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This paper examines the time-varying return connectedness between renewable energy, oil, precious metals, the Gulf Council Cooperation region and the United States stock markets during two successive crises: the pandemic Covid-19 and the 2022 Russo-Ukrainian war. The main objective is to investigate the effect of the Covid-19 pandemic and the Russo-Ukrainian war on the connectedness between the considered stock markets.

This paper uses the time-varying parameter vector autoregression approach, which represents an extension of the Spillover approach (Diebold and Yilmaz, 2009, 2012, 2014), to examine the time-varying connectedness among stock markets.

This paper reflects the effect of the two crises on the stock markets in terms of shock transmission degree. We find that the United States and renewable energy stock markets are the main net emitters of shocks during the global period and not just during the two considered crises sub-periods. Oil stock market is both an emitter and a receiver of shocks against Gulf Council Cooperation region and United States markets during the full sample period, which may be due to price fluctuation especially during the two crises sub-periods, which suggests that the future is for renewable energy.

This paper examines the effect of the two recent and successive crises, the Covid-19 pandemic and the 2022 Russo-Ukrainian war, on the connectedness among traditional stock markets (the United States and Gulf Council Cooperation region) and commodities stock markets (renewable energy, oil and precious metals).

The purpose of this paper is to contribute to the literature in three ways: first, the authors investigate the impact of the sampling errors on optimal portfolio weights and on financial investment decision. Second, the authors advance a comparative analysis between various domestic and international diversification strategies to define a stochastic optimal choice. Third, the authors propose a new methodology combining the re-sampling method, stochastic optimization algorithm, and nonparametric stochastic dominance (SD) approach to analyze a stochastic optimal portfolio choice for risk-averse American investors who care about benefits of domestic diversification relative to international diversification. The authors propose a new portfolio optimization model involving SD constraints on the portfolio return rate. The authors define a portfolio with return dominating the benchmark portfolio return in the second-order stochastic dominance (SSD) and having maximum expected return. The authors combine re-sampling procedure and stochastic optimization to establish more flexibility in the investment decision rule.

The authors apply the re-sampling procedure to consider the sampling error in the optimization process. The authors try to resolve the problem of the stochastic optimal investment strategy choice using the nonparametric SD test by Linton et al. (2005) based on sub-sampling simulated p values. The authors apply the stochastic portfolio optimization algorithm with SSD constraints to define optimal diversified portfolios beating benchmark indices.

First, the authors find that reducing sampling error increases the dominance relationships between different portfolios, which, in turn, alters portfolio investment decisions. Though international diversification is preferred in some cases, the study’s results show that for risk-averse US investors, in general, there is no difference between the diversification strategies; this implies that there is no increase in the expected utility of international diversification for the period before and after the 2007-2008 financial crisis. Nevertheless, the authors find that stochastic diversification in domestic, global, and Europe, Australasia, and Far East markets delivers better risk returns for the US risk averters during the crisis period.

The originality of the idea in this paper is to introduce a new methodology combining the concept of portfolio re-sampling, stochastic portfolio optimization with SSD constraints, and the nonparametric SD test by Linton et al. (2005) based on subsampling simulated p values to analyze the impact of sampling errors on optimal portfolio returns and to investigate the problem of stochastic optimal choice between international and domestic diversification strategies. The authors try to prove more coherence in the portfolio choice with the stochastically and the uncertainty characters of the paper.

This paper aims to investigate the hedge, safe-haven and diversifier properties of Islamic indexes, Bitcoin and gold for ten of the most affected countries by the coronavirus, which are the USA, Brazil, the UK, Italy, Spain, Germany, France, Russia, China and Malaysia.

This research uses the Ratner and Chiu (2013) methodology based on the dynamic conditional correlation models to improve Baur and McDermott (2010). The authors adopt a careful investigation of the features of a diversifier, hedge and safe haven using the dynamic conditional correlation–GARCH and quantile regression models.

Empirical results indicate that Islamic indexes are not considered as hedge assets for the conventional market for all studied countries during the COVID-19 pandemic crisis period. However, gold works as a strong hedge in all countries, except for Brazil and Malaysia. Bitcoin is a strong hedge in the USA and a strong hedge and safe haven in China.

