Implications For Portfolio Management Research Articles

Risk dynamics in energy transition: Evaluating downside risks and interconnectedness in fossil fuel and renewable energy markets

Amidst rising concerns over climate change, the global shift from oil-powered vehicles to lithium-powered electric vehicles marks a critical pivot in the energy sector. This transition holds profound implications for the traditional dominance of oil in the energy market. This study aims to investigate the risk dynamics between the fossil fuel sector, represented by the crude oil, and the renewable energy sector, symbolized by lithium, focusing on the risk spillover and interconnectedness. The study employs a two-step approach that combines the conditional autoregressive value-at-risk (CAViaR) and time-varying parameters vector-autoregression (TVP-VAR). The study spans from January 2011 to August 2023, focusing on extreme market events like the COVID-19 pandemic and the Russia-Ukraine conflict. Findings reveal a strong tail-risk connectedness between the lithium stocks of the same country, and during extreme market events such as the COVID-19 pandemic and the Russia-Ukraine conflict, there is a strong transmission of tail risk across the lithium stocks of different countries. Moreover, a strong bidirectional tail-risk connectedness is observed between crude oil and lithium stocks. The study has important implications for portfolio managers, fund managers and investors with respect to portfolio optimization and asset allocation. Also, the findings have important implications for financial risk management with respect to energy transition from fossil fuels to renewable energy.

Extreme downside risk connectedness and portfolio hedging among the G10 currencies

This study investigates the frequency connectedness among foreign exchange markets of G10 countries, focusing on tail risk and its implications for portfolio management. To do so, we use a novel framework that combines the Conditional Autoregressive Value-at-Risk (CAViaR) model with the novel time-varying frequency and quantile connectedness method developed by Chatziantoniou et al. (2022) based on Baruník and Křehlík (2018) and Ando et al. (2018) approach. A key value of this paper to the literature is the provision of fresh empirical evidence on the extreme downside linkages among the markets examined. From the average connectedness measures, the top shock transmitters within the network were EUR, NOK, AUD, SEK, and NZD, while the main shock receivers emerged to be JPY and CHF, followed by CAD and GBP. We note that events in the major funding markets (the Eurozone, Japan) have a higher impact on the participants in these same markets than in relatively small markets (New Zealand, Norway). From the dynamic connectedness results, the magnitude of connectedness for the entire sample period increased during the COVID-19 era, compared to the magnitude before the COVID-19 outbreak. The cumulative spillover also reveals that USDNOK is the vastest net transmitter of spillovers to other markets, including SEK, CHF, and AUD. However, the EUR is the largest net beneficiary followed by JPY and CAD. Findings from the time-varying extreme downside analysis suggest that throughout the period, SEK and NOK are the other currencies' strongest and most frequent net spillover shock emitters for the short-, medium-, and long-term dynamics. Currency portfolio implications are discussed.

The Indirect Diversification Benefits of Investing in Japanese Firms: An Alternative Perspective

AbstractThis paper examines the role of firm-level multinationality in equity portfolio diversification for Japanese firms from 1998 to 2015. We use a unique multinationality dataset for constituents of the Nikkei 225 based on two measures of sales and subsidiaries. We employ an extended version of the traditional Capital Asset Pricing Model (CAPM) to analyse the exposure of firm returns to various geographical regions. There is evidence that firms are not influenced by the geographic regions where they report operations. The results also indicate that there are benefits from investing in Japanese multinationals but these benefits do not increase with increasing multinationality. A new category of firms is identified that may be beneficial to investors—firms that are influenced by a geographical region where they do not report sales or subsidiaries. This finding has far reaching implications for portfolio management. Investors must do more than analyse the international location of firm operations. They must analyse the geographical influences on firm returns. Existing studies fail to distinguish between these two criteria, assuming them to be the same. We find evidence to the contrary.

Intention to Use Robo Advisory Services in Malaysia

In Malaysia, robo-advisory services have become increasingly popular in the financial industry. This study examines the factors that determine the intention to use robo-advisory services in Malaysia, including the performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and trust. The target respondents of this study are individuals from the M40 income group in Malaysia. A total of 400 responses was collected and analyzed through Partial Least Squares Structural Equation Modelling (PLS-SEM) using SmartPLS software. The findings demonstrated that performance expectancy, social influence, hedonic motivation, price value, and trust are significant in affecting the behavioral intention to use robo-advisory services in Malaysia, except for effort expectancy and facilitating conditions, which showed an insignificant result. Moreover, this study would contribute to the understanding of the emergence of robo-advisory services in Malaysia and provide practical and theoretical implications for portfolio managers, robo-advisory firms, and researchers to aid in the future development of robo-advisory services and the financial industry in Malaysia.

