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The aim of this paper is to examine the effect of information disclosure by unlisted bond issuers on the stock price informativeness of listed firms in the same industry.

This paper takes advantage of information disclosure during the bond issuance and examines the spillover effect of unlisted bond issuers' information disclosure on listed firms in the stock market. The sample is composed of A-share firms listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2018. All the data are obtained from the China Stock Market and Accounting Research and WIND databases. The impact of bond market information disclosure on price informativeness of listed firms in the same industry is identified through multivariate regression analyses.

Empirical results show that price informativeness of listed firms has a significantly positive association with the information disclosure of same-industry unlisted bond issuers. Further analyses show that the above finding is more significant when information disclosure of bond issuers is a more important channel for acquiring industry information (i.e. when industry is more concentrated, when economic uncertainty is high, and when industry information is less transparent) and understanding the industry competitive landscape (i.e. when bond issuers are relatively large, when bond issuers and listed firms have more direct product competition, when bond issuance firms are large-scale state-owned business groups), and when there are more cross-market information intermediaries (i.e. more cross-market institutional investors and more sell-side analysts). This paper indicates that information disclosure of bond issuers has a positive spillover effect on the stock market.

The novelty of the research is that the authors examine industry information spillover from unlisted firms to listed firms leveraging on unlisted firms' information disclosure in bond markets.

This paper aims to examine the dynamic spillover effects and network connectedness between the oil prices and the Islamic and conventional financial markets in the Gulf Cooperation Council countries. The focus is on network connectedness during the 2008–2009 global financial crisis, the 2014–2016 oil crisis and the COVID-19 pandemic. The authors use daily data covering the period from January 1, 2007 to April 14, 2022.

This study applies a spillover analysis and connectedness network to investigate the risk contagion among the Islamic and conventional stock–bond markets. The authors rely on Diebold and Yilmaz’s (2012, 2014) methodology to construct network-associated measures.

The results suggest that overall connectedness among financial market uncertainties increased during the global financial crisis, the oil price collapse of 2014–2016 and the COVID-19 crisis. In addition, the authors show that the contribution of oil shocks to the financial system is limited, as the oil market was a net receiver during the 2014 oil shock and the COVID-19 crisis. On the other hand, the Islamic and conventional stock markets are extensive sources of network effects on the oil market and Islamic and conventional bond markets. Furthermore, the authors found that the Sukuk market was significantly affected by the COVID-19 pandemic, whereas the conventional and Islamic stock markets were the highest transmitters of shocks during the COVID-19 pandemic outbreak. Moreover, oil revealed a weak connectedness with the Islamic and conventional stock markets during the COVID-19 health crisis, implying that it helps provide diversification benefits for international portfolio investors.

This study contributes to this field by improving the understanding of the effect of fluctuations in oil prices on the dynamics of the volatility connection between oil and Islamic and conventional financial markets during times of stress through a network connectedness framework. The main results of this study highlight the role of oil in portfolio allocation and risk minimization when investing in Islamic and conventional assets.

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 purpose of this paper is to examine information and volatility linkages among real estate, equity, bond and money markets in Australia.

A novel rational expectations framework of financial contagion (Kodres and Pritsker, 2002), along with a combination of robust statistical methods including simple and dynamic correlations and generalized impulse response (Fereidouni et al., 2014) have been employed using data covering three dynamic pre-pandemic economic cycles, namely, global financial crisis (GFC) period, pre-pandemic housing boom and pre-pandemic housing downturn from 2008 (February) to 2019 (December).

Results reveal information linkages across real estate, equity, bond and money markets through correlations in return and volatilities of these series. Finding indicates that the three financial markets (equity, bond and money markets) are interdependent and integrated through information and volatility linkages during the GFC period and pre-pandemic housing downturn period. Financial markets have stronger associations with real estate market during pre-pandemic housing boom. The findings contribute to the general notion that the performances of three financial markets are closely related to the “boom” phase of the real estate cycle.

This research provides an extension of existing literature regarding the information and volatility contagion of the expanded set of core investment markets in Australia. The findings could assist household buyers and investors in designing strategic investment portfolios/hedging strategies and minimizing asset specific risks through diversification over short-term and long-term. In addition, results could support the maintenance, growth and development of a combination of competitive balanced investment markets including real estate, equity, bond and money markets in post-pandemic economy.

This work investigates the volatility spillovers across stock markets and the nature of such spillovers through different periods of crises and tranquility.

Using daily stock return volatility data from June 2003 to June 2021, the generalized forecast error variance decomposition method (based on Diebold and Yilmaz, 2012 approach) is employed to measure the degree of volatility spillovers/connectedness among stock markets of 24 Asia–Pacific and 12 European Union (EU) economies.

The empirical results from static analysis suggested that about 28.1% (63.7%) of forecast error variance in return volatility for Asia–Pacific (EU) markets is due to spillovers. The evidence from dynamic analysis suggested that during mid of the global financial crisis, European debt crisis (EDC) and Covid-19, the gross volatility spillovers for Asia–Pacific (EU) was around 67% (80%), 65% (80%) and 73% (67%), respectively. The degree of net volatility transmission from Singapore (Denmark) to other Asia–Pacific (EU) markets was found to be highest.

The findings have crucial implications for the investors and portfolio managers in assessment of risk and optimum allocation of assets and investment decisions.

