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The purpose of this paper is to investigate the stability of the long‐run relationships between emerging (India, China, South Korea, and Taiwan) and developed stock markets (USA and Japan). The study aims at adding to the literature on market integration by investigating the hypothesis that the Asian emerging stock markets are increasingly converging with the US stock market over time.

The authors use time varying cointegration tests (rolling and recursive cointegration) which allow for time variation in the underlying data generating process (possible structural breaks in the long‐run relationships). Ten year index data from mid 1998 to 2008 of the respective stock markets have been used for this study.

Empirical findings support the presence of one long‐run relationship (cointegration vector) between emerging and developed stock markets. Both domestic and external forces affect stock market behavior, leading to long‐run equilibrium but the individual Asian emerging stock markets tend to display stronger linkages with the USA (developed counterpart) rather than with their neighbors. The degree of convergence among Asian emerging markets has increased over the last few years.

This is the first paper to study cointegration among Asian emerging stock markets namely India, China, South Korea, and Taiwan, as well as their cointegration with the developed stock markets of the USA and Japan.

Purpose: Through globalization, financial markets have become more integrated and their tendency to act together has increased. The majority of the literature states that there is a cointegration between developed and emerging markets. How do positive or negative shocks in developed markets affect emerging markets? And how do positive or negative shocks in emerging markets affect developed markets? For this reason, the aim of the study is to investigate the asymmetric causality relationship between developed and emerging markets with Hatemi-J asymmetric causality test.

Design/methodology/approach: In this study, the Dow Jones Industrial Average (DJIA) index was used to represent developed markets and the Morgan Stanley Capital International (MSCI) Emerging Market Index was used to represent emerging markets. The asymmetric causality relationship between the DJIA Index and the MSCI Emerging Market Index was investigated using monthly data between January 2009 and April 2019. In the first step of the study, the Johansen Cointegration Test was used to determine whether there is a cointegration between the markets. In the next step, the Hatemi-J asymmetric causality test was applied to see the asymmetric causality relationship between the markets.

Findings: There is a weak correlation between developed and emerging markets. This result is important for international investors who want to diversify their portfolios. As a result of the Johansen Cointegration Test, it was found that there is a long-term relationship between the MSCI Emerging Market Index and the DJIA Index. Therefore, investors who make long-term investment plans should not forget that these markets act together and take into account the causal relationship between them. According to the asymmetric causality test results, a unidirectional causality relationship from the MSCI Emerging Market Index to the DJIA Index was determined. This causality shows that negative shocks in the MSCI Emerging Market Index have positive effects on the DJIA Index.

Originality/value: This study contributes to the literature as it is one of the first studies to examine the asymmetrical relationship between developed and emerging markets. This study is also useful in predicting the short- and long-term relationship between markets. In addition, this study helps investors, portfolio managers, company managers, policymakers, etc., to understand the integration of financial markets.

Design/Methodology/Approach: This chapter applies tests associated with the adaptive market hypothesis (AMH) and Johansen cointegration test. AMH acknowledges the views of the efficient market hypothesis and behavioural finance approach.

Purpose: Cryptocurrencies are considered a new asset class by multiasset portfolio managers. Hence, we examine the AMH and cointegration in the cryptocurrency market to know whether select cryptocurrencies can be diversified.

Findings: We find that cryptocurrencies are efficient and there is a long-run relationship among constituent series, and there is no short-run causality derived from bitcoin, Ethereum and litecoin to bitcoin, while stellar and Dogecoin have short-run causality to bitcoin.

Originality/Value: This chapter is different from the existing one as this is the first study in which the AMH and Johansen cointegration test are applied to check the efficiency and relationship of Bitcoin, Ethereum, and Monero, Stellar, litecoin and Dogecoin.

The purpose of this paper is to explore the association between economic factors (consumer price index, real gross domestic product per capita, base discount rate, and rate of unemployment) and numbers of hospital psychiatric beds.

Time series analytical techniques (unit root and cointegration tests) were applied to two regional data sets from the nineteenth century (North Carolina, USA; Berkshire, UK) and three national data sets in the twentieth century (US; UK; Italy) to test the hypothesis of a relationship.

All data sets suggest a long‐run relationship between economic factors and psychiatric bed numbers. Increase of consumer price predicted a decrease of hospital beds (and vice versa) in all data sets and was the strongest predictor of changes in psychiatric bed numbers. Hence, economic factors appear to be an important driver for the supply of hospital beds.

Cointegration tests are not true causality tests as they only measure the ability to forecast the value of an X variable knowing the value of N other variables. Therefore, one cannot rule out that the relationship between economic factors and psychiatric hospital beds is an indirect one, caused by another unidentified factor. Also, this study alone does not provide evidence to decide whether economic factors mainly influence demand or supply, although various findings suggest the latter.

CPI is of particular significance for changes in psychiatric bed provision, and co‐integration tests are a useful method to explore such association.

This study is the first one to apply time series analytical techniques to explore the role of economic factors in the processes of psychiatric institutionalisation and deinstitutionalisation.

This paper examines bilateral and multilateral cointegration properties of the German stock market and the three most credible Central European candidates for membership in the European Union. The cointegration tests cover the time period of July 5, 1995, to March 27, 2002. The DAX is used to represent the German equity market and the IFCI indices represent the Central European equity markets. Application of the Johansen (1988) cointegration procedure indicates that there is no long‐term relationship between the German market and the Central European markets, either individually or as a group. The Granger‐causality test does reveal some short‐term effects running from the German to the Polish market but no reverse causality. Overall, the results suggest that neither trade, financial liberalization, nor the introduction of the Euro has yet had sufficient impact to bring these markets into a long‐term relationship.

