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This paper aims to study the co-movement dynamics of Islamic equity returns to explain international portfolio diversification opportunities for investors having a heterogeneous stock holding period in light of Brexit.

The authors use the following three recent methodologies: the multivariate generalised autoregressive conditional heteroskedastic-dynamic conditional correlations, continuous wavelet transforms and maximum overlap discrete wavelet transform. Dow Jones Islamic country-based indexes are used from 2 September 2013 to 31 December 2019.

There is a high correlation between the United Kingdom (UK) Islamic stock market return with the Canadian, USA, Malaysian and Indian implying lesser diversification benefits for the investors. However, the results tend to indicate that UK Islamic stock market investors who have allocated their investment in Sri Lanka, Kuwait, Japan and Turkey have enjoyed diversification benefits. Besides, there is a declining correlation between UK Islamic stock markets and other selected markets aftermath of Brexit. Turkey seems the most volatile stock over the period, appealing to risk-lover investors to gain from price changes. When the shock occurs in the financial sector, the volatility is mean-reverting faster than other markets in Sri Lanka. On the other hand, Malaysia appears to have the least volatility implying a stable financial sector.

The results tend to shed light on effective portfolio diversification benefits in light of the recent shock (Brexit) between the UK Islamic stock index and other selected indexes that vary from country to country depending on investment horizons. This critically confirms the significance of heterogeneity in investment horizons and provides significant inferences for portfolio diversification strategies.

To the best of the authors’ knowledge, this study is the first study investigating the Brexit effect on Islamic stocks, guiding Shariah sensitive investors in their diversification strategies, providing information to investors to consider the implications of this incident on Islamic stocks for future shocks.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

The paper seeks to investigate conditional correlations and conditional volatility spillovers across international stock markets and industrial sectors from the perspective of the UK investor.

Utilizing the DCC model, the paper extracts the time‐varying conditional correlations between the UK, US and European stock markets and industrial sectors. It also uses the multivariate generalized autoregressive conditional heteroscedasticity (MVGARCH) to assess the transmission of volatility from the US and European stock markets to the UK.

The findings suggest that the UK equity market is more integrated with Europe, in terms of both aggregate stock markets and sectors. Correlations are higher during bear markets and tend to fall during periods of recovery. The sectoral analysis also provides interesting insights into the dynamics of volatility transmission across sectors.

The results suggest that the search for a better understanding of the dynamics of correlations between markets and sectors must continue.

The investigation raises interesting questions for investors and regulators, as well as theoretical finance. For example, the finding that correlations increase in bear markets suggests that hedging strategies need to be revisited. The existence of sectoral idiosyncratic volatility offers further evidence that arbitrage may at times become more risky and thus limited.

The findings from analysing both market‐wide and sectoral integration raises the overarching question of whether studies of market integration and portfolio diversification, as well as the authorities overseeing financial stability, should be focusing on sectoral rather than market‐wide analysis.

The study aims to investigate the presence of herding behavior in the stock market of UK with a special emphasis on news sentiment regarding the economy. The authors focus on the news sentiment because in the current digital era, investors take their decision making on the basis of current trends projected by news and media platforms.

For empirical modeling, the authors use machine learning models to investigate the presence of herding behavior in UK stock market for the period starting from 2006 to 2021. The authors use support vector regression, single layer neural network and multilayer neural network models to predict the herding behavior in the stock market of the UK. The authors estimate the herding coefficients using all the models and compare the findings with the linear regression model.

The results show a strong evidence of herding behavior in the stock market of the UK during different time regimes. Furthermore, when the authors incorporate the economic uncertainty news sentiment in the model, the results show a significant improvement. The results of support vector regression, single layer perceptron and multilayer perceptron model show the evidence of herding behavior in UK stock market during global financial crises of 2007–08 and COVID’19 period. In addition, the authors compare the findings with the linear regression which provides no evidence of herding behavior in all the regimes except COVID’19. The results also provide deep insights for both individual investors and policy makers to construct efficient portfolios and avoid market crashes, respectively.

In the existing literature of herding behavior, news sentiment regarding economic uncertainty has not been used before. However, in the present era this parameter is quite critical in context of market anomalies hence and needs to be investigated. In addition, the literature exhibits varying results about the existence of herding behavior when different methodologies are used. In this context, the use of machine learning models is quite rare in the herding literature. The machine learning models are quite robust and provide accurate results. Therefore, this research study uses three different models, i.e. single layer perceptron model, multilayer perceptron model and support vector regression model to investigate the herding behavior in the stock market of the UK. A comparative analysis is also presented among the results of all the models. The study sheds light on the importance of economic uncertainty news sentiment to predict the herding behavior.

