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The assessment of interdependence between stock markets is an important aspect of international portfolio management. The purpose of this paper is to examine and highlight the diversification potential of South Asian stock markets vis-à-vis developed and European stock markets.

The developed stocks markets include USA and UK, and South Asian stock markets include India, Pakistan and Sri Lanka while DJ STOXX 600 index is used to represent the European stock markets. Monthly data are used to examine long-run relationship through ARDL bound testing approach and estimates are obtained using DLOS. Short-term dynamics are captured through vector error correction-based Granger causality.

South Asian stock markets are closely linked with each other; similarly, developed/European markets are interlinked. US stock market not only impacts European stock markets, it also Granger cause South Asian stock markets. The findings suggest increase in comovement of South Asian stock markets with the global markets after financial crises of 2007-2008.

The diversification benefits of South Asian stock markets for international investors are still evident due to their low relationship (in both long and short run) with developed/European stock markets.

Given the emergence of South Asian stock markets, new insight on their relationship with developed stock markets can provide interesting findings for international portfolio diversification. The South Asian equity markets are an important source of investment because of their immense growth and weak correlation with international markets.

This study examines the effects of global oil shocks on sectoral returns during the Pakistani market’s bearish, normal and bullish behavior by controlling VIX and SP500.

We analyze daily sectoral return data from the Pakistan Stock Exchange, covering the period from January 2, 2012, to February 17, 2022. Oil shocks are classified into demand, risk and supply shocks using Ready (2018) methodology, distinguishing their unique characteristics and importance. We utilize quantile regression to evaluate how these oil shocks affect sectoral returns, considering market dynamics. Additionally, we employ the Granger causality test to validate our findings.

The quantile regression results indicate that the effects of oil shocks on each sector are heterogeneous and significant during both bullish and bearish market phases. Specifically, supply shocks demonstrate a more substantial influence than other shocks, consistent with Kilian’s (2009) findings. Furthermore, the Granger causality test outcomes, conducted after removing control variables, reinforce our findings.

This study offers evidence that aids investors in understanding how shocks affect sectoral returns. Additionally, it provides insights for policymakers to develop policies that respond effectively to market fluctuations caused by these shocks.

This study holds value for researchers investigating the causes of shocks and their implications for the stock market. Moreover, the insights from this study, focusing on the Pakistani market, could provide a fundamental reference for other oil-dependent nations aiming to mitigate the impacts of global oil price volatility.

It has been demonstrated in the US market that expected market excess returns can be predicted using the average higher-order moments of all firms. This study aims to empirically test this theory in emerging markets.

Two measures of average higher moments have been used (equal-weighted and value-weighted) along with the market moments to predict subsequent aggregate excess returns using the linear as well as the quantile regression model.

The authors report that both equal-weighted skewness and kurtosis significantly predict subsequent market returns in two countries, while value-weighted average skewness and kurtosis are significant in predicting returns in four out of nine sample markets. The results for quantile regression show that the relationship between the risk variable and aggregate returns varies along the spectrum of conditional quantiles.

This is the first study that investigates the impact of third and fourth higher-order average realized moments on the predictability of subsequent aggregate excess returns in the MSCI Asian emerging stock markets. This study is also the first to analyze the sensitivity of future market returns over various quantiles.

This study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets.

This study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns.

The results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks.

The sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate.

This paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior.

The study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.

The purpose of this study is to investigate how the uncertainty associated with fiscal policy, i.e. government expenditure and tax revenues, can affect the interest rates in a group of eleven countries, comprising high- and low-debt countries: Cyprus, Greece, Ireland, Italy, Portugal, Spain, Australia, Canada, Denmark, New Zealand and Norway.

The empirical analysis makes use of the structural VAR (SVAR) methodological approach, which allows us to decompose the effects of the contribution of shocks generated by each variable, as well as their transmission effects.

The empirical findings suggest that both demand and supply factors influence interest rates across their frequency spectrum. For the majority of high-debt countries, the course of the yields on their government bonds is driven mainly by supply side factors and not demand (i.e. government expenses or taxes) factors.

Given that the economies of certain (mostly small) countries are affected by economic conditions in large countries, especially when they have large capital flows or trade much with these countries, the future empirical analysis could also consider both domestic and international (control) macroeconomic variables to explain the course of interest rates due to fiscal changes.

The previous literature does not capture the financial crisis period, nor does it take a comparative approach – high debt versus low debt – to investigate the effect of fiscal shocks on interest rates. Thus, we aim to respond to the following questions: (1) How do fiscal shocks affect interest rates in the sample of selected countries? (2) How different is the impact of fiscal shocks on interest rates in high- and low-debt countries?

The rising interconnectedness between international banks, at one end, allow participants to share risk and diversification which leads to stable local lending and increase in competitiveness, however, at the other end poses potential for volatility spillover and thereby contagion phenomena. Therefore, investigating the presence of co-integration amongst international banks can provide useful information about risk spillover in times of financial turbulence

The authors employ wavelet correlation and wavelet multiple cross-correlation strategies, following an initial decomposition of returns series through maximal overlap discrete wavelet transformation (MODWT).

