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Purpose – This chapter aims to investigate the stock market comovements between Mexico and the world capital market using nonlinear modeling tools.

Methodology/approach – We apply recent nonlinear cointegration and nonlinear error correction models (NECMs) to investigate the comovements between stock prices over the recent period.

Findings – While the previous literature only highlights some evidence of time-varying comovements, our chapter aims to specify the mechanism characterizing the comovement process through the comparison of two nonlinear error correction models (NECMs). It shows a nonlinear relationship between stock prices that are activated per regime.

Originality – Studying the integration hypothesis between stock markets over the recent financial crisis, our findings highlight strong evidence of significant comovements that explain the global collapse of stock markets in 2008–2009.

The purpose of this paper is to propose an empirical procedure for examining the time‐varying features of cross‐market correlations in selected Gulf stock markets.

The paper directly infers the cross‐market linkages from the stock data using a multivariate dynamic conditional correlation GARCH model (DCC‐GARCH). The paper attempts to date the structural breaks in the time‐paths of the conditional correlation indices to investigate whether the cross‐market comovement encompasses significant changes in nature or not.

Conditional cross‐market correlations between studied markets are shown to be time‐varying, past‐dependent and subject to structural breaks. However, the comovements are still small within the Gulf region and insignificant between the Gulf stock markets and the world market.

Even though the paper attempted to relate the observed changes in market linkages to major economic and political events that the Gulf region experienced during the sample period, a more careful, in‐depth analysis is needed since the primary objectives of this paper consist only of measuring stock market comovements and detecting their possible structure changes.

For global investors, there is still room for international and regional diversification in Gulf markets, given the low degree of comovements documented in the study.

The application of the DCC‐GARCH model and structural change test in a linear framework appears to be suitable for studying the time‐varying properties of cross‐market linkages between markets in the Gulf region. It also provides information about the degree of financial integration of the studied markets with the world stock market through an analysis of the conditional correlation coefficients.

We propose a novel dynamic factor model to characterise comovements between returns on securities from different asset classes from different countries. We apply a global-class-country latent factor model and allow time-varying loadings. We are able to separate contagion (asset exposure driven) and excess interdependence (factor volatility driven). Using data from 1999 to 2012, we find evidence of contagion from the US stock market during the 2007–2009 financial crisis, and of excess interdependence during the European debt crisis from May 2010 onwards. Neither contagion nor excess interdependence is found when the average measure of model implied comovements is used.

This paper aims to examine the comovement among green bonds, energy commodities and stock market to determine the advantages of adding green bonds to a diversified portfolio.

Generic 1 Natural Gas and Energy Select SPDR Fund are used as proxies to measure energy commodities, bonds index of S&P Dow Jones and Bloomberg Barclays MSCI are used to represent green bonds and the New York Stock Exchange is considered to measure the stock market. Granger causality test, wavelet analysis and network analysis are applied to daily price for the select markets from August 26, 2014, to March 30, 2021.

Results from the Granger causality test indicate no causality between any pair of variables, while cross wavelet transform and wavelet coherence analysis confirm strong coherence at a high scale during the pandemic, validating comovement among the three asset classes. In addition, network analysis further corroborates this connectedness, implying a strong association of the stock market with the energy commodity market.

This study offers new evidence of the temporal association among the US stock market, energy commodities and green bonds during the COVID-19 crisis. It presents a novel approach that measures and evaluates comovement among the constituent series, simultaneously using both wavelet and network analysis.

The various stock market indexes are interrelated due to the similar fundamentals which determine the movement in the respective markets. Applying the efficient market hypothesis, an investor should not be able to predict the movement of one index based on the past movement of another index. If the stock markets are efficient, then no long term comovement should exist between stock market indexes. The existence of a long term relation can be tested by use of cointegration tests and common serial correlation feature tests. If no cointegration exists and if no common serial correlation feature exists, then we would not be rejecting efficiency of the stock markets. Using the S&P 500 stock index, the Wilshire 5000 index, and the NASDAQ index, the Hang Seng index, the Footsie index, and the Nikkei index to proxy world stock market indexes, the empirical results of the cointegration and common feature test support the efficiency of the stock markets in most instances. However, the Footsie index consistently demonstrated a relation with the three US stock market indexes included in the study.

To provide an alternative channel of investigation of comovement in four large European equity markets over a sample period of nearly 30 years.

The paper adopts a two stage methodological approach. In the first instance, the interaction between the equity market and the industrial production in each of the countries is analysed in a hidden Markov framework. This helps extract the information on expansion and contraction of the economies over the three decades. In the second stage, the inference on probability of expansion and contraction of the economies is used to measure the level concordance between these probability series. This helps deduce the level of comovement between the equity markets.

Although the nature of interaction between the equity market and the industrial production in these countries are different, the overall comovement in the equity markets is well established.

The paper introduces a new style in the process of investigation with respect to comovement in different markets and illustrates that with an example of four large European markets.

The purpose of this paper is to study synchronization in stock index cycles across 82 countries and the linkage between macroeconomic and financial integration and stock market synchronization.

The author document the synchronization structure of the world equity index cycles and its evolution over time. The author examine the explanatory power of various economic and financial variables on cycle comovements.

Trade openness, capital openness, and an EU membership contribute to higher stock index cycle synchronization. Additionally, the macroeconomic and financial variables have asymmetric impacts on countries of different development levels.

The author is the first to thoroughly chronicle the turning points, i.e., bear and bull regimes, of world equity indexes and empirically examine determinants of their cyclical comovement across nations.

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.

This chapter examines the increased levels of cross-asset price comovement and its relationship with the recent rounds of “extraordinary intervention” from the US Federal Reserve. The results show that, even after controlling for the preceding financial crisis, asset return volatility, investor risk perceptions, and channels of monetary stimulus, historically unrelated financial asset returns experienced abnormal changes in their conditional correlations. The strength of these cross-asset correlations is directly linked to periods of Federal Reserve interventions yet disappear when the interventions were (in fact or were perceived to be) withdrawn. Despite being studied extensively in the academic literature, no traditional intervention channels can explain the changes in cross-comovement. It is proposed that the Fed’s extraordinary stimulus caused investors to use Fed announcements as a common, low-cost information source on which they used to make common portfolio-allocation decisions. The changes in comovement during the intervention period may have reduced investor welfare for those with longer-horizon allocation strategies, those not prepared for the eventual ending of the stimulus, and for underfunded liability-optimizing portfolio managers (e.g., state pension funds).

Using intraday prices for the S&P 500 and Nikkei Stock Average stock indexes and aggregate trading volume for the New York and Tokyo Stock Exchanges, we show how short-run comovements between national stock market returns vary over time in a way related to the trading volume and liquidity in those markets. We frame our analysis in the context of the heterogeneous-agent models of trading developed by Campbell, Grossman and Wang (1993) and Blume, Easley and O’Hara (1994) and Wang (1994) which predict that trading volume acts as a signal of the information content of a given price move. While we find that there exists significant short-run dependence in returns and volatility between Japan and the U.S., we offer new evidence that these return “spillovers” are sensitive to interactions with trading volume in those markets. The cross-market effects with volume are revealed in both close-to-open and open-to-close returns and often exhibit non-linear patterns that are not predicted by theory.