The purpose of this paper is to examine the extent to which Central European emerging stock markets (focusing on Poland) have been affected by the recent international financial crisis, and how the current investment climate (barriers, risks, challenges and opportunities) influences appetite for investments in Polish equities. In doing so, the study aims to report timely findings in relation to the determinants of the safety and profitability of international portfolio diversification to the Polish stock market.

Based on qualitative empirical research, the authors analyse the differences between the foreign (UK) and domestic (Poland) investors' views on equity investments in Poland. The study builds on questionnaires and interviews with practitioners associated with the Polish stock market.

The authors report that the global financial crisis influenced changes to domestic and international investors' appetite for risk related to equity investments in emerging stock markets: investors are more prudent about emerging markets but the Polish stock market has shown substantial growth potential and positively distinguished itself from other Central European stock exchanges; particular types of investment risks associated with equity investments in the Polish stock market have abated. Polish equities are an attractive component of the international portfolio diversification, provided that trading strategies are adjusted to the contemporary investment environment.

This paper addresses the absence of the academic literature devoted to the analysis of equity investments in the contemporary Central European emerging stock markets. The authors discuss the differences in appetite for risk between the UK and Polish investors and assumptions about investments in Poland. The authors also contribute to the international debate on investor protection and regulations that can improve investment processes.

The purpose of the paper is to investigate co-movement of major implied volatility indices and economic policy uncertainty (EPU) indices with both the health-based fear index and market-based fear index of COVID-19 for the USA and the UK to help investors and portfolio managers in their informed investment decisions during times of infectious disease spread.

This study uses wavelet coherence approach because it allows to observe lead–lag nonlinear relationship between two time-series variables and captures the heterogeneous perceptions of investors across time and frequency. The daily data used in this study about the USA and the UK covers major implied volatility indices, EPU, health-based fear index and market-based fear index of COVID-19 for both the first and second waves of COVID-19 pandemic over the period from March 3, 2020 to February 12, 2021.

The results document a strong positive co-movement between implied volatility indices and two proxies of the COVID-19 fear. However, in all the cases, the infectious disease equity market volatility index (IDEMVI), the COVID-19 proxy, is more representative of the stock market and exhibits a stronger positive co-movement with volatility indices than the COVID-19 fear index (C19FI). This study also finds that the UK’s implied volatility index weakly co-moves with the C19FI compared to the USA. The results show that EPU indices of both the USA and the UK exhibit a weak or no correlation with the C19FI. However, this study finds a significant and positive co-movement of EPU indices with IDEMVI over the short horizon and most of the sampling period with the leading effect of IDEMVI. This study’s robustness analysis using partial wavelet coherence provides further strengths to the findings.

The investment decisions and risk management of investors and portfolio managers in financial markets are affected by the new information on volatility and EPU. The findings provide insights to equity investors and portfolio managers to improve their risk management practices by incorporating how health-related risks such as COVID-19 pandemic can contribute to the market volatility and economic risks. The results are beneficial for long-term equity investors, as their investments are affected by contributing factors to the volatility in US and UK’s stock markets.

This study adds following promising values to the existing literature. First, the results complement the existing literature (Rubbaniy et al., 2021c) in documenting that type of COVID-19 proxy matters in explaining the volatility (EPU) relationships in financial markets, where market perceived fear of COVID-19 is appeared to be more pronounced than health-based fear of COVID-19. Second, the use of wavelet coherence approach allows us to observe lead–lag relationship between the selected variables, which captures the heterogeneous perceptions of investors across time and frequency and have important insights for the investors and portfolio managers. Finally, this study uses the improved data of COVID-19, stock market volatility and EPU compared to the existing studies (Sharif et al., 2020), which are too early to capture the effects of exponential spread of COVID-19 in the USA and the UK after March 2020.

This study aims to examine the spillover effects of trans-Atlantic macroeconomic uncertainties on the local stock market returns in the USA and eight selected European countries, namely, Germany, France, Spain, Italy, Greece, Ireland, Sweden and the UK, during the 2000-2019 period.

