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Capital markets thrive on information, and the information revolution has transformed these markets all over the world. Investors can now keep track of the movements of capital markets in real-time and they react to the flow of information from around the world. One of the concerns of stock market investors is whether the markets operate efficiently, independently, and with sound fundamentals. However, real market movements tend to exhibit a link as is evident from recent market movements across the world.

The assessment of interdependence between stock markets is an important aspect of international portfolio management. The aim of this chapter is to examine the shock and volatility spillover between the Standard and Poor’s 500 (S&P500) index from the United States (US) Stock Exchange and the Istanbul Stock Exchange 100 (BIST100) index from the Stock Exchange Istanbul.

S&P500 index, which is the most important index representing US markets, and BIST100 index, which is the index representing the Turkish market, were used as variables in this study. In the analysis, the causality in variance test was applied to determine the volatility spillover between these two markets. Later, multivariate GARCH (MGARCH) models were used to measure the volatility spillover in the markets. VAR(1)-GARCH (1,1)-Diagonal BEKK model was applied to the daily data to determine the shock and volatility spillover in the markets.

As a result of the variance causality test, it was found that there is a bi-directional volatility spillover between S&P500 index and BIST100 index. When the return spillover between the markets is examined, a one-way spillover from the S&P500 index to the BIST100 index emerged. Diagonal BEKK model results show that each market is affected by its own news (unexpected shocks) and volatility. Furthermore, the volatility is persistent for both markets. These findings demonstrate that the US market and the Turkish market interact with each other.

We investigate whether or not the effects of the subprime financial crisis on 12 Asian economies are similar to those of the Asian financial crisis by examining volatility spillovers and time-varying correlation between the US and Asian stock markets. After pretesting volatility causality and constancy of correlation, we estimate an appropriate smooth-transition correlation VAR-GARCH model for each Asian stock market. First, the empirical evidence indicates stark differences in stock market linkages between the two crises. The volatility causality comes from the crises-originating country. Volatility in Asian stock markets Granger-caused volatility in the US market during the Asian crisis, whereas volatility in the US stock market Granger-caused volatility in Asian stock markets during the subprime crisis. Second, decreased correlations during the period of financial turmoil were observed, especially during the Asian financial crisis. Third, the estimated points of transition in the correlation are indicative of market participants’ awareness of the ensuing stock market crashes in July 1997 and in September 2008.

Introduction – The rapid flow of information between the markets eliminates the possibility of diversifying the portfolio by bringing the markets closer, and may cause the volatility in a market to spread to another market. In this context, revealing the relationships between conventional and participation markets or financial assets is important in terms of portfolio diversification and risk management.

Purpose – The major aim of this work is to analyse the existence of volatility spillover between conventional stock index and participation index based on the indexes in Turkish Capital Markets. BIST-30 and Katılım-30 indexes are used as the representatives of conventional stock index and participation index, respectively.

Methodology – Firstly, the univariate HYGARCH (1,d,1) parameters are calculated, and secondly, the dynamic equicorrelation (DECO) methodology is applied. DECO model is proposed to simplify structural assumptions by introducing a structure in which all twosomes of returns take the same correlation for a given time period. In this way, DECO model enables to have an optimal portfolio selection in comparison to an unrestricted time varying-dynamic correlation approaches and gives more advanced forecasting ability for the duration of the financial crisis periods compared to the various portfolios.

Findings – There is a strong correlation between BIST-30 and Katılım-30. They are affected by the same shocks. We expect to see different investor behaviours for Katılım-30 and BIST-30. However, they seem to have almost the same investor profile. In addition, there is a causality in both ways and volatility spillover between them.

Many Information Theoretic Measures have been proposed for a quantitative assessment of causality relationships. While Gouriéroux, Monfort, and Renault (1987) had introduced the so-called “Kullback Causality Measures,” extending Geweke’s (1982) work in the context of Gaussian VAR processes, Schreiber (2000) has set a special focus on Granger causality and dubbed the same measure “transfer entropy.” Both papers measure causality in the context of Markov processes. One contribution of this paper is to set the focus on the interplay between measurement of (non)-markovianity and measurement of Granger causality. Both of them can be framed in terms of prediction: how much is the forecast accuracy deteriorated when forgetting some relevant conditioning information? In this paper we argue that this common feature between (non)-markovianity and Granger causality has led people to overestimate the amount of causality because what they consider as a causality measure may also convey a measure of the amount of (non)-markovianity. We set a special focus on the design of measures that properly disentangle these two components. Furthermore, this disentangling leads us to revisit the equivalence between the Sims and Granger concepts of noncausality and the log-likelihood ratio tests for each of them. We argue that Granger causality implies testing for non-nested hypotheses.

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.

This chapter aims to determine whether diversification benefits accrue from adding emerging market hedge funds (EMHFs) to an emerging market bond/equity portfolio, and subsequently whether the type of exposure hedge funds provide is justified by their fees. We use multivariate cointegration analysis to show that the advantages of adding hedge funds to balanced portfolios are limited for the three regions of Asia, Eastern Europe, and Latin America, as well as for the entire global emerging market universe. In summary, we find that emerging market hedge funds are generally redundant for diversifying long-only emerging market investment portfolios with long-term investment horizons. This result also holds when we extend our sample by the global financial crisis in 2008 and 2009 and allow for structural breaks according to the Gregory-Hansen (1996) test. Hence, even during the global financial crisis in 2008 and 2009, when risk diversification was most needed, long-term comovements between hedge funds and traditional assets is, with the exception of the Eastern European region, not disrupted. Because EMHF returns are heavily influenced by the emerging market equity and bond markets, we conclude that the “alpha fees” charged by EMHFs may not always be appropriate for the three main regions under consideration. This also holds, however, to a lesser extent, for a global diversification among hedge funds and traditional assets in emerging markets.

This paper investigates the nature of the causal relationship between stock price and exchange rate related to five emerging countries – Mexico, Argentina, Brazil, Thailand, and Malaya – by applying the techniques of unit root, a test proposed by Toda and Yamamoto (1995), the variance decomposition analysis, and the impulse response function. Empirically, we have found that there is a unidirectional Granger causality for all these countries. This relationship is very important, especially for the case of Malaya. Our results also suggest that total convertibility strengthens the relation between the two markets, but cannot be considered as a crucial determining factor.