Risk spillovers and portfolio management between developed and BRICS stock markets

This paper investigates spillover effects and portfolio diversification between the four major developed stock markets (USA, Europe, Japan and Asia) and five of the most important emerging stock markets known as the BRICS (Brazil, Russia, India, China and South Africa). To this end, we apply the multivariate DECO-FIEGARCH model to daily spot indices during the period 1998–2016. The results reveal a significant and asymmetric long memory process for both the developed and the BRICS markets. Moreover, we find a significant variability in the time-varying conditional correlations between the considered markets during both bull and bear markets, particularly from early 2007 to summer 2008. Additionally, we analyze the optimal portfolio weights, time-varying hedge ratios and hedging effectiveness based on the estimates of the model. The results underline the importance of overweighting the optimal portfolios with stocks from the developed countries over those from the BRICS. Finally, we assess the practical implications for mixed developed-BRICS stock portfolios, based on finding strong evidence of diversification benefits and downside risk reductions that confirm the usefulness of using developed market stocks in the BRICS stock portfolio risk management.     

Region-wide connectedness of Asian equity and currency markets

This study systemically analyzes the dynamics of interdependence between the Asian equity and currency markets. The novelty of our study is that unlike other studies that explore either co-movements among equity markets or co-movements among currency markets, we pay particular attention to the interdependence between the two in terms of both return and volatility connectedness. We find that the contribution of crossspillovers between the Asian equities and currencies is substantial for the region-wide connectedness of both the returns and volatilities. We also find that the short-term spillovers are far more important for the return spillovers, while the long-term spillovers are far more important for the volatility spillovers, presumably reflecting the long-lasting effects of volatility shocks. All the results consistently underline the pivotal role of cross-interdependence between equity and currency markets, both as channels for integrating Asian financial markets and as sources of financial contagion across these markets. Our findings will provide useful guidance for portfolio risk management to adopt better hedging strategies for foreign exchange risks involved in the international investment of Asian equities.     

Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis

This study examines market co-movements in Islamic and mainstream equity markets across different regions in order to discover contagion during 9 major crises and to measure integration between markets. Using wavelet decomposition to unveil the multi-horizon nature of co-movement, we find that the shocks were transmitted via excessive linkages, while the recent subprime crisis reveals fundamentals-based contagion. While Islamic markets show traces of reduced exposure to the recent crisis owing to low leverage effect, their less diversified portfolio nature increases vulnerability to other crises. We generally find incomplete market integration, with relatively higher fundamental integration for Islamic markets which may be attributable to their real sector allocation nature.     

The strength and source of asymmetric international diversification

We find that correlations between international markets continue to increase over time compared to previous research, with only Asian markets providing lower correlations relative to American and European markets. Consistent with previous studies, the benefits from international diversification are asymmetric, with reduced diversification benefits during bear markets. We extend previous results by examining the characteristics and causes of the returns affecting these asymmetric correlations, relating these results to the herding behavior of investors across markets rather than to fundamental economic reasons. Specifically, we determine that the increase in correlations among markets is most closely associated with the larger correlations from the largest positive return time intervals in bear markets rather than the negative returns. Use of stock index futures avoids issues inherent in the use of international cash indexes.     

Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America,Middle East,and BRICs

We studied the risk-return distances of 18 emerging stock markets in the period from January 2000 to December 2013. Distances are linked to volatility and time-varying correlations estimated in standard and asymmetric DCC models. Our results revealed a positive relationship between risk-return distances and volatility, which means that during more volatile periods, the risk-return characteristics in emerging markets exhibit lower similarity to the characteristics found in developed markets. This result seems to be in sharp contrast to most empirical studies using correlations. Within the portfolio framework, our results suggest that diversification into emerging stock markets may still provide desirable benefits to international investors.     

