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The purpose of this paper is to explore the dynamic influence of WTI crude oil returns on the stock returns of China’s traditional energy sectors, including oil and gas exploitation, coal mining and processing, petroleum processing and coking, electricity, heat production and supply and mining services.

Hong’s information spill-over test and the DP Granger causality test are applied to investigate the relationship between the two markets. Moreover, a rolling window is introduced into the above two tests to capture time-varying characteristics of the influence of WTI crude oil returns.

The empirical results indicate that, first, there exists significant bidirectional linear causality between WTI crude oil returns and China’s traditional energy sectoral stock returns, but the nonlinear causality appears weaker. Second, the influence of WTI crude oil returns on traditional energy sectoral stock returns has time-varying characteristics and industry heterogeneity both in the linear and nonlinear cases. Finally, the decline of WTI crude oil prices may strengthen its linear influence on the stock returns of traditional energy sectors, while the excessive rise of market values in traditional energy sectors may weaken the linear and nonlinear influence of WTI on them.

The general nexus between international crude oil market and China’s traditional energy stock market is explored both in the linear and nonlinear perspectives. In particular, the dynamic linear and nonlinear influence of WTI crude oil returns on China’s traditional energy sectoral stock returns and its industry heterogeneity are analysed in detail.

This paper aims to empirically examine the effect of Coronavirus disease 2019 (COVID-19) pandemic on cryptocurrency market returns with particular attention to top five cryptocurrencies and COVID-19 confirmed and death cases.

The study applies the linear Toda and Yamamoto and nonlinear Diks and Panchenko Granger causality test to know the causal relationship of cryptocurrencies with COVID-19 pandemic. The study also uses the Narayan and Popp endogenous two structural break tests to capture the break period of the sample.

The findings of the study confirm the existence of unidirectional causal relation from COVID-19 confirmed and death cases to cryptocurrency price returns. While examining the break periods, the post-break period result indicates the presence of unidirectional linear causality from COVID-19 confirmed cases to Bitcoin and Ethereum price returns. This shows that prior knowledge of COVID-19 pandemic growth helps to predict the return of cryptocurrencies.

The study suggests the investors or crypto lovers to observe the growth of COVID-19 situations during their investment in cryptocurrency markets.

Departing from the expansionary austerity literature, this study aims at examining how fiscal consolidation affects the economic growth in Tunisia using annual data over the period 1970–2018.

To revisit the fiscal consolidation-economic growth nexus, the ambiguous empirical findings in previous literature make useful the adoption of alternative econometric techniques. The authors use an extended nonlinear autoregressive distributed lag (ARDL) cointegration approach developed by Shin et al. (2014) and the Diks and Panchenko's (2006) nonlinear Granger causality test. Furthermore, a traditional approach based on changes in cyclically-adjusted primary balance was applied to define the fiscal consolidation episodes in Tunisia.

The empirical evidence reveal that fiscal adjustment in Tunisia may hurt the economy, both in the short- and long-run, through its contractionary effect on economic growth. Another important finding concerns the unidirectional nonlinear Granger causality running from fiscal consolidation to economic growth.

Fiscal adjustment in Tunisia is found to play a prominent role in reducing public debt; but at the same time, it may be costly and not beneficial to the economy. This view corroborates with the fact that fiscal consolidation is more likely to end successfully only under specific conditions. This calls for a deeper reflection upon new insights regarding the design of fiscal adjustment in Tunisia. To reach this end, it is suggested to combine the defensive consolidation strategy with offensive components such as investment, infrastructure, education and health.

The existing economic analysis on fiscal policy-growth nexus in Tunisia has often identified fiscal consolidation through the use of the actual fiscal balance. With the goal of more accurate estimation, this study bridges the gap by using the cyclically-adjusted primary balance (CAPB) as a much suitable indicator to investigate the non-Keynesian effect of fiscal consolidation in Tunisia. This indicator eliminates the influence of cyclical fluctuations and many other fixed expenditures such as the interest paid on the public debt.

The purpose of this paper is to analyse the adaptive market efficiency in the price–volume (P–V) relationship of the stocks listed in the Mexican Stock Exchange. The period under study goes from 1982 to 2015. In order to detect causality and, thus, determine adaptive efficiency in the market, one linear and two non-linear tests are applied. There are few papers in the literature that study the P–V relationship in Latin American markets; as such, this paper may be of interest and importance to financial academics and practitioners alike.

The Diks and Panchenko (DP) non-parametric Granger causality and the Brooks and Hinich (BH) cross-bicorrelation tests are applied.

