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This research provides some evidence by the vine copula approach, suggesting the significant and symmetric causal relation between subsections of Baltic Exchange and hence concluding that investing in different indexes, which is currently a risk diversification system, is not a correct risk reduction strategy.

The daily observations of Baltic Capesize Index (BCI), Baltic Handysize Index (BHSI), Baltic Dirty Tanker Index (BDTI) and Baltic LNG Tanker Index (BLNG) over an eight-year period have been used. After collecting data, calculating the return and estimating the marginal distribution of return rates for each of the indexes applying asymmetric power generalized autoregressive conditional heteroskedasticity and autoregressive moving average (APGARCH-ARMA), and with the assumption of skew student's t-distribution, the dependence of Baltic indexes was modeled based on Vine-R structures.

A positive and symmetrical correlation was observed between the study groups. High and low tail dependence is observed between all four indexes. In other words, the sector business groups associated with each of these indexes react similarly to the extreme events of other groups. The BHSI has a pivotal role in examining the dependency structure of Baltic Exchange indexes. That is, in addition to the direct dependence of Baltic groups, the dependence of each group on the BHSI can transmit accidents and shocks to other groups.

Since the Baltic Exchange indexes are tradable, these findings have implications for portfolio design and hedging strategies for investors in shipping markets.

Vine copula structures proves the causal relationship between different Baltic Exchange indexes, which are derived from different types of markets.

The purpose of this paper is to examine the relationship between financial development, openness in financial services trade and economic growth in BRICS countries for the period 1990–2012.

An index for financial development has been constructed using principal component analysis technique by including banking sector development, stock market development, bond market development and insurance sector development. For the robustness of the result, the long-run cointegrating relationship amongst the variables has been analyzed.

Overall financial development has a positive and significant impact on economic growth. To take the full advantage of openness in financial services trade, countries need to put more emphasis on the development of their stock markets, bond markets and the insurance sector. The result shows that openness in financial services trade has a positive impact on economic growth when the stock market, bond market and insurance sector are included in the system.

The policy implication of the findings is that policymakers should focus more on developing all four areas of finance to get the full benefit of the financial system on the process of economic growth.

The authors have constructed the better indicators of financial development in the case of BRICS economies. Most of the studies in BRICS economies have measured the development of the financial sector as either banking sector development or stock market development. However, the present study includes all four areas of finance (banking sector development, stock market development, insurance sector development and bond market development) into account.

Recently, decoupling between the US and China has emerged as an important issue in global economics. We propose an analytical framework for trade decoupling analysis, borrowing the idea from the production function in non-competitive input-output tables. Using that methodology, we analyze the mobile phone trade network subject to various measures imposed by the US. A scenario analysis is performed to compare the extent of decoupling after a trade war with worst-cases. In bilateral trade, China’s share of total US imports fell significantly in 2019 compared to 2017. However, China’s indirect exports to the US increased during the same period. A similar pattern is observed in the global trade network visualized via multidimensional scaling (MDS). China’s out-degree centrality decreased slightly, while Vietnam’s role expanded. Actual figures for 2019 show a decreased out-degree centrality for Chinese final good exports, but a much higher one in the scenarios. Also, China’s indirect exports to the US have increased. But China does not appear to play a key role in the network as assumed in the scenario. Throughout the study, intermediate goods were treated homogeneously, and further studies considering the heterogeneity of input-output linkages are needed.

Unlimited quantitative easing (QE) is one of the monetary policies used to stimulate the economy during the coronavirus disease 2019 (COVID-19) pandemic. This policy has affected the financial markets worldwide. This empirical research aims at studying the dependence among stock markets before and after unlimited QE announcements.

The copula-based GARCH (1,1) and minimum spanning tree models are used in this study to analyze 14 series of stock market data, on 6 ASEAN and 8 other countries outside the region. The data are divided into two periods to compare the differences in dependence.

The findings show changes in dependence among the volatility of daily returns in 14 stock markets during each period. After the unlimited QE announcement, the upper tail dependence became more apparent, while the role of the lower tail dependence was reduced. The minimum spanning tree can show the close relationships between stock markets, indicating changes in the connection network after the announcement.

