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This paper investigates the influence of three different sentiment indicators on the time-varying stock–bond correlation of 15 countries during the global crisis period of the coronavirus disease 2019 (COVID-19) pandemic.

The author uses the time-varying correlation estimated using the autoregressive moving average -dynamic conditional correlation - generalised autoregressive conditional heteroskedasticity (ARMA-DCC-GARCH) model to achieve this aim. The impact of investor sentiment on the stock–bond correlation was analysed using the Markov regime-switching regression.

The study results show that the sentiment indicators of fear, uncertainty and distress have a pronounced negative impact on the stock–bond correlation. They further provide evidence of a strong regime effect on the stock–bond correlation with sentiment indicators.

The paper has a relevant impact on policymakers and fund managers. First, the policymakers now have more insightful evidence of how the stock and bond markets react during crises. Second, the fund managers need to focus on behavioural variables as they may be driving factors in crisis periods that may impair portfolio management.

To the best of my knowledge, the paper is the first to throw light on the behaviour of the stock–bond correlation for 15 countries during the COVID-19 period.

This study aims to observe the extent of asset diversification benefits in the Association of Southeast Asian Nations (ASEAN)-5 market by examining the effect of financial integration (FI) and financial development (FD) on domestic stock–bond co-movements, SBcorr.

The dynamic conditional correlation - multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) technique is adopted to construct FI and stock−bond co-movement variables. Then, the study uses static panel data analysis to examine the effect of FI on stock−bond co-movements.

FI does not provide asset diversification benefits due to high country risks in ASEAN-5. However, when FI is moderated by FD, FI × FD, the study shows that FI × FD provides higher asset diversification benefits in ASEAN-5.

This study shows the importance of incorporating the level of FD when assessing the effect of FI on stock–bond co-movements in ASEAN-5. In the presence of FI, a well-diversified investor should always consider the state of FD, which will show a better representation of asset diversification strategy in the emerging markets. Additionally, policymakers of ASEAN-5 countries should prioritise enhancing their financial system to attract more investment into the countries.

Refers to previous research on deciding the balance between equities and bonds in investment portfolios and puts forward a model based on a single period correlation to predict future stock‐bond correlations from past interest and growth rates. Explains the concepts involved and uses 1948‐2000 US data to test it. Shows that the model predicts stock‐bond correlation significantly better than the traditional method of extrapolating from past correlations; and relates this to the theory of loanable funds. Concludes that high interest rates and high growth lead to higher correlations between stocks and bonds and calls for further research.

This paper investigates the impact of a change in economic policy uncertainty (ΔEPUt) and the absolute value of a change in geopolitical risk (|ΔGPRt|) on the returns of stocks, bonds and gold in the Chinese market.

The paper uses Engle's (2009) dynamic conditional correlation (DCC) model and Chiang's (1988) rolling correlation model to generate correlations of asset returns over time and analyzes their responses to (ΔEPUt) and  |ΔGPRt|.

Evidence shows that stock-bond return correlations are negatively correlated to ΔEPUt, whereas stock-gold return correlations are positively related to the |ΔGPRt|, but negatively correlated with ΔEPUt. This study finds evidence that stock returns are adversely related to the risk/uncertainty measured by downside risk,  ΔEPUt and  |ΔGPRt|, whereas the bond return is positively related to a rise in ΔEPUt; the gold return is positively correlated with a heightened |ΔGPRt|.

The findings are based entirely on the data for China's asset markets; further research may expand this analysis to other emerging markets, depending on the availability of GPR indices.

Evidence suggests that the performance of the Chinese market differs from advanced markets. This study shows that gold is a safe haven and can be viewed as an asset to hedge against policy uncertainty and geopolitical risk in Chinese financial markets.

This study identify the special role for the gold prices in response to the economic policy uncertainty and the geopolitical risk. Evidence shows that stock and bond return correlation is negatively related to the ΔEPU and support the flight-to-quality hypothesis. However, the stock-gold return correlation is positively related to |ΔGPR|, resulting from the income or wealth effect.

The presence of a dynamic correlations between stock-bond and stock-gold relations in response to  ΔEPUt and  |ΔGPRt| has not previously been tested in the literature. Moreover, this study finds evidence that bond-gold correlations are negatively correlated to both ΔEPUt and  |ΔGPRt|.

Aims to test to determine whether the selection of the historical return time interval (monthly, quarterly, semiannual, or annual) used for calculating real estate investment trust (REIT) returns has a significant effect on optimal portfolio allocations.

Using a mean‐variance utility function, optimal allocations to portfolios of stocks, bonds, bills, and REITs across different levels of assumed investor risk aversion are calculated. The average historical returns, standard deviations, and correlations (assuming different time intervals) of the various asset classes are used as mean‐variance inputs. Results are also compared using more recent data, since 1988, with, data from the full REIT history, which goes back to 1972.

Using the more recent REIT datarather than the full dataset results in optimal allocations to REITs that are considerably higher. Likewise, using monthly and quarterly returns tends to understate the variability of REITs and leads to higher portfolio allocations.

The results of this study are based on the limited historical return data that are currently available for REITs. The results of future time periods may not prove to be consistent with the findings.

Numerous research papers arbitrarily decide to employ monthly or quarterly returns in their analyses to increase the number of REIT observations they have available. These shorter interval returns are generally annualized. This paper addresses the consequences of those decisions.

It has been shown that the decision to use return estimation intervals shorter than a year does have dramatic consequences on the results obtained and, therefore, must be carefully considered and justified.

This study examines co-movements between global Islamic index and heterogeneous rated/maturity sukuk. It tests the impact of financial uncertainty on these movements.