Derived from the DP test, the findings show that there exists bi-directional non-linear Granger causality in 25.71 per cent of the firms studied, compared to 8 per cent when applying the linear Granger causality test. Therefore, there is evidence of weak-form efficiency in the market. From the BH test, evidence is shown of the adaptive market efficiency, since 71.42 per cent of firms exhibited some form of non-linear dependence in certain periods of time. With these results, the information process should be better studied for a greater comprehension of regulatory policies in the market and better decision-making tools for the investors.

This paper complements studies on the P–V relationship and efficiency in a Latin American market.

Este documento analiza la eficiencia adaptativa del mercado para la relación precio-volumen de las empresas que cotizan en la Bolsa Mexicana de Valores. El periodo bajo estudio es de 1982 a 2015. Para detectar causalidad y determinar la eficiencia adaptativa del mercado, se aplicó una prueba lineal y dos no-lineales. Existen pocos documentos en la literatura que estudien la relación precio-volumen en mercados latinoamericanos. Como tal, este documento puede ser de interés e importancia tanto para académicos como para profesionales de las finanzas.

Se aplicó la prueba de causalidad no-paramétrica de Diks y Panchenko y la prueba de bicorrelación cruzada de Brooks y Hinich.

Derivado de la prueba DP, los hallazgos muestran que existe causalidad no-lineal bidireccional en 25.71% de las empresas bajo estudio, comparado a un 8% cuando se aplica la prueba de causalidad lineal de Granger. Por lo tanto, existe evidencia de eficiencia en forma débil del mercado. De la pruba BH, se muestra evidencia de eficiencia adaptativa del mercado, dado que el 71.42% de las empresas exhibieron alguna forma de dependencia no-lineal en ciertos periodos de tiempo. Con estos resultados, el proceso de información debe ser mejor estudiado para una mayor comprensión de las políticas regulatorias del mercado y mejores herramientas para la toma de decisiones por los inversionistas.

Este documento complementa los estudios sobre la relación precio-volumen y la eficiencia en un mercado latinoamericano.

The objective of this paper is to investigate the direction of the causal relationship between dividend policy (DP) and earnings management (EM).

This research utilizes the panel data analysis to investigate the causal relationship between EM and DP. It provides empirical insights based on a sample of 280 French nonfinancial companies listed on the CAC All-Tradable index during the period of 2008–2015. The study initiates with a Granger causality examination on the unbalanced panel data and employs a dynamic panel approach with the generalized method of moments (GMM). It further estimates the empirical models simultaneously using the three-stage least squares (3SLS) method and the iterative triple least squares (iterative 3SLS) method.

The estimation of our various empirical models confirms the presence of a bidirectional causal relationship between DP and EM.

Our study highlights the prevalence of EM in the French context, particularly within DP. It underscores the need for regulatory bodies, the Ministry of Finance, external auditors and stock exchange organizers to prioritize governance mechanisms for improving the quality of financial information disclosed by companies.

This research is, to the best of our knowledge, the first is to extensively investigate the reciprocal causal relationship between DP and EM in France. Previous studies have not placed a significant emphasis on exploring this bidirectional link between these two variables.

Contrary to the restrictive bivariate results of Saunders (1995), our findings from open‐economy multivariate models accord with the conventional IS/LM apparatus and decisively support the use of fiscal policy as a key macrostablization tool in the U.S. economy. We provide theoretical explanations for our results and produce empirical evidence for their robustness.

Since financial sector plays a critical economic role in Hong Kong, the current research aims to comprehensively analyze the association between financial development and economic growth in the country to draw correct conclusions about the impact that financial sector's development has on the growth of the economy. This requires both using of more comprehensive data that includes all or nearly all elements of the country's financial sector and utilizing advanced econometrics techniques to provide more reliable evidence based on the findings. In the study, both issues have been addressed more academically to aid the relevant authorities better.

This study empirically examines the financial development-economic growth nexus in Hong Kong employing data covering 1980–2019. The quantile-on-quantile (QQ) approach of Sim and Zhou (2015) is utilized to investigate certain subtle aspects of the association linking financial development and economic growth. In addition, the authors benefit from applying the nonlinear Granger causality test of Diks and Panchenko (2006) to assess the variables' nexus in a nonlinear manner.

In contrast to the evidence of a unidirectional linkage documented in many related studies, the empirical findings suggest that a bi-directional relationship exists between financial development and economic growth for Hong Kong. This is a helpful input for the relevant policymakers and implies that they can set appropriate policies and regulations to balance financial development and economic growth in this country.