Foreign exchange rates are examined using cointegration tests over various time periods linked to regime shifts in central bank behavior. The number of cointegrating vectors appears to vary across these regime changes within the foreign exchange market. For example, cointegration is not generally found prior to the Plaza Agreement of September 22, 1985, but it is present after that date. The significance of these changes is evaluated using a likelihood ratio procedure proposed by Quintos (1994). The changing nature of the cointegrating relationships indicate that certain aspects of central bank activity do have long-term effects on exchange rates.

Islamic capital markets, i.e. ICMs, featured as socially responsible investments, less levered and more reflective of the real sector, are a recent development in financial markets showing an impressive growth and offering the potential for portfolio diversification benefits. The purpose of this study is to understand the long-run integration of ICMs in the Asia/Pacific region.

This sample includes ICMs of Asia/Pacific region (such as Pakistan, India, China, Japan, Thailand, Malaysia and Indonesia) for 280 weeks between 2011 and 2016. Selected indexes are FTSE Islamic except for Pakistan and Indonesia. Evidence was obtained through the application of correlation, unit root, Johansen cointegration and Granger causality tests.

This study documents the results of the integration of ICMs based on developmental stage, geographic location, economic cooperation and shared religious beliefs/civilization. Partial support was observed for all hypotheses: integration of markets based on economic grouping, location, economic treaties and shared civilization. The Japanese market was the most integrated, while the Indian and Malaysian markets are the least. Evidence supports the shift of leadership role from advanced markets to emerging markets.

Selected diversification opportunities are available for global Islamic as well as conventional investors. This study recommends closer cooperation among Muslim majority countries of the region, as well as the effective use of economic cooperation treaties for joint economic growth and prosperity.

This study contributes to the literature by providing evidence on the integration of ICMs in an economically important region (Asia/Pacific) that is witnessing an increasing role in the global gross domestic product and international trade.

This paper examines the cointegration of wheat market prices in Northern Bangladesh. Results are based on weekly wholesale price data on wheat collected from the Department of Agricultural Marketing (DAM) in eight markets in the Rangpur division of Northern Bangladesh. The data has 208 observations for wheat in each of the eight markets ranging over a period of January 2006 to December 2009. Johansen’s cointegration test reveals that most of the wholesale markets of wheat in the Rangpur division are co-integrated which indicates that price signals and information are transmitted smoothly across the markets. The discovery of the market integration appears to be quite significant for the success of price policy and market liberalization programs which are being undertaken in Bangladesh.

The purpose of this paper is to look at the contemporaneous movement of the stock market indices of the five most COVID-infected countries, namely, the USA, Brazil, Russia, India and UK after the first wave along with market indices of the three least affected countries, namely, Hong Kong, South Korea and New Zealand during the first wave.

Data have been collected from the website of Yahoo finance on daily closing values of five indices. Augmented Dickey–Fuller test with its three forms has been applied to check the stationarity of the select five indices at the level and at the first difference before the pandemic, during the pandemic and post-first wave of the pandemic. Johansen cointegration test is applied to find out that there is no cointegration among the select five indices.

The five countries do neither fall in the same economic and political zone nor do they have the same economic status. But during the period of pandemic and the new-normal period, the cointegration is very distinct. The developing and developed nations thus stood at an indifferentiable stage of the economic crisis which is well reflected in their stock markets. However, the least three COVID-affected countries do not show any cointegration during the pandemic time.

The comovement even seen during the normal time in the other studies is not compared to a similar period in earlier years. But, in this study to look into the exclusive effect of COVID pandemic, the period most affected with it is compared with the period after it and that in the immediate past year had no effect.

The purpose of this paper is to study the market efficiency, unbiasedness and the direction of causality among four agricultural commodity futures contracts for a forecasting horizon of 28 days, 56 days and 84 days which are traded at National Commodity and Derivatives Exchange Ltd.

To analyse the efficiency of futures market in Indian scenario, we focus on maize, chickpea, soybean and wheat which are among the most important agricultural commodities traded in India. In the first step, Augmented Dickey-Fuller test and nonparametric Phillips-Perron approaches have been used to examine the stationarity of all futures and spot price series. After testing the presence of cointegration in futures and spot series using Johansen’s Cointegration approach, the joint restrictions of β ₀=0, β ₁=1 and β ₁=1 on the cointegrating vectors were imposed to test whether the futures price is an unbiased predictor of spot at contract maturity. In the next step, linear Toda and Yamamoto (1995) and the nonparametric Diks and Panchenko (2006) causality tests were applied to examine the direction of causality. Finally, nonlinear test were applied on the vector error correction model (VECM) residuals to investigate whether any remaining causality is strictly nonlinear in nature.

The results of cointegration tests between futures and spot prices of the selected agricultural commodities indicated a long term relationship do exist in three out of four futures contracts. However, the Wald tests results on the cointegrating vectors indicate markets as inefficient and biased. Further, analysis of short-term relationship using alternate tests of causality do not give consistent results for same commodity series indicating that results may vary due to alternate measures and specifications. Finally, if we consider the results of Diks-Panchenko test on the filtered VECM-residuals, results provide evidence that if cointegration is taken into account; neither spot nor future leads or lags the other consistently.

The results are based on the sample of four agricultural futures commodity contracts. The study can be extended to a larger sample of contracts and relative efficiency of each contract can be explored.

There are very few studies that have explored the efficiency, unbiasedness and direction of causality using both linear and nonlinear techniques for Indian agriculture commodity futures market for different forecasting horizons.