This paper applies the dynamic conditional correlation multivariate GARCH model (i.e. multivariate generalized autoregressive conditional heteroskedasticity model or DCC MGARCH) to examine the potential existence of the spillover from the uncertainty of the USA to EU stock markets and vice versa. To capture different dynamic relationships between multiple time-series variables following different regimes, this paper applies the Markov switching model to the stock returns of both the USA and the eight major stock markets.

The increases in US uncertainty have significant negative impacts on all EU stock returns, whereas only the increases in the uncertainties of Spain, Ireland, Sweden and the UK have significant negative impacts on US stock returns. Notably, the economic policy uncertainty (EPU) in the USA has a dynamic effect on the European stock markets. In a bear market (State 1), the increases in the EPU of the USA and EU have significant negative impacts on EU stock returns in most cases. However, only the increase in US EPU has significant negative impacts on EU stock returns in bull markets (State 2). Reciprocally, the increases in the EU EPUs of Germany, Spain and the UK have significant impacts on US stock returns in bear market.

The observations challenge the conventional wisdom according to which only larger economies can lead the smaller counterparts. The findings also highlight the stronger dependence of the US stock market on international macroeconomic uncertainty.

This paper aims to examine the behaviour, both contemporaneous and causal, of stock and bond markets across four major international countries.

The authors generate volatility and correlations using the realised volatility approach and implement a general vector autoregression approach to examine causality and spillovers.

While results confirm that same asset-cross country return correlations and spillovers increase over time, the same in not true with variance and covariance behaviour. Volatility spillovers across countries exhibit a substantial amount of time variation; however, there is no evidence of trending in any direction. Equally, cross asset – same country correlations exhibit both negative and positive values. Further, the authors report an inverse relation between same asset – cross country return correlations and cross asset – same country return correlations, i.e. the stock return correlation across countries increases at the same time the stock and bond return correlation within each country declines. Moreover, the results show that the stock and bond return correlations exhibit commonality across countries. The results also demonstrate that stock returns lead movement in bond returns, while US stock and bond returns have predictive power other country stock and bond returns. In terms of the markets analysed, Japan exhibits a distinct nature compared with those of Germany, the UK and USA.

The results presented here provide a detailed characterisation of how assets interact both with each other and cross-countries and should be of interest to portfolio managers, policy-makers and those interested in modelling cross-market behaviour. Notably, the authors reveal key differences between the behaviour of stocks and bonds and across different countries.

Aims to investigate whether the level and volatility of interest rates affect the excess returns of major Asian listed property markets within a time‐varying risk framework.

A three‐factor model is employed with excess return volatility, interest rate level and interest rate volatility as its factors. The generalized autoregressive conditionally heteroskedasticity in the mean (GARCH‐M) analyzes are undertaken on monthly excess returns of property stock indexes for the period 1987‐2003.

Property stocks are generally sensitive to changes in the long‐term and short‐term interest rates and to a lesser extent, their volatility. Moreover, there are disparities in the magnitude as well as direction of sensitivities in interest rate level and volatility across the listed property markets and under different market conditions. Overall, results indicate changes in the ARCH parameter, risk premia, volatility persistence and interest rate level and volatility effects before and after the 1997 Asian financial crisis. However, these noted changes are not uniform and depend on the individual listed property markets.

The findings enhance investors' understanding in financial asset pricing and complement existing evidence in international real estate. With the increasing significance of property stocks as real estate investment vehicles for international investors to gain property exposure in Asia and internationally, the paper is timely and provides the basis for more advanced research in international real estate investment strategies and capital asset pricing.

The purpose of this paper is to examine volatility transmissions between portfolios of cross‐listed equities and exchange rate differences and also the volatility persistence for home, foreign equities, and exchange rate differences in the UK and German markets.

A primary focus of this paper is to see if there is an impact first on the volatility persistence for foreign equities that are listed in the UK and German markets, second on the respective home portfolios of cross‐listed equities, and third on the exchange rate differences. In addition, whether there are any bilateral spillovers between the following equity portfolios: foreign cross‐listed equities, home cross‐listed equities, and also local or global exchange rate differences are investigated.

The paper finds that the volatility persistence is more prominent than error persistence from cross‐listed equities, foreign or home, and the exchange rate differences. Furthermore, the transmission mechanism indicates a bilateral integration process in some of the cases that were examined. Based on these results, it is concluded that in the UK market the foreign cross‐listings affect less the domestic equities compared to the German market.

This paper examines the interdependence of portfolios of home and foreign equities for cross‐listings that belong to the same stock exchange with two exchange rates, a local and a global one in order to provide more evidence in this area of literature.