Firstly, we conduct a bivariate wavelet analysis to assess the co-movements between stocks and sukuk indexes. Secondly, we use General dynamic factor model and stochastic volatility to construct financial uncertainty index from Islamic stock indexes. Finally, we run regression analysis to determine the impact of uncertainty on the obtained correlations.

Our results suggest the absence of flight to quality phenomenon since correlations are positive especially at a short investment horizon. There is evidence of contagion phenomena across assets. Financial uncertainty may be considered as a determinant of stock-sukuk co-movements. Our results show that a rise in financial uncertainty induces correlation to move in the opposite direction in the short term, (exception for correlation with AA-Rated sukuk). However, the sign of stock market uncertainty becomes positive in the long term, which leads sukuk and stocks to move in the same direction (exception for 1–3 Year and AA Rated sukuk).

Investors may combine sukuk with 1–3 Year maturity and AA Rated when considering long holding periods. Further, all sukuk categories provide diversification benefit in time high financial uncertainty expectation for AA Rated sukuk when considering short holding periods.

To the best of our best knowledge, our study is the first investigation of the impact of financial uncertainty on Stock-sukuk co-movements and provides recommendation considering sukuk with different characteristics.

Over the last few years, Central and East European economies have become more integrated with the West European economy. In general, these economies have become more market-oriented and restrictions on foreign investment have been relaxed. An important step in this development was the admission of eight East European countries to the European Union (EU) in 2004. As the economic ties between Western, Central and Eastern Europe strengthen, one would naturally expect the financial markets to follow suit and become more integrated as well. A good example is the historical case of the Italian and German government bond markets: Before 1999 these two markets differed markedly in terms of credit quality and price volatility, but since the creation of the Euro zone in 1999 they have become highly similar.

The purpose of this study is to assess alternative financial stress indicators for India in terms of tracing crisis events, mapping with the business cycle and the macroeconomic effect of stress indices.

The study constructs the composite indicator of systemic stress of Hollo, Kremer and Lo Duca (2012) for India using two different methods for computing time-varying cross-correlation matrix, namely, exponentially weighted moving average (EWMA) and dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity (DCC-GARCH). The derived indices are evaluated with widely used, equal variance and principal component weighting indices in terms of tracing stress events, mapping with the business cycles and the macroeconomic effect. For this purpose, the study identifies various episodes of financial stress and uses the business cycle dates in the sample covering from January 2001 to October 2018.

The results suggest that stress indices based on EWMA and DCC-GARCH accurately identify the well-known stress periods and capture the recession dates and show an adverse effect on economic activity. Primarily, the DCC-GARCH-based stress index emerges as a better indicator of stress because it efficiently locates all the major-minor events, traces the build-up of stress and reverts to the normal level during stable times.

The DCC-GARCH-based stress index is a very useful indicator for policymakers in regularly monitoring India’s financial conditions and providing timely identification of systemic stress to avoid adverse repercussion effects of the financial crisis.

The 2007–2008 financial crisis and subsequent recurrent instability in the financial markets highlighted the requirement for an appropriate financial stress indicator for a timely assessment of the system-wide financial stress. To the authors’ knowledge, this is the first study that incorporates the systemic nature of financial stress in the construction of stress indices for India and provides a holistic evaluation of the financial stress from an emerging country’s perspective.

Portfolio construction and diversification is a prominent challenge for investors. It reflects market agents’ behavior and response to market conditions. This paper aims to investigate the stock-bond nexus in the case of two emerging and two mature markets, India, South Africa, the UK and the USA, using long-term historical monthly data.

To address the issue at hand, copula quantile-on-quantile regression (C-QQR) is used to model the correlation structure. Although this technique is driven by copula-based quantile regression model, it retains more flexibility and delivers more robust and accurate estimates.

Results suggest that there is substantial heterogeneity in the bond-stock returns correlation across the countries under study point to different investors’ behavior in the four markets examined. Additionally, the findings reported herein suggest that using C-QQR in portfolio management can enable the formation of tailored response strategies, adapted to the needs and preferences of investors and traders.

To the best of the authors’ knowledge, no previous study has addressed in a comparative setting the stock-bond nexus for the four countries used here using long-term historical data that cover the periods 1920:08-2017:02, 1910:01-2017:02, 1933:01-2017:02 and 1791:09-2017:02 for India, South Africa, the UK and the USA, respectively.

This paper investigates the impact of financial stress on the dynamic connectedness and hedging for oil market and stock-bond markets of the Gulf Cooperation Council (GCC).

This study uses the wavelet coherence model to examine the interactions between financial stress, oil and GCC stock and bond markets. Second, the authors apply the time–frequency connectedness developed by Barunik and Krehlik (2018) so as to identify the direction and scale connectedness among these markets. Third, the authors examine the optimal weights, hedge ratio and hedging effectiveness for oil and financial markets based on constant conditional correlation (CCC), dynamic conditional correlation (DCC) and Baba-Engle-Kraft-Kroner (BEKK)-GARCH models.

The authors have found that the correlation between the oil and stock-bond markets tends to be stable in nonshock periods, but it evolves during oil and financial shocks at lower frequencies. Moreover, the authors find that the oil market and financial stress are the main transmitters of risks. The connectedness is mainly driven by the long term, demonstrating that the markets rapidly process the financial stress spillover effect, and the shock is transmitted over the long run. Optimal weights show different patterns for each negative and positive case of the financial stress index. In the negative (positive) financial stress case, investors should have more oil (stocks) than stocks (oil) in their portfolio in order to minimize risk.

This study has gone some way toward enhancing one’s understanding of the time–frequency connectedness between the financial stress, oil and GCC stock-bond markets. Second, it identifies the impact of financial stress into hedging strategies offering important insights for investors aiming at managing and reducing portfolio risk.