Dynamic interactions between Central European currencies and the euro

We argue that the non-euro EU currencies of Central European countries have moved increasingly together with the euro in foreign exchange markets. To prove this point, we examine the dynamics of cross-elasticity between selected Central European currencies (the Czech koruna, Polish zloty, and Hungarian forint) and the euro exchange rates in U.S. dollar terms using daily data for the January 4, 2000 to April 5, 2019 sample period. We adopt the cross-elasticity model originally proposed and tested for the EU currencies by Orlowski (2016). To test the currency co-movements over time, we employ the Bai-Perron multiple breakpoint regression and two-state Markov switching tests. We find evidence of increasing co-movements between the Central European currencies and the euro that become particularly pronounced in times of financial distress. Co-movements of local exchange rates with the euro are also more pronounced during the euro-periphery sovereign debt crisis.     

欧洲股票市场的规模和动因:基于不同β系数的资本资产定价模型实证研究

我们选用在13个欧洲股市上市的证券,形成规模和动因组合。我们不仅发现规模溢价的证据,还发现8个样本市场存在重大动因收益率。这些收益率可能不构成异常现象,因为它们与不同β值的资本资产定价模型一致。我们还发现,系统风险与经济周期有关。此外,研究结果显示,虽然规模和动因收益率显著,但是难以在中、短期利用它们,因为在我们的样本中只有极少年份它们的数值为正且很大。     

Do alternative energy markets provide optimal alternative investment opportunities?

This paper investigates diversification opportunities for investors among different alternative energy markets. We sample six alternative energy markets namely World, Developed, Emerging, EU, BRIC and G7 with daily data ranging from January 2006 to December 2017. For estimations, we use wavelet multiple correlation and wavelet multiple cross correlation proposed by Polanco-Martínez and Fernández-Macho (2014) to find pairwise correlation at different investment horizons. Our work contributes in measuring integration level among alternative regional energy markets across different investment horizons. Our results highlight that World, Developed, Emerging, EU markets offer maximum diversification when included with either Emerging or BRIC energy markets in a portfolio. Furthermore, diversification benefits are more prominent under intra-week to monthly investment horizons for all portfolio combinations. We also rank different pairs of alternative markets based on their integration level which carry important implications for portfolio diversification and risk management.     

Time–frequency quantile dependence between Bitcoin and global equity markets

In this paper, we examine return dependence between Bitcoin and stock market returns using a novel quantile cross-spectral dependence approach. The results suggest a right-tail (high return) dependence between Bitcoin and the stock markets in the long term and that said dependence decreases significantly from yearly to monthly investment horizons. Furthermore, right-tail dependence between Bitcoin and the US stock market is the strongest compared with other stock markets. We also extract information on the time-varying and time–frequency structure of co-movements between Bitcoin and the stock markets using wavelet-coherence analysis, the results of which suggest that the co-movement between Bitcoin and the US stock market is positive, whereas, for other stock markets, it is negative at certain frequencies and time periods. Overall, the findings highlight additional risk-management capabilities of Bitcoin according to different stock markets.     

Dynamic volatility transmission and portfolio management across major cryptocurrencies: Evidence from hourly data

This study used hourly data to examine the dynamic conditional correlations and hedging strategies in the main cryptocurrency markets: Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), and Ripple (XRP). Multivariate generalized autoregressive conditional heteroskedasticity family models provided evidence of significant positive dynamic conditional correlations among these markets. A weaker conditional correlation was observed for the LCT–XRP portfolio than for the BTC–ETH portfolio, which had the highest correlation value. The dynamic correlations intensified after the cryptocurrency crisis. The results of a portfolio risk analysis suggested that investors should hold less BTC than LTC, ETH, and XRP to minimize risk while maintaining consistent expected portfolio returns. Investors should hold less BTC than the other cryptocurrencies during a crisis. In addition, the cheapest hedge strategy is to hold long BTC and short XRP regardless of the period. Holding long BTC and short LTC was found to be the most expensive hedge strategy. Finally, the study showed that an optimally weighted diversified portfolio provides the greatest reduction in risk and downside risk for ETH and LTC. For XRP, portfolio hedging is the best mechanism for reducing risk.     

