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The study's purpose is to investigate the price volatility of four dairy commodities (skim milk powder [SMP], whole milk powder [WMP], butter and cheddar cheese) in the three most significant regional markets (EU, Oceania and US) in the international dairy market.

The study uses a panel-Generalized Autoregressive Conditional Heteroskedastic (panel-GARCH) modeling technique and data from January 12, 2001, to April 28, 2017.

Conditional volatility was higher during subperiods 2007–2010 and 2014–2016 when conditional cross-correlations between prices had the lowest values. In some cases, they were negative (i.e. between the EU and the USA and between Oceania and the USA for both butter and cheese). Interdependence across the three dairy markets, especially for SMP and WMP markets and for the butter market between EU and Oceania is also strongly evidenced. Interdependence is responsible for the spillover of price shocks across the three regions.

The data set used should be extended to cover the COVID-19 pandemic period.

This is the first study to use panel-GARCH to examine international dairy prices and volatility linkages, where previous studies mainly used multivariate GARCH models. Panel-GARCH allows a high-dimensional data series (i.e. 12 dairy prices) and generates potential efficiency gains in estimating conditional variances and covariances by incorporating information about heterogeneity across markets and considering their interdependence.

The purpose of this paper is to explore the determinants of the cross‐market transmission mechanism for terrorist shocks, focusing on two major terrorist events and 68 national stock markets.

The paper generates daily abnormal returns from a three‐factor world asset‐pricing model. Abnormal returns are then regressed on proxies of three transmission mechanisms; a world integration channel, a bilateral integration channel, and a liquidity channel.

The findings indicate that terrorism shocks are diffused cross‐nationally in a non‐uniform manner. This paper finds empirical support for all three channels when considered separately. The bilateral integration channel contains the highest explanatory power since it is found that a third country's trade linkages with the “ground‐zero” country explain about 24 percent of the stock market reaction. A country's share in the world trade, a proxy for the world integration channel, is able to explain about 12 percent of abnormal‐return variation, while the liquidity channel exhibits the lowest predictive power, with the value of stock trading explaining about 6 percent. A hybrid model, where proxies for all channels are included, shows that only the bilateral trade linkages with the “ground‐zero” country are significant determinants of the stock market reaction.

Provides evidence useful for portfolio management and authorities' assessment of terrorist shocks' impact on capital markets.

It is the first study that investigates the determinants of cross‐market transmission of terrorist shocks.

This study aims to elucidate the volatility spillovers among commodities, equities and socially responsible investments, underpinning their dynamic correlations during the economic instability wrought by the COVID-19 pandemic and associated financial crises.

This research quantitatively analyzes volatility transmission across various financial assets from January 2005 to October 2020 by employing the Diebold and Yilmaz (2012) spillover index. The methodology incorporates a temporal examination to capture the evolution of volatility dependencies pre and post the emergence of COVID-19.

The findings indicate substantial volatility spillovers among the assets in question, aligning with the current financialisation of commodity markets and a rise in financial market integration. These spillovers also show variation over time. Notably, the interconnectedness among the assets intensifies during periods of stress. For instance, the total spillover index significantly surpassed 80% toward the end of January 2020, following the onset of the COVID-19 crisis. Furthermore, the results imply that financial markets appear to be segmented.

The findings afford investors a more comprehensive insight into both the character and scale of the interdependencies across a broad array of financial markets. Indeed, grasping the extent to which financial markets are segmented or integrated during times of stress and stability is crucial for investors. Such understanding is key to more accurately evaluating risks, diversifying investment portfolios and devising more efficient hedging strategies.

This study contributes to financial literature by offering a comprehensive investigation into the spillover effects across a diverse set of asset classes during an unprecedented global health crisis, filling a gap in existing research on market behavior against the backdrop of a pandemic-induced financial crisis.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

In this study, the authors analyze the impact of geopolitics risk on Sukuk, Islamic and composite stocks, oil and gold markets and portfolio diversification implications during the COVID-19 pandemic and Russia–Ukraine conflict period.

The study used a mix of wavelet-based approaches, including continuous wavelet transformation and discrete wavelet transformation. The analysis used data from the Geopolitical Risk index (GP{R), Dow Jones Sukuk index (SUKUK), Dow Jones Islamic index (DJII), Dow Jones composite index (DJCI), one of the top crude oil benchmarks which is based on the Europe (BRENT) (oil fields in the North Sea between the Shetland Island and Norway), and Global Gold Price Index (gold) from May 31, 2012, to June 13, 2022.