This study adds to the literature on risk management by systematically examining the impact of global financial crises, EDC and Covid-19 on the market interactions by capturing the magnitude, duration and pattern of the shock-specific market volatilities for a large sample of Asian and European markets using recent and large data set.

The purpose of this paper is to investigate the linkages among equity exchange traded funds (ETF) returns and transmission of volatilities of the USA, Europe and key emerging countries’ stock markets. Standard & Poor’s 500 (spy) and iShares Europe are used to represent the USA and European stock markets, the emerging market part of the data set consists of daily returns of equity ETF representing broad equity market indices of the BRIC countries (Brazil, Russia, India and China); the mist countries (Mexico, Indonesia, South Korea and Turkey) and South Africa and covers the period of February 3, 2012-February 28, 2014.

The paper utilizes multi-variate auto-regressive moving-averages (MARMA) methodology to study equity market returns and spillovers. Second, generalized auto-regressive conditional heteroskadasticity (GARCH) modeling is employed to model volatility persistence and transmissions.

The findings include the existence of significant co-movement of returns among all country ETFs; however, despite increasing interdependencies among the global stock markets there are still very good opportunities for diversification. For example, USA and Europe based investors may do well to ignore opportunities in each other’s markets but can realize diversification benefits by investing in ETFs representing China, South Africa and Turkey. As far as volatilities are concerned, the findings indicate that no ETF volatility is transmitted from the sample countries to USA, Brazil, China and South African stock markets. Also, US market volatility is transmitted to India, Russia, Mexico and Turkey while European volatility spills over to Mexico and South Korea. The presence of spillovers among stock markets’ return series and persistence of volatilities are useful to investors interested in diversifying their portfolios and to traders/fund managers who are interested in maximizing returns.

The implications include: first, investors should not only rely on current domestic news to guide their investment decisions, but also take into consideration international news for there are substantial spillovers. Second, given that volatilities can proxy for risk, there are lessons for both individual and institutional investors in terms of further examining pricing securities, hedging and other trading strategies as well as framing regulatory policies. Third, investors should be able to ride the financial cycle by following closely monetary policies of the FED and European Central Bank and resulting credit expansion or contraction since research indicates (and as corroborated in this study) equity prices are linked to VIX which is also correlated with capital flows and credit expansion and interest rates. Limitations include: first, the investigation could be expanded to include individual countries in Europe instead of using one Europe-wide ETF. As ETFs for other emerging markets become available it is also possible to include additional countries. Second, ETFs may not be the best vehicles for diversification.

Methodology (MARMA and GARCH) is widely used for analyzing financial data. The use of BRIC and MIST countries and the interaction among them may be novel. Spillovers among emerging financial markets is a fairly new area. Typically, the authors see studies of spillovers from the developed countries to the developing ones. The data period is important since it covers both credit expansion and contraction (or the start of it) by the FED and is current.

This paper aims to investigate the spillover effects of jump and crash events among Chinese nonfinancial firms.

This sample consists of more than 1.5 million weekly observations of over 3,000 Chinese listed firms over the period 1991–2015. The authors utilize univariate tests to compare the post-event performance of matched peer and non-peer control firms and cross-sectional regressions of their abnormal returns/cumulative abnormal returns (ARs/CARs) and returns on assets (ROAs).

The authors find that extreme risk-adjusted abnormal stock returns (stock price crashes and jumps) generate statistically significant ARs/CARs in the same directions in industry, size, leverage, and geographical location matched peer firms in Chinese stock market. Further tests reveal that peer firms' response to the crash event is pronounced more in the group of firms about which the information asymmetry is high between investors and firms.

Portfolio investors can adjust their portfolios accordingly by selling stocks of the matching rival firms during a crash period. Policymakers may develop policies so as to protect the interests of small investors in the events of crashes in the markets. They can reduce the information asymmetry between the firms and the investors by making information about the firms more transparent, so as to reduce the contagion in case of crash event.

This study has important implications for portfolio investment managers and policymakers.

To the best of authors' knowledge, this is the first study that combines the jump and crash events and attempts to assess their spillover effects on other firms in Chinese stock market.

The study presents and evaluates a proposition that there is market information bundled with the mobile money (m-money) system. Also, that such information is disseminated to farmers in the process of their normal financial transactions and business interactions. This market information is important to mitigate the price uncertainty of farm products.

The empirical analysis is conducted with a two-stage econometric procedure. First, a probit model is used to estimate the likelihood of m-money take-up by farm entrepreneurs. Second, the ordinary least squares model is used to regress the farming price uncertainty index on the m-money take-up, which is quantified with a set of predicted values from the probit model in the first stage. The data used in econometric estimation come from Kenya's FinAccess Household Survey published in 2016.

The results of this paper show a negative effect of m-money service take-up on the price uncertainty index. A one unit increase in the m-money system is associated with a 12% reduction in the price uncertainty index. The authors interpret this as saying that access to the m-money system by farm business has a beneficial spillover effect on product risk mitigation, ceteris paribus.

The implication of this research is that policy initiatives which support farm entrepreneurs to access the m-money system should be encouraged not only for their financial inclusion advantage but also for their positive externality on product risk amelioration for rural farm businesses.

The paper introduces an idea that the m-money system is bundled with relevant information for mitigating price risk to the benefit of rural farm businesses.