The behavior of MENA oil and non-oil producing countries in international portfolio optimization

It is well documented in developed economies that portfolio investment across national borders brings benefits of increasing returns and/or reducing risk. Dividing MENA stock markets into two main groups (oil producing and non-oil producing countries), this study examines the potential role of each group in providing diversification benefits for international investors. In addition, the behavior of the long and the short-run Efficient Frontiers (EFs) constructed by each of the sub-groups and the combined MENA markets is explored. Multi-objective international portfolio models are proposed under Mean-Variance and Mean-Lower Partial Moment frameworks, and the Multiple Fitness Function Genetic Algorithm (MFFGA) is used to find the EFs of optimal portfolios. The findings indicate that the stock markets of oil producing countries can be considered as a potential avenue for international portfolio diversification for investors not only from the same countries but also from the other MENA markets. It was also found that international portfolios constructed from the combination of MENA equity markets are more stable compared to the portfolios of sub-group markets. Further, the findings indicate that the behavior of short-term EFs in the MENA region cannot be predicted by the behavior of long-term EFs.     

Impact of the COVID-19 outbreak and its related announcements on the Chinese conventional and Islamic stocks’ connectedness

In this paper, we assess the impacts of the COVID-19 counts (infected cases, deaths and recovered) and related announcements on the Islamic and conventional stocks interplays in the Chinese market. We test whether Islamic stocks are perceived as assets providing diversification benefits in time of COVID-19 pandemic. Doing so, we implement a multivariate GJR-GARCH model under dynamic conditional correlation (DCC) as well as multiple and partial wavelet coherence methods to recent Chinese daily data ranging from 2 December 2019 to 8 May 2020 and COVID-19 related announcement for the period. Our results from multivariate GJR-GARCH models reveal that COVID-19 infected cases and deaths do impact mean DCCs between Islamic and conventional stocks, number of recovered do not have such impact, while none of the above have any significant impact on the DCCs fluctuations. However, when we analyze the impact of COVID-19 related announcement on the variation of conditional correlation between two stocks (i.e. DCC volatility) our findings show that 7 out of 10 such announcements (mainly those with serious health treats or economic implications) do effect those volatilities in Chinese equity market. The empirical findings from partial and multiple wavelet coherences provide robust evidence of instability in the co-movement between Islamic and conventional indexes for different scales and over dissimilar sub-periods. Indeed, the weakening of co-movements is especially notable in the very short and short-run where operating the short-term investors. Our empirical findings offer several key propositions for policy makers and portfolio managers in China with broad implications applicable to other markets.     

Modeling dynamic conditional correlations with leverage effects and volatility spillover effects: Evidence from the Chinese and US stock markets affected by the recent trade friction

In this article, we investigate the dynamic conditional correlations (DCCs) with leverage effects and volatility spillover effects that consider time difference and long memory of returns, between the Chinese and US stock markets, in the Sino-US trade friction and previous stable periods. The widespread belief that the developed markets dominate the emerging markets in stock market interactions is challenged by our findings that both the mean and volatility spillovers are bidirectional. We do find that most of the shocks to these DCCs between the two stock markets are symmetric, and all the symmetric shocks to these DCCs are highly persistent between Shanghai’s trading return and S&P 500′s trading or overnight return, however all the shocks to these DCCs are short-lived between S&P 500′s trading return and Shanghai’s trading or overnight return. We also find clear evidence that the DCC between Shanghai’s trading return and S&P 500′s overnight return has a downward trend with a structural break, perhaps due to the “America First” policy, after which it rebounds and fluctuates sharply in the middle and later periods of trade friction. These findings have important implications for investors to pursue profits.     

Dynamic linkages and the propagation mechanism driving major international stock markets: An analysis of the pre- and post-crash eras

The stock market crash of October 1987 earmarked fears of a deep-seated financial crisis. In recent years, while there has been a number of empirical studies devoted to examinations of the number of common trends in a system of stock price indexes, only a minority has focused on what effect the crash has had on the characteristics [namely, the amount of co-movements amongst markets, their dynamic linkages, and implications for the transmission or propagation mechanism] of major stock markets. In this paper, we demonstrate how the techniques of unit root testing, cointegration, vector error-correction modelling (VECM) and forecast error variance decomposition (VDC) analysis, may be used to shed some light on these concerns in the context of six major international stock markets. Using two non-overlapping samples, we find evidence of a single cointegrating vector (or five common trends) over each of the pre- and post crash samples. A VECM is then constructed in which the temporal causal dynamics are examined, followed by decomposing the total impact of an unanticipated shock to each of the variables beyond the sample period, into proportions attributable to shocks in the other variables including its own. Results tend to broadly indicate: (1) the crash does not appear to have affected the relative leading role played by the US market over other markets; (2) the German and, British markets seem to have become more dependent on other markets over the post-crash era relative to the pre-crash; and (3) provide confirming evidence that, in general, the crash has brought about a greater interaction amongst markets, with a greater role for fluctuations in explaining shocks across markets (including that for the U.S.).     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

