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We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

The purpose of this paper is to examine whether macroeconomic variables have a symmetric or asymmetric effect on stock prices (SP) of Karachi Stock Exchange 100 index in the context of Pakistan. It also examines whether the asymmetric impact of macroeconomic variables on SP has been affected by tail events such as the global financial crisis.

This study uses linear and nonlinear autoregressive distributed lag models for the full sample period as well as in pre- and post-crisis periods. The whole sample period covers the data from June 2004 to June 2016 which include 145 observations in total. The pre-crisis period covers data from June 2004 to December 2007 and the post-crisis period covers the data from January 2009 to June 2016 where these periods include 43 and 90 observations, respectively.

The findings suggest that the relationship between macroeconomic variables and SP is asymmetric in the short run whereas this effect is symmetric in the long run when the whole sample period is selected. However, when pre- and post-crisis periods are selected this effect becomes asymmetric in the long run as well; that is, positive and negative shocks in macroeconomic variables do not affect the SP in the same way.

Investors, governments and other stakeholders are advised to consider the asymmetric behavior of macroeconomic variables and SP while making an investment or other decisions. They may consider the financial crisis as well since the asymmetric behavior of the underlying variables change as a result of the financial crisis.

This study extends previous studies by examining the asymmetric effect of macroeconomic variables and also contributes to the existing literature by discussing how this relationship changes as a result of the financial crisis.

This paper attempts to examine the transmission of exchange rate changes into the domestic prices together with other important determinants of later, in case of a developing country, namely, India.

In an open economy Philips curve framework, a symmetric model developed by Pesaran et al. (2001) together with a complete asymmetric model developed by Shin et al. (2014) has been applied to assess the transmission of exchange rate changes into the domestic prices (inflation) of India. In addition, non-linear cumulative dynamic multipliers are used to portray the route between disequilibrium position of short run and new long-run equilibrium of the system. The multipliers highlight the asymmetric adjustment paths and/or duration of disequilibrium and therefore add valuable information to the long and short-run asymmetry.

In symmetric framework, exchange rate pass-through is reported to be incomplete and short-run pass through is found to be lower than the long-run pass through. A contractionary monetary policy stance is observed to decrease inflation in the long-run only and in the short-run, a case for price puzzle is observed, although the coefficient is statistically insignificant. Similarly, the impact of output growth is positive in both the short and long-run and both the coefficients are statically significant. Finally, the oil price inflation is also found to escalate the domestic inflationary pressures in both the short and long run, although the pass-through transmission is lower in the short-run than in the long-run. In case of an asymmetric setting, evidence in favour of directional asymmetry is reported whereby long-run impact of currency appreciation is found to be higher than depreciation. Similarly, a contractionary monetary policy action lowers the inflation, the easy one increases it; however, the impact of both the positive and negative changes in interest rate is found to be symmetric. An increase in GR is found to increase the inflation by a relatively appreciable magnitude than is observed when the fall in GR is reported. The possible reason for this asymmetric response of inflation may be explained in terms of asymmetric behaviour of demand conditions during economic upturns and downturns and downward inflexibility of prices. Finally, the transmission of oil price inflation to domestic inflation is also found to be asymmetric. An increase in oil price inflation leads to an increase in domestic inflation by a higher magnitude. whereas a decrease in it lowers inflation only marginally.

From a policy perspective, it is certainly important for the central banks to monitor the exchange rate changes so as to design the appropriate policy actions to resist any inflationary pressures resulting from the external sector. More importantly, a gauge on the factors that lead to destabilizing exchange rate movements or large currency price fluctuations is highly warranted. The results also highlight the relevance of proper domestic demand management and lowering dependence on oil imports to avoid the unnecessary inflation pressures in the economy.

While some studies have explored the possibilities of asymmetric interactions in the case of India, however, these studies have considered only the partial asymmetric model specifications and have not included a well-established theoretical base to include the other potential determinants of inflation as well. In this regard, the authors applied a complete asymmetric model specification developed by Shin et al. (2014) in an open economy Philips curve framework to assess the transmission of exchange rate changes into the domestic prices (inflation) of India. This paper will enrich the existing literature from a viewpoint of a comprehensive analysis of exchange rate pass-through by taking note of potential asymmetries coupled with other important determinants of inflation.

The purpose of this paper is to provide some insights into the exchange rate exposure of Australian stock returns.