The originality of this study can be divided into two parts. Methodologically, unlike past studies that utilized mostly linear and parametric methods, the paper contributes to the literature by applying the more robust nonparametric and nonlinear methodologies. Theoretically, most researchers have used various financial development indicators, which led to very different conclusions. Therefore, this study attempts to resolve this deficiency in the literature by using a more comprehensive index for financial development.

The purpose of this paper is to examine the relationship between stock prices and exchange rates in 12 OECD countries.

The authors examine the nexus of stock prices and exchange rates for 12 OECD countries by using the vector error correction model, the bounds testing methodology and linear and non‐linear Granger causality methods.

The empirical results substantiate that a long‐run level equilibrium relationship among the exchange rates and stock prices exists in only seven out of twelve countries. The results of the linear causality tests indicate that significant short‐run and long‐run causal relationships exist between the two financial markets. The results of the tests for non‐linear Granger causality suggest that unidirectional and bidirectional non‐linear causal relationships exist between stock prices and exchange rates among these OECD countries.

The findings from this paper suggest the causal relationships between stock prices and exchange rates are not only linear, but also non‐linear.

With growing interdependence between financial markets, the goal of this paper is to examine the dynamic interdependence between corporate equity and public real estate markets for the USA and a select group of seven European developed economies under a cross-country framework in crisis and boom market conditions. Dynamic interdependence is related to four measures of market linkages of “correlation, spillover, connectedness and causality”.

This study adopts a four-step investigation. The authors first estimate “time-varying variance–covariance spillovers and implied correlations” modeled with the bivariate BEKK-MGARCH methods. Second, the methods of Diebold and Yilmaz (2012, 2014) measure the conditional volatility spillover-connectedness effects across the corporate equity and public real estate markets based on a decomposition of the forecast error variance. Third, the authors implement nonlinear bivariate and multivariate causality tests to understand the lead-lag dynamics of the two asset markets' returns, volatilities and net directional volatility connectedness across different sample periods. Finally, the authors conclude the study by providing a portfolio hedging analysis.

The authors find that corporate equity and public real estate are moderately interdependent to the extent that their diversification benefits increases in the longer term. Moreover, the authors find increased corporate equity-public real estate causal dependence of the market groups of the European and international portfolios during the GFC and INTERCRISIS periods. The nonlinear causality test findings indicate that the joint information of asset markets can be a useful source of prediction for future innovation of market risks. Additionally, policy makers may also be able to employ conditional volatility and volatility connectedness as two other measures to manage market stability in the cross-asset market dependence during highly volatile periods.

One major take away from this academic research is since international portfolio investors are not only concerned the long-term price relationship but also the correlation structure and volatility spillover-connectedness, the conditional BEKK modeling, generalized risk connectedness analysis and nonlinear causal dependence explorations from this multi-country study can shed fresh light on the nature of market interdependence and magnitude of volatility connectedness effects in a multi-portfolio framework.

The hedging performance analysis for portfolio diversification and risk management indicates that industrial stocks (“pure” equities) are valuable assets that can improve the hedging performance of a well-diversified corporate equity-public real estate portfolio during crisis periods. For policymakers, the findings provide important information about the nature of causal links and predictability during the crisis and asset-market boom periods. They can then equip with this information to manage and coordinate market stability in cross corporate equity-real estate relationships effectively.

Although traditional research has in general reported at least a moderate degree of relationship between the two asset markets, investors' knowledge of stock-public real estate market linkage is somewhat inadequate and confine mostly to broad stocks (i.e. stocks that are exposed to public real estate influence) in a single-country context. In this paper, the authors examine the interdependence dynamics in a multi-country (multi-portfolio) context. A clear understanding their changing market relationships in a multi-country context is of crucial importance for portfolio investors, financial institutions and policy makers. Moreover, since the authors use an orthogonal stock market index, the authors allow global investors to understand the potential diversification benefits from stock markets that are beyond the public real estate market under different market conditions.

In this paper the techniques of zero-non-zero (ZNZ) patterned vector autoregressive modelling are utilized to examine two issues associated with the European single currency – the euro. First, “Granger causality” is employed to examine the causal linkages between the euro exchange rate, the euro area money supply and the gross domestic product (GDP) growth in the euro area. Second, we examine the hypothesis that the euro has become a major influence on international stock markets by testing for the causal relationships between movements in the euro exchange rate, the U.K. pound exchange rate and the London stock market index.