Conditional value-at-risk forecasts of an optimal foreign currency portfolio

This study provides daily conditional value-at-risk (C-VaR) forecasts for a foreign currency portfolio comprising the USD/EUR, USD/JPY, and USD/BRL currencies. To do so, we estimate multivariate stochastic volatility models with time-varying conditional correlations using a Bayesian Markov chain Monte Carlo algorithm. Then, given the model-specific currency return density forecasts, we make the optimal portfolio choice by minimizing the C-VaR through numerical optimization. According to out-of-sample experiment, including emerging markets into the currency basket is essential for downside risk management, and considering model uncertainty as well as the parameter uncertainty can improve the portfolio performance.     

Measuring real–financial connectedness in the U.S. economy

We analyze the connectedness between the real and the financial sectors of the U.S. economy. Using the weekly ADS index of the Philadelphia Fed (the widely used business conditions indicator) to represent the real side, we find that during times of financial distress and business cycle turning points, the direction of connectedness runs from the real sector to financial markets. The ADS index is derived from a model containing a measure of term structure along with real variables. Therefore, it might not be the best representative of the real activity used in the connectedness analysis. As an alternative, we derive a real activity index (RAI) from a dynamic factor model of the real sector variables only. The behavior of RAI over time is quite similar to that of the ADS index. When we include RAI to represent the real side, connectedness from the real side to financial markets weakens substantially, while the connectedness from financial markets to the real side becomes more pronounced.     

Market integration between conventional and Islamic stock prices

The paper assesses the market integration between conventional and Islamic stock prices from the long- and short-run perspectives for France, Indonesia, the UK and the US from September 8, 2008 to September 6, 2013 using various econometric approaches. The results show long-run relationships for all countries, except for the UK where there is no cointegration between conventional and Islamic stock prices. These findings suggest that the Islamic finance industry in the considered economies (except the UK) does not seem to be compliant to Islamic law's maxims, which hinders portfolio managers and market participants to benefit from the opportunities of international diversification and hedging effectiveness. From the correlation perspective, there is evidence of weak linkages between the Indonesian market and the developed markets for both conventional and Islamic stock prices, thus suggesting that investors can diversify their portfolios at the international level to minimize risk. However, there is high connection between the developed markets for both conventional and Islamic indexes. In addition, for each economy, the Islamic index is found to be strongly linked with its conventional counterpart. The structural change analysis reveals common break dates for several cross correlations, thus reflecting the similar time-paths of the interactions between markets. The presence of breaks in the inter-market linkages has important implications for international investors as regards portfolio diversification benefits and for financial policy makers regarding contagion risks and market policies.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons

This study investigates the role of hedging and portfolio design among stocks, exchange rates, and gold in small open economies (SOEs) from 4 January 2000 to 31 March 2020. We adopt the trivariate dynamic conditional correlation-fractionally integrated asymmetric power ARCH model and unconditional quantile regression model, and our findings show that the hedging role of the U.S. dollar (USD) and gold against stocks differs under regular and extreme market conditions. The USD can act as a powerful hedge asset for stocks in regular market periods. Moreover, during the global financial crisis and COVID-19 outbreak, the safe-haven effect of gold becomes stronger for almost all stocks, whereas the USD can serve as a strong safe haven against stock markets of Korea, Taiwan, and Singapore when stock returns are extremely low. In terms of portfolio designing, we find that adding the USD and gold to portfolios improves their hedging effectiveness, and the optimally weighted stock-USD-gold portfolio is the best portfolio strategy, irrespective of referring to return or risk.