decomposition of stationary time series, the research could be conducted with a non-stationary time series through wavelets. Furthermore, wavelets promote the conservation of time for localized information, enabling co-movement to be measured in the time-frequency space. Wavelet analysis is based on the wavelet transform, where changes occur in the signal or time series with the assistance of functions known as wavelets. Moreover, it plays a role as a small wave consisting of the starting and ending points. When these waves are manipulated through its accurate motion and a squeezing or stretching process, a nonstationary and complex signal could be depicted as the elements of frequency that go through localisation in time. The wavelet analysis decompose a time series into highly specified time scales, rather than the blunt categorizations of short-term dynamics and long-term trends of traditional methods, such as error-correction models and co-integration relationships. And wavelet analysis Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 7 of 22 5.2. Results of DCC-GARCH model The DCC-GARCH model is suitable to assess co-movements between the stock markets of interests because it allows to directly infer the cross-market conditional correlations. The model inspects the dynamic correlation on decomposed components of time series. Table 3 furnish the magnitudes of key parameters. Figure 1. Analysis results. Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 14 of 22 The results of the co-movement from Table 3 between S&P stock market and GCC stock markets showed that the scale wise-estimated parameters were significant for all GCC stock markets except for Qatar at the short run. Values of beta is greater than alpha in all cases. Hence, a clear dominance of long-run persistence over short-run persistence is evident in the said time. The significance of DCC parameters specifies the existence of volatility clustering. The sum of alpha and beta less than one infers the evidence of the mean reverting process. For the DWJ stock market and GCC stock markets, the results were almost the same. Figure 2 shows the dynamic conditional correlation between the GCC stock market return and the US stock markets. The figures indicate that the DCC can display homogenous overlap to positive and negative values. The value ranges between −0.20 and 0.20. Hence, this time-scale accounts for the high risk and high return scenario. It appears that the conditional correlations are mostly negative from 2008 to 2010, Figure 1. (Continued). Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 15 of 22 indicating that higher volatility in US stock markets induces lower stock returns in GCC. The highest conditional correlations are observed in KSA and followed by UAE and Qatar, while the stock market in Bahrain and Kuwait are least correlated with the US markets among its peers. Figure 2. DCC plots. Note: D1, D2, D3, D4, D5 and D6 denote the investment horizon at (2–4) weeks, (4–8) weeks, (8–16) weeks, (16–32) weeks, (32–64) weeks and (64– 128) weeks, respectively. Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 16 of 22 Figure 2 depicts the dynamic conditional correlation DCC between each US stock market and the GCC stock markets at different time scales from d1 to d6 scales, where d1 to d3 represent the short run and d4-d6 represent the long run. The range of the DCC suggests the existence of ample scopes for portfolio formation at different time horizons. The results of Figure 2 and Table 3 indicate that the probability of higher returns is substantially higher in long-run periods. On the other hand, a comparatively higher possibility of more risk cannot be ruled out in the long run as well. Therefore, risk-averse players may get benefit from diversification of assets for up to 16 weeks. The players willing to take a risk for achieving excess profit may target diversification in the long run-up to 64–128 weeks. The horizontal axes of the figures show the time. All in all, the results to somewhat confirm the obtained ones from wavelet analysis, but the issue lies in analyzing the co-movement between the stock markets of interests in terms of the degree of association in time-varying frequency scales. Findings of wavelet coherence analysis can effectively evaluate the magnitude of prevailing association and dependence in short, medium, and long-run scales, while the DCC-GARCH Figure 2. (Continued). Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 17 of 22 examines the DCC by critically evaluating historical correlation and conditional volatility. Thus, DCCGARCH cannot extract the time varying scale-wise nature of dynamic correlation. 