Using a dynamic econometric approach that allows for both asymmetry and time‐varying risk exposures in both the exchange rate variable and the market variable, a large sample of Australian firms were tested over the period of January 2001 and December 2005. The data were analysed using three different classification methods, forming portfolios according to industry sector, size deciles, and censoring deciles.

Although the evidence of exchange rate exposure is limited across the sample of industries, the following were found: a time‐varying asymmetric effect primarily in the utilities sector, time‐varying exposure in the materials and energy sectors, and an asymmetric effect in the technology sector. Further, some time‐varying asymmetric exchange rate exposure was found across most size and censoring deciles and also substantial evidence of a positive asymmetric effect in the market beta across all three classification methods.

This approach varies from previous studies in this area that only allow for asymmetry and time variation in exchange rate exposures. The paper also examines the Australian stock market, a market which has not been extensively tested in this area of empirical research.

This paper aims to examine whether Indonesian cross-border trade responds asymmetrically to exchange rate volatility (ERV).

An exponential generalized autorgressive conditional heteroscedasticity model is applied to estimate the ERV of Indonesia and ten main trade partners using quarterly data from 2006 to 2020. A nonlinear autoregressive distributed lag estimation is applied to estimate the impact of ERV on cross-border trade. Impacts from the global financial crisis (GFC) of 2008 and the COVID-19 pandemic are covered. Dynamic panel data is used for the robustness test.

In the short-run, ERV significantly affects exports to most of the top partners (positively, negatively or both). In the long run, asymmetric effects occur in Indonesia’s exports to five top destinations. The weakening of the Indonesian Rupiah mainly supports exports in the short term. Imports from top partners are also affected by ERV in both the short run and, to a lesser extent, in the long run. Both the GFC and the COVID-19 pandemic reduced trade: for most cases, in the short run. The dynamic panel model suggests that ERV has asymmetric impact on cross-border trade in the long run.

Exchange rate strategies need to avoid a single-side policy approach and, instead, account for exporter and importer differences in risk behaviour and an asymmetric response to ERV in trade. Policymakers need to consider policies that stabilise the currency.

This study provides evidence that cross-border trade can react asymmetrically to the exchange rate uncertainty and that the impacts of real ERV are asymmetric as well. The authors also apply a dynamic panel that signals that ERV matters in the long run for Indonesian trade with top partners.

The purpose of this paper is to construct a frequency-domain framework to study the asymmetric spillover effects of international economic policy uncertainty on China’s stock market industry indexes.

This paper follows the time domain spillover model, asymmetric spillover model and frequency domain spillover model, which not only studies the degree of spillover in time domain but also studies the persistence of spillover effect in frequency domain.

It is found that China’s economic policy uncertainty plays a dominant role in the spillover effect on the stock market, while the global and US economic policy uncertainty is relatively weak. By decomposing realized volatility into quantified asymmetric risks of “good” volatility and “bad” volatility, it is concluded that economic policy uncertainty has a greater impact on stock downside risk than upside risk. For different time periods, the sensitivity of long-term and short-term spillover economic policy impact is different. Among them, asymmetric high-frequency spillover in the stock market is more easily observed, which provides certain reference significance for the stability of the financial market.

The originality aims at extending the traditional research paradigm of “time domain” to the research perspective of “frequency domain.” This study uses the more advanced models to analyze various factors from the static and dynamic levels, with a view to obtain reliable and robust research conclusions.

The primary objective of the paper is to examine the asymmetric Cointegration and asymmetric causality between financial development and poverty alleviation on annual data in Indian context over the period from 1980 to 2019.

First nonlinearity test by Brooks et al. (1999) is applied to ascertain the nonlinear behavior of the variables used. Once the nonlinear behavior of variables is confirmed, asymmetric and nonlinear unit root tests by Kapetanios and Shin (2008) are applied to check for the order of integration of selected variables. Next, nonlinear autoregressive distributed lag model (NARDL) is employed to analyze the asymmetric Cointegration. Finally, Hatemi-j- asymmetric causality tests is applied to work out the direction of asymmetric causality.

The empirical findings document the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The findings of Wald's test also confirm the presence of asymmetric Cointegration. The asymmetric cumulative dynamic multipliers used to examine the behavior of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator. This result exhibits the robustness of the model. Furthermore, the result emanating from recently introduced asymmetric causality test reveals a unidirectional asymmetric causality between negative shocks in financial development and poverty. The findings of the present study necessitate the need for investigating asymmetric and nonlinear effects in finance–poverty nexus, which existent literature has completely neglected, in order to have relevant policy conclusions.