From the pandemic to the Russia–Ukraine crisis: Dynamic behavior of connectedness between financial markets and implications for portfolio management

This study assesses the time-varying connectedness and portfolio implications among equity markets, commodities, and cryptocurrencies. To this end, we employ the DCC-GARCH model and time-frequency framework on daily data. The sample covers a period spanning from January 2018 to October 2023. The results confirm the existence of financial contagion evidence during the pandemic outbreak and the Russian invasion of Ukraine among the equity markets and alternative assets. Furthermore, from the perspective of portfolio management, we find that gold can be a suitable asset for diversifying specific risks, followed by soft commodities and Bitcoin during tranquil periods. We demonstrate that gold serves as a good long-term safe investment, whereas gold and Bitcoin lose their safe-haven properties in the short and mid term. Conversely, oil is the least effective diversification and safe-haven asset for equities. However, the hedging analysis indicates an increase in the hedge ratio during crisis periods across all pairs. The hedging performance of each asset is modest and varies due to critical market circumstances during the pandemic and the war. These findings suggest that investors should frequently rebalance the portfolio structure rather than adopting a static method such as buy and hold.

Multi-scale dependence and risk contagion among international financial markets based on VMD-Vine copula-CoVaR

ABSTRACT Considering the frequency domain and nonlinear characteristics of financial risks, we propose a VMD-Vine copula-CoVaR framework to study the dependence structures and risk spillovers among international financial markets at different time scales. Furthermore, a mean-variance optimization technique has been applied to evaluate the performance of the optimal cross-market portfolios. The empirical results show that: (1) The R-Vine copula is superior to the C- and D-Vines; (2) Compared with the Asian stock markets, the European stock markets are more correlated with each other. The correlations between the markets at the long-term scale are greater than those at the short- and medium-term ones; (3) The optimal pair copulas are combined with the CoVaR to estimate the systemic spillover risks among the markets. The downside and upside spillover risks across the markets are not always symmetric. Moreover, the ΔCoVaRs at the medium-term scale are the highest and the lowest at the short-term one; and (4) The optimal cross-market portfolio constructed by our framework perform better than the benchmarks by annualized return, Sharpe ratio, and maximal drawdown. The findings have direct implications for portfolio managers and investors to prevent extreme risks and take better international investment decisions based on the knowledge of optimum portfolio.

Dynamic correlations between Bitcoin, carbon emission, oil and gold markets: New implications for portfolio management

<abstract> <p>In this paper, we aim to uncover the dynamic spillover effects of Bitcoin environmental attention (EBEA) on major asset classes: Carbon emission, crude oil and gold futures, and analyze whether the integration of Bitcoin into portfolio allocation performance. In this study, we document the properties of futures assets and empirically investigate their dynamic correlation between Bitcoin, carbon emission, oil and gold futures. Overall, it is evident that the volatility of Bitcoin, as well as other prominent returns, exhibit an asymmetric response to good and bad news. Additionally, we evaluate the hedge potential benefits of these emerging futures assets for market participants. The evidence supports the idea that the leading cryptocurrency-Bitcoin can be a suitable hedge instrument after the COVID-19 pandemic outbreak. More importantly, our analysis of the portfolio's performance shows that carbon emission futures are diversification benefit products in most of the considered cases. Notably, incorporating carbon futures into portfolios may attract new investors to carbon markets for double goals of risk diversification. These findings also provide insightful evidence to investors, crypto traders, and portfolio managers in terms of hedging strategy, diversification and risk aversion <sup>[<xref ref-type="bibr" rid="b19">19</xref>,<xref ref-type="bibr" rid="b20">20</xref>,<xref ref-type="bibr" rid="b21">21</xref>,<xref ref-type="bibr" rid="b22">22</xref>,<xref ref-type="bibr" rid="b23">23</xref>,<xref ref-type="bibr" rid="b24">24</xref>,<xref ref-type="bibr" rid="b25">25</xref>]</sup>.</p> </abstract>