The results of the study indicate that during the COVID-19 and Russia–Ukraine conflict period geopolitical risk (GPR) was in the leading position, where BRENT confirmed the lagging relationship. On the other hand, during the COVID-19 pandemic period, SUKUK, DJII and DJCI are in the leading position, where GPR confirms the lagging position.

The present study is unique in three respects. First, the authors revisit the influence of GPR on global asset markets such as Islamic stocks, Islamic bonds, conventional stocks, oil and gold. Second, the authors use the wavelet power spectrum and coherence analysis to determine the level of reliance based on time and frequency features. Third, the authors conduct an empirical study that includes recent endogenous shocks generated by health crises such as the COVID-19 epidemic, as well as shocks caused by the geopolitical danger of a war between Russia and Ukraine.

1. We analyze the impact of geopolitics risk on Sukuk, Islamic and composite stocks, oil and gold markets and portfolio diversification implications during the COVID-19 pandemic and Russia–Ukraine conflict period.

2. The results of the wavelet-based approach show that Dow Jones composite and Islamic indexes have observed the highest mean return during the study period.

3. GPR and BRENT are estimated to have the highest amount of risk throughout the observation period.

4. Dow Jones Sukuk, Islamic and composite stock show similar trend of volatility during the COVID-19 pandemic period and comparatively gold observes lower variance during the COVID-19 pandemic and Russia–Ukraine conflict.

We analyze the impact of geopolitics risk on Sukuk, Islamic and composite stocks, oil and gold markets and portfolio diversification implications during the COVID-19 pandemic and Russia–Ukraine conflict period.

The results of the wavelet-based approach show that Dow Jones composite and Islamic indexes have observed the highest mean return during the study period.

GPR and BRENT are estimated to have the highest amount of risk throughout the observation period.

Dow Jones Sukuk, Islamic and composite stock show similar trend of volatility during the COVID-19 pandemic period and comparatively gold observes lower variance during the COVID-19 pandemic and Russia–Ukraine conflict.

To study the key determinants of chronically high inflation in Iran.

Relying on annual data from 1978 to 2019, the authors employ an Auto-Regressive Distributed Lag (ARDL) model and Error Correction Model (ECM) to study the inflationary effects of monetary and fiscal policies as well as exchange rate swings and sanctions intensification.

The authors find that increase in money supply, depreciation of nominal exchange rate, increase in fiscal deficit and intensification of sanctions are among the key drivers of inflation in Iran. Their impact is profound in the long run, but in the short run only money supply and currency depreciation are significant. Also, when exploring the inflation in different components of Consumer Price Index (CPI), we find robust long- and short-run effects from money supply and exchange rate, while the effects of fiscal deficit and sanctions vary across different components.

The authors contribute to the literature by setting apart the long-vs short-run effects of key variables on inflation in Iran. The authors also employ improved measures of fiscal deficit and sanctions that are shown to be of significance in the long run. Lastly, the authors go beyond the aggregate index and examine the variations in different CPI components.

The purpose of this paper is to analyse the long-run relationship between geopolitical risk and exchange rates in four ASEAN countries.

We augment theoretical nominal exchange rate models available in the literature with the geopolitical risk index developed by Caldara and Iacoviello (2019), and then estimate these models using the ARDL approach to Cointegration.

Our analysis uncovers evidence of Cointegration in the exchange rate models when the MYR-USD, IDR-USD, THB-USD and PHP-USD exchange rates are used as dependent variable. Next, geopolitical risk is a significant long-run driver for these exchange rates. Third, in all countries higher geopolitical risk leads to a depreciation of domestic currency.

There are implications for entrepreneurs, central banks, portfolio managers and arbitrageurs who actively trade in financial markets. Financial market players can benefit from a better understanding of how geopolitical events affect the portfolio of financial assets across various countries, while entrepreneurs can work out hedging strategies.

This is a contribution to the study of interlinkages between political risk and foreign exchange markets. It is the first study to adopt the geopolitical risk index of Caldara and Iacoviello (2019) to the study the foreign exchange markets of ASEAN countries.