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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.

In this paper we develop a new semi-parametric model for conditional correlations, which combines parametric univariate Generalized Auto Regressive Conditional Heteroskedasticity specifications for the individual conditional volatilities with nonparametric kernel regression for the conditional correlations. This approach not only avoids the proliferation of parameters as the number of assets becomes large, which typically happens in conventional multivariate conditional volatility models, but also the rigid structure imposed by more parsimonious models, such as the dynamic conditional correlation model. An empirical application to the 30 Dow Jones stocks demonstrates that the model is able to capture interesting asymmetries in correlations and that it is competitive with standard parametric models in terms of constructing minimum variance portfolios and minimum tracking error portfolios.

Asia's economic integration into the global system has many dimensions. It is part of the broader globalization process that has taken place over the past two decades and involves dynamics of convergence, integration, and interactions of both real and financial activities. Section 1 examines some of the recent trends in the real and financial interactions between Asia and the rest of the world and among different markets within Asia. It contains four chapters on this theme, addressing the issues of macroeconomic similarities and differences, interactions among Asian stock markets and between them and the US equity market, as well as spillovers across various types of financial markets in the region in response to shocks.

The BEKK GARCH class of models presents a popular set of tools for applied analysis of dynamic conditional covariances. Within this class the analyst faces a range of model choices that trade off flexibility with parameter parsimony. In the most flexible unrestricted BEKK the parameter dimensionality increases quickly with the number of variables. Covariance targeting decreases model dimensionality but induces a set of nonlinear constraints on the underlying parameter space that are difficult to implement. Recently, the rotated BEKK (RBEKK) has been proposed whereby a targeted BEKK model is applied after the spectral decomposition of the conditional covariance matrix. An easily estimable RBEKK implies a full albeit constrained BEKK for the unrotated returns. However, the degree of the implied restrictiveness is currently unknown. In this paper, we suggest a Bayesian approach to estimation of the BEKK model with targeting based on Constrained Hamiltonian Monte Carlo (CHMC). We take advantage of suitable parallelization of the problem within CHMC utilizing the newly available computing power of multi-core CPUs and Graphical Processing Units (GPUs) that enables us to deal effectively with the inherent nonlinear constraints posed by covariance targeting in relatively high dimensions. Using parallel CHMC we perform a model comparison in terms of predictive ability of the targeted BEKK with the RBEKK in the context of an application concerning a multivariate dynamic volatility analysis of a Dow Jones Industrial returns portfolio. Although the RBEKK does improve over a diagonal BEKK restriction, it is clearly dominated by the full targeted BEKK model.

While changes in stock prices are said to affect exchange rates, exchange rate changes are also said to affect stock prices. The purpose of this paper is threefold. First, the authors review all empirical literature by dividing them into two groups of univariate and multivariate studies. Second, a table which summarizes the main features of each study is provided to help future researchers to have easy access to summary of each study. Finally, a new direction for future research is proposed. This new direction relies upon non-linear ARDL approach and shows how to investigate symmetric vs asymmetric effects of exchange rate changes on stock prices.

The paper reviews existing published work and provides suggestions for future research.

The paper reviews existing published work and provides suggestions for future research. An application reveals that exchange rate changes have asymmetric effect on stock prices.

This is the first review paper on the relation between exchange rates and stock prices.

Given the cryptocurrency market boom in recent years, this study aims to identify the factors influencing cryptocurrency pricing and the major gaps for future research.

A systematic literature review was undertaken. Three databases, Scopus, Web of Science and EBSCOhost, were used for this review. The final analysis comprised 88 articles that met the eligibility criteria.

The influential factors were identified and categorized as supply and demand, technology, economics, market volatility, investors’ attributes and social media. This review provides a comprehensive and consolidated view of cryptocurrency pricing and maps the significant influential factors.

This paper is the first to systematically and comprehensively review the relevant literature on cryptocurrency to identify the factors of pricing fluctuation. This research contributes to cryptocurrency research as well as to consumer behaviors and marketing discipline in broad.

This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.

The purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO₂ emissions during the time span from 1980 to 2020.

The study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in the Indian economy.

The estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO₂ emissions. The authors found that economic growth positively impacts CO₂ emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO₂ emissions. Similarly, RE consumption positively affects CO₂ emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO₂ emissions.

The study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO₂ emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO₂ emissions on further economic growth.

To the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in India, using the STAR model.