6. Conclusion and policy implications The co-movement of stock market returns for GCC and the US was examined in this study. Essentially, market co-movement is essential in deciding the allocation of assets and diversification of the portfolio. The recent works of literature have the tendency of placing a sole focus on the time-variation in co-movement. However, in reality, there are various scales of time in financial markets. By implementing the wavelet coherence approach, the evolution of co-movement between the markets over time and various scales of time was investigated. This study has proven that time-variations and scale-variations are present in these markets’ co-movements. Furthermore, the instability of the co-movement during the economic decline throughout the time and across the scales was clearly seen. It was also found that there was a significant longterm degree of co-movement between several GCC stock markets and the US stock markets. From the findings, a diverse co-movement across the scales of time during economic decline was proven. Specifically, it was found that the co-movement of the GCC and the US stock markets was highly diverse during the time of economic decline. There was a concentration of co-movement at a medium scale of time, which was for 32 to 64 weeks. The diverse characteristics of the economic decline or changing regime possibly resulted in the variation in the co-movement dynamics. Therefore, further study is required to investigate the exact factor of this variation in co-movement. Essential implications could be made from this study for international investors. It was indicated from the co-movement over a longer scale of time that the advantages of the diversification of portfolio and time are unobtainable by international investors. Significant variations were found in the chances for international portfolio diversification across these markets, specifically in terms of time and scale. This implies that GCC stock markets gives an attractive diversification opportunity for local and international investors when they construct their own portfolios. Additionally, the diversification of the portfolio was present during economic decline. However, developing a diversified portfolio was a challenge due to the instability in the co-movement between the stock markets. This study has provided contributions to the existing works of literature through the implementation of the wavelet coherence method to investigate the co-movement of financial markets in the GCC with the US market. Furthermore, the investigation on the association between co-movement and the indicators of stock markets could provide insights regarding the reaction of stock markets towards the changing stock cost in the same emerging markets. With that being said, it could be highlighted that there is a general connection between GCC stock markets. These markets also have a relation with the US stock markets. Last but not least, it could be concluded that the KSA market is a GCC market which receives the highest impact. This finding is highly crucial for various parties related in the field of stocks market, such as the Table 3. DCC-GARCH estimation S&P vs KSA UAE KUW OMA QAT BAH α0.020344** 0.025488** 0.003537** 0.034179 0.019201* 0.036216** β0.969505** 0.971655** 0.804351** 0.852319** 0.968573** 0.789064** α+β0.989849 0.997143 0.807888 0.886498 0.987774 0.82528 DWJ vs KSA UAE KUW OMA QAT BAH α0.026910** 0.019296* 0.003549** 0.025208 0.011008 0.033944** β0.968680** 0.970681** 0.809793** 0.862441** 0.969892** 0.482977 α+β0.995590 0.989977 0.813342 0.887649 0.9807 0.516921 * and ** denote statistical significance at the 5% and 1% levels respectively. Matar et al., Cogent Business & Management (2021), 8: 1948658 https://doi.org/10.1080/23311975.2021.1948658 Page 18 of 22 governments, investors, and policymakers. For instance, Significant implications of this study results could be made for policymakers and government. For policymakers, the significant longterm degree of co-movement between several GCC stock markets and the US stock markets implies that any growth of the US stock market should be considered for policymakers in GCC countries. Also governments especially in GCC countries could pay attention for the results of this study such as the instability of the co-movement during the economic decline throughout the time and across the scales. Besides, the co-movement of the GCC and the US stock markets was highly diverse during the time of economic decline. The government can get benefit from these results for their public data and statistics and for controlling and monitoring financial markets. Funding The authors received no direct fund for this research Author details Ali Matar 1 ORCID ID: http://orcid.org/0000-0003-0599-5855 Mahmoud Al-Rdaydeh 2 E-mail: [email protected] ORCID ID: http://orcid.org/0000-0002-8810-4837 Anas Ghazalat 3 Bilal Eneizan 4 1 Department of Finance and Banking, Jadara Universiy, Jordan. 2 Business Administration, Ibn Rushd College for Management Sciences, Saudi Arabia. 3 Accounting, Arab Open University, Jordan. 4 Marketing, Jadara University, Irbid, Jordan. Citation information Cite this article as: Co-movement between GCC stock markets and the US stock markets: A wavelet coherence analysis, Ali Matar, Mahmoud Al-Rdaydeh, Anas Ghazalat & Bilal Eneizan, Cogent Business & Management (2021), 8: 1948658. References Akoum, I., Graham, M., Kiviaho, J., Nikkinen, J., & Omran, M. (2012). Co-movement of oil and stock prices in the GCC region: A wavelet analysis. 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