International investors in China and the US stock markets should replace Islamic ‎indexes with Bitcoin in their conventional portfolio of securities during the pandemic.

To the best of the authors’ knowledge, this is the first paper that re-evaluates the hedge, safe-haven and diversifier properties of Islamic indexes, Bitcoin and gold for ten of the most affected countries by the coronavirus.

This paper aims to investigate simultaneously the causality and the dynamic links between exchange rates and stock market indices. It attempts to identify the short- and long-term effect of the US dollar on major stock market indices of Brazil, Russia, India, China and South-Africa (BRICS) nations.

This paper applies a new methodology combining the panel generalized method of moments model and the panel auto-regressive distributed lag (ARDL) method to investigate the existence of a causal short-/long-run relationships and dynamic dependence among all stock market returns and exchanges rates changes of BRICS countries.

Results show that exchange rate changes have a significant effect on the past and the current volatility of the BRICS stock indices. Besides, ARDL estimations reveal that exchange rate movements have a significant effect on short- and long-term stocks market indices of all BRICS countries

The findings have implications for policymakers and market participants who try to manage the exchange rate will have a different dose of intervention if they know that the effects of currency depreciation are different than appreciation. These results have important implications that investors should take into account in frequency-varying exchange rates and stock returns and regulators should consider developing sound policy measures to prevent financial risk.

This paper aims to investigate whether Islamic indexes, Bitcoin and gold still act as hedges or/and “safe-haven” assets during the COVID-19 pandemic crisis. This paper examines the role of the Morgan Stanley Capital International all-country world index, Islamic index, gold and Bitcoin as a hedge or safe-haven asset for the world conventional stock market over the period from April 30, 2015 to March 27, 2020.

In this paper, the authors re-evaluate the hedge and safe haven properties of Islamic indexes, gold and Bitcoin following Baur and Lucey’s (2010) and Baur and McDermott’s (2010) methodology.

Empirical results show that the Islamic index is not a hedge or a safe haven asset for the world conventional stock market during the recent coronavirus crisis period. Different from the whole period, the authors find that gold is a strong hedge but only a weak safe or is not a safe haven during the coronavirus sub-period. Bitcoin reports distinctive properties, as it acts as a weak hedge and not a safe-haven asset.

This paper is the first study that investigates whether the global Islamic index still acts as hedges or “safe-haven” assets during the new COVID-19 crisis period. The results can help investors make informed decisions when adding cryptocurrencies and Islamic indexes to their portfolios during the coronavirus crisis.

Since equity markets have a dynamic nature, the purpose of this paper is to investigate the performance of a revision procedure for domestic and international portfolios, and provides an empirical selection strategy for optimal diversification from an American investor's point of view. This paper considers the impact of estimation errors on the optimization processes in financial portfolios.

This paper introduces the concept of portfolio resampling using Monte Carlo method. Statistical inferences methodology is applied to construct the sample acceptance regions and confidence regions for the resampled portfolios needing revision. Tracking error variance minimization (TEVM) problem is used to define the tracking error efficient frontiers (TEEF) referring to Roll (1992). This paper employs a computation method of the periodical after revision return performance level of the dynamic diversification strategies considering the transaction cost.

The main finding is that the global portfolio diversification benefits exist for the domestic investors, in both the mean-variance and tracking error analysis. Through TEEF, the dynamic analysis indicates that domestic dynamic diversification outperforms international major and emerging diversification strategies. Portfolio revision appears to be of no systematic benefit. Depending on the revision of the weights of the assets in the portfolio and the transaction costs, the revision policy can negatively affect the performance of an investment strategy. Considering the transaction costs of portfolios revision, the results of the return performance computation suggest the dominance of the global and the international emerging markets diversification over all other strategies. Finally, an assessment between the return and the cost of the portfolios revision strategy is necessary.

The innovation of this paper is to introduce a new concept of the dynamic portfolio management by considering the transaction costs. This paper investigates the performance of a revision procedure for domestic and international portfolios and provides an empirical selection strategy for optimal diversification. The originality of the idea consists on the application of a new statistical inferences methodology to define portfolios needing revision and the use of the TEVM algorithm to define the tracking error dynamic efficient frontiers.