This study allows the dependency to be compared between stock market volatility before and after the announcement of unlimited QE during the COVID-19 pandemic. Moreover, the study fills the literature gap by combining the copula-based GARCH and the minimum spanning tree models to analyze and reveal the systemic network of the relationships.

The international trade literature has established that export product diversification lowers export product revenue instability. The current analysis investigates whether this finding carries over services exports.

The empirical analysis covers a sample of 152 countries over the period 1980–2014 and employs the two-step system generalized method of moments (GMM) approach.

The empirical findings indicate that services export diversification reduces services export revenue instability both over the full sample as well as over sub-samples of high-income countries (HICs), least developed countries (LDCs) as well as developing countries (i.e. non-HICs) that are not LDCs. HICs appear to experience a higher positive effect of services export diversification on services export revenue instability than in developing countries. The analysis also shows that countries that further open-up to international trade enjoy a greater reducing effect of services export diversification on the instability of services export revenue.

This analysis, therefore, adds to the existing studies on the relationship between export product diversification and the instability of revenue derived from goods exports by focusing on the services export side. An important message from the analysis is that countries that diversify their services export basket enjoy lower services export revenue instability when they further integrate into the world trade market.

This study highlights the importance of services export diversification, including for stabilizing services export revenue to services traders. Diversifying services export items, including across traditional and modern services sectors involves the implementation of a wide range of policies and measures, of which the liberalization of the services sectors through reduction and eventually the elimination of services trade barriers; the improvement of the business environment and the development of domestic financial markets (see for example, Hoekman, 2017). It could be interesting that another study consider policies and measures that could promote services export diversification.

To the best of the authors’ knowledge, this is the first time this topic is being addressed, including empirically.

This study examines the impact of regional economic integration (REI) on stock market linkages in the BRICS (Brazil, Russia, India, China and South Africa) economic bloc. In this type of study, the BRICS framework is an appealing empirical case, given its uncommon characteristics. For example, BRICS member states come from remote geographic locations (Africa, Asia, Europe and South America) and have contrasting socioeconomic profiles.

An empirical design is framed from the perspective of bilateral trade between South Africa and BRIC. The author accepts trade intensity as a proxy of regional economic integration and then examines the resulting effect on the stock market co-movement within BRIC. The study applies a two-step econometric procedure of the BEKK-MGARCH and panel data models.

Overall, bilateral trade, as a proxy of economic inwctegration, is associated with an increase in stock market integration. This positive relationship is particularly observed during episodes of surplus trade, and more interestingly, was initiated three years after BRICS’ existence and continues to grow at an increasing rate.

The study outcome should benefit international trade practitioners and global investors interested in portfolio diversification or concerned with risk spillovers.

First, notwithstanding South Africa's significant economic presence in the African continent, to the best of the author’s knowledge, this is the first study to empirically evaluate the BRICS economic integration on their stock market linkages from the perspective of South Africa. The value of this contribution is that further work may investigate the bidirectional spillover impact conveyed by South Africa's trade interactions within the juxtaposition of Africa and BRICS economies. Second, given that research on REI and stock market integration has historically concentrated on mature regional blocs of Europe, Asia, South and North America, the current study advances knowledge while correcting the prevailing literature imbalance.

The purpose of this paper is to illustrate a profitable and original index options trading strategy.

The methodology is based on auto regressive integrated moving average (ARIMA) forecasting of the S&P 500 index and the strategy is tested on a large database of S&P 500 Composite index options and benchmarked to the generalized auto regressive conditional heteroscedastic (GARCH) model. The forecasts validate a set of criteria as follows: the first criterion checks if the forecasted index is greater or lower than the option strike price and the second criterion if the option premium is underpriced or overpriced. A buy or sell and hold strategy is finally implemented.

The paper demonstrates the valuable contribution of this option trading strategy when trading call and put index options. It especially demonstrates that the ARIMA forecasting method is a valid method for forecasting the S&P 500 Composite index and is superior to the GARCH model in the context of an application to index options trading.

The strategy was applied in the aftermath of the 2008 credit crisis over 60 months when the volatility index (VIX) was experiencing a downtrend. The strategy was successful with puts and calls traded on the USA market. The strategy may have a different outcome in a different economic and regional context.