The study used “Per capita consumption expenditure” as a measure for poverty due to lack of continuous time series data on headcount ratio. In future, researchers can extend this study by incorporating headcount ratio as a measure of poverty in their respective works. There is further scope of research on this issue by finding out the impact of formal and informal sources of credit on poverty separately. A panel data study for developing countries over a period of time could further confirm/negate the findings of the present study.

To the best of the authors’ knowledge none of the studies in Indian context has scrutinized asymmetric and nonlinear impact of financial development on poverty. To dredge up asymmetric structures at work, the authors have used the highly celebrated NARDL estimator. To enrich the existent body of knowledge along the lines of asymmetric (nonlinear) linkages, the authors have also used recently introduced asymmetric causality test by Hatemi-j-(2012) to find out the direction asymmetric causality.

Investors aim for returns when investing in stocks, making return volatility a crucial concern. This study compares symmetric and asymmetric GARCH models to forecast volatility in emerging nations like the G4 countries. Accurate volatility forecasting is vital for investors to make well-informed investment decisions, forming the core purpose of this study.

From January 1993 to May 2021, the study spans four periods, focusing on the global economic crisis of 2008, the Russian crisis of 2015 and the COVID-19 pandemic. Standard generalized autoregressive conditional heteroscedasticity (GARCH), exponential GARCH (E-GARCH) and Glosten-Jagannathan-Runkle GARCH models were employed to analyse the data. Robustness was assessed using the Akaike information criterion, Schwarz information criterion and maximum log-likelihood criteria.

The study's findings show that the E-GARCH model is the best model for forecasting volatility in emerging nations. This is because the E-GARCH model is able to capture the asymmetric effects of positive and negative shocks on volatility.

This unique study compares symmetric and asymmetric GARCH models for forecasting volatility in emerging nations, a novel approach not explored in prior research. The insights gained can aid investors in constructing more effective risk-adjusted international portfolios, offering a better understanding of stock market volatility to inform strategic investment decisions.

This study applies asymmetric rather than conventional symmetric analysis to advance theory in occupational psychology. The study applies systematic case-based analyses to model complex relations among conditions (i.e., configurations of high and low scores for variables) in terms of set memberships of managers. The study uses Boolean algebra to identify configurations (i.e., recipes) reflecting complex conditions sufficient for the occurrence of outcomes of interest (e.g., high versus low financial job stress, job strain, and job satisfaction). The study applies complexity theory tenets to offer a nuanced perspective concerning the occurrence of contrarian cases – for example, in identifying different cases (e.g., managers) with high membership scores in a variable (e.g., core self-evaluation) who have low job satisfaction scores and when different cases with low membership scores in the same variable have high job satisfaction. In a large-scale empirical study of managers (n = 928) in four (contextual) segments of the farm industry in New Zealand, this study tests the fit and predictive validities of set membership configurations for simple and complex antecedent conditions that indicate high/low core self-evaluations, job stress, and high/low job satisfaction. The findings support the conclusion that complexity theory in combination with configural analysis offers useful insights for explaining nuances in the causes and outcomes to high stress as well as low stress among farm managers. Some findings support and some are contrary to symmetric relationship findings (i.e., highly significant correlations that support main effect hypotheses).

This paper investigates the (a)symmetric effects of financial development in the presence of economic growth, energy consumption, urbanization and foreign direct investment on environmental quality of South Africa between 1980 and 2017.

A robust measure of financial development is generated using banking institutions and non-banking institutions market-based financial development indicators, while environmental quality is measured using carbon footprint, non-carbon footprint and ecological footprint. The objectives of the study are captured using linear and non-linear autoregressive distributed lag.

The result from the symmetric analysis suggests that financial development stimulates carbon footprint and ecological footprint in the short run; however, financial development abates non-carbon footprint. In the long run, financial development has a significant negative effect on carbon footprint and ecological footprint. However, the asymmetric analysis established strong asymmetric effect in the short run, while no asymmetric effect is found in the long run. The short run asymmetric analysis reveals that positive shock in financial development increases carbon footprint and ecological footprint; however, positive changes in financial development reduce non-carbon footprint. Negative shocks in financial development, on the other hand, have a positive impact carbon footprint, non-carbon footprint and ecological footprint.

The study's outcome implies that the concept of “more finance, more growth” could also be applied to “more finance, better environment” in South Africa. The study offers vital policy suggestions for the realization of sustainable development in South Africa.

This empiric adds to the body of knowledge on the influence of financial development on various components of environmental quality (carbon footprint, non-carbon footprint and ecological footprint) in South Africa.