The results indicate high integration level between Citibank and Deutsche Bank whereas potential of diversification exists between pairs of Citibank–Hong Kong and Shanghai Banking Corporation and Bank of America–Deutsche Bank, with former more evident in short- and medium-term relationship and later in long-run investment horizon. This paper carries implications for investors, fund managers and policymakers in foreseeing the prospects of contagion attributable to high level integration levels.

Implications for cross-border banking integration includes the presence of common lender effect which appears as a dominant factor for cross-border contagion. Therefore, banks based in different countries should focus more on funds diversification rather than borrowing much from any single creditor. Furthermore, foreign operations based on subsidiaries instead of relying on direct cross-border lending can help in reducing volatility of the foreign financial resources. Nevertheless, based on the results and significant strand of existing literature, the presence of contagion is inevitable, and therefore, a careful consideration of cross-border banking supervision and co-operation by the financial authorities can help in mitigating the volatility of global capital flows.

First, this study fills gap in the existing literature regarding the discussion on portfolio diversification opportunities in the banking sector. The banking sector is usually perceived as a main source of fixed income securities or financing; however, on the contrary, investors may also be interested for investments in publicly listed bank's stock. Most of the work regarding portfolio diversification revolves around capital market instruments; however, publicly listed shares of largest bank also present an avenue for diversification. Second, major fundamentals and the associated factor for banks performance are reflected in the its profits, either these profits result from large customer base or proper allocation of bank's assets, etc. Therefore, returns of these banks serve as a barometer for their performance and co-movement between any two banks can highlight the presence and extent of their underlying association. Third, the authors apply the latest extensions in wavelet techniques after decomposing returns series through the MODWT framework. This decomposition followed by wavelet estimations allow us to investigate banks integration level across different time and frequency space thereby carrying implications for both short- and long-run investors. Fourth, by analysing the presence of returns co-movements, the authors can predict the extent of plausible contagion since the recent global financial crisis of 2008–2009 used banks as the main medium of propagation of shocks. Fifth, the work presents many implications for the investment community, major trading partners associated with banks through different instruments and for policymakers so that the effect of contagion can be anticipated or at least mitigated in case of future financial turbulence.

Highlights

1. We investigate portfolio diversification opportunities in the banking sector.

2. Time-frequency returns co-movements is measures by applying wavelet multiple correlation and cross-correlation techniques on decomposed return series.

3. Deutsche Bank and Bank of America act as highest transmitter and recipient of volatility, respectively using the spillover approach of Diebold and Yilmaz (2012).

4. Citibank and Deutsche Bank exhibit high pairwise correlation indicating no diversification benefits.

5. Citibank exhibits high level of integration with other banks in the short- and medium-run whereas Deutsche Bank exercises high integration levels in the long-run investment period.

We investigate portfolio diversification opportunities in the banking sector.

Time-frequency returns co-movements is measures by applying wavelet multiple correlation and cross-correlation techniques on decomposed return series.

Deutsche Bank and Bank of America act as highest transmitter and recipient of volatility, respectively using the spillover approach of Diebold and Yilmaz (2012).

Citibank and Deutsche Bank exhibit high pairwise correlation indicating no diversification benefits.

Citibank exhibits high level of integration with other banks in the short- and medium-run whereas Deutsche Bank exercises high integration levels in the long-run investment period.

This paper aims to explore the impact of investor sentiments on economic policy uncertainty (EPU). The analysis also considers the momentum effect, stock market returns volatility and equity pricing inefficiencies across markets, which, to the best of the authors’ knowledge, has not been addressed in the literature. The role of these control variables has collectively been considered to have important behavioral implications for international investors

Quantile regressions are used for estimation purpose, as it provides robust and more efficient estimates rather than those coming from the traditional regression model.

The momentum effect is negative and significant only at higher quantiles, while oil prices are positive and significant across all quantiles. The exchange rate exerts a negative and significant effect on EPU, whereas equity price volatility (i.e. investor sentiment) exerts a negative and significant impact on EPU in most of the quantiles.

The results have important implications for international investors and policymakers, especially in terms of the breakdown of economic policy uncertainty across different sample markets. The breakdown of complete sample period into sub-samples acts as a robust analysis and documents the similarity of the results for the Asian and developed markets cases, but not in the case of the European markets.

The findings imply the importance of financial stability that impacts the accumulation of systemic risks and adds smoothness to the financial cycle in particular geographical areas.

The contribution of this paper is threefold. First, existing literature highlights and empirically tests the impact of economic policy uncertainty on different market, macro-economic and global control variables. The analysis, however, performs it in the reverse order, i.e. analyzing the impact of the momentum effect (investor sentiment variables), equity market inefficiencies and volatility (market variables) and exchange rates and Brent oil (control variables). Second, to check the sensitivity of economic policy uncertainty, the analysis analyzes a wide range of markets, segregated as emerging, developed and European regions over the sample period to generate region-wise implications. Finally, the analysis explores the relationship of aforementioned variables with economic policy uncertainty keeping in view the non-linear structure and prior evidence and investor sentiments and economic policy uncertainty in the regression model.