Another look at the asymmetric relationship between stock returns and trading volume: evidence from the Markov-switching model

PurposeThe purpose of this paper is to bridge the gap between the existing theoretical and empirical studies by examining the asymmetric return–volume relationship. Indeed, the authors aim to shed light on the return–volume linkages for French-listed small and medium-sized enterprises (SMEs) compared to blue chips across different market regimes.Design/methodology/approachThis study includes both large capitalizations included in the CAC 40 index and listed SMEs included in the Euronext Growth All Share index. The Markov-switching (MS) approach is applied to understand the asymmetric relationship between trading volume and stock returns. The study investigates also the causal impact between stock returns and trading volume using regime-dependent Granger causality tests.FindingsAsymmetric contemporaneous and lagged relationships between stock returns and trading volume are found for both large capitalizations and listed SMEs. However, the causality investigation reveals some differences between large capitalizations and SMEs. Indeed, causal relationships depend on market conditions and the size of the market.Research limitations/implicationsThis paper explains the asymmetric return–volume relationship for both large capitalizations and listed SMEs by incorporating several psychological biases, such as the disposition effect, investor overconfidence and self-attribution bias. Future research needs to deepen the analysis especially for SMEs as most of the literature focuses on large capitalizations.Practical implicationsThis empirical study has fundamental implications for portfolio management. The findings provide a deeper understanding of how trading activity impact current returns and vice versa. The authors’ results constitute an important input to build and control trading strategies.Originality/valueThis paper fills the literature gap on the asymmetric return–volume relationship across different regimes. To the best of the authors’ knowledge, the present study is the first empirical attempt to test the asymmetric return–volume relationship for listed SMEs by using an accurate MS framework.

Connectivity and spillover during crises: Highlighting the prominent and growing role of green energy

How influential are green energy instruments? We examine how green- and carbon-energy assets differ regarding transmitting and receiving shocks between normal versus crises periods. Crises include the global financial crisis and Euro debt crisis, two waves of COVID-19, and the ongoing Russia-Ukrainian war. Our empirical illustration is based on volatility impulse function (VIRF) for dynamic conditional correlation–generalised autoregressive conditional heteroskedasticity (DCC-GARCH) method using daily data from January 03, 2007–March 31, 2023, of several green and brown energy instruments and market and energy controls, we evidence asymmetric connectedness that increases during crises. For specific green instruments, volatility transmissions can be transmitting or receiving. However, green instruments stand out overall as prominent transmitters, while brown energy instruments are prominent receivers. Results are consistent with green energy vehicles impacted by macroeconomic and market states and reflecting this to investors. Results are also consistent with green and brown interconnectivity. Further network analysis provides robustness to our study results and suggests this role is evolving. The study results are significant for policy intervention during the transition to alternative energy sectors and for risk and portfolio management implications.

Systemic Risk in the Global Energy Sector: Structure, Determinants and Portfolio Management Implications

We examine the dynamics of tail dependence across returns of 105 global energy firms from 26 countries covering the regions of America, Asia Pacific and Europe. A partial correlation-based approach is used to quantify the dependence structure and level of systemic risk under relatively stable and extremely bearish and bullish market conditions. The dependence network of energy stock returns is constructed based on the novel triangulated maximally filtered graph (TMFG). The results reveal a high degree of tail dependence and role played by geographical proximity. The strongest links are found under extreme bearish market conditions. American and European energy firms are more interconnected and contribute more to systemic risk than Asian-Pacific companies. The dependence intensifies during periods of market turmoil, especially during the COVID-19 pandemic. A higher instability in the dependence structure is observed during extremely bearish market circumstances. A simple portfolio trading strategy based on the dependence ranking of energy firms outperforms a naïve equally-weighted buy-and-hold portfolio strategy.

The Dynamic Return and Volatility Spillovers among Size-Based Stock Portfolios in the Saudi Market and Their Portfolio Management Implications during Different Crises

This study contributes to the ongoing debate on the size effect and size-based investment styles by investigating the return and volatility spillovers and time-varying conditional correlations among Saudi large-, mid-, and small-cap indices. To this end, we utilize the weekly returns on the MSCI Saudi large-, mid-, and small-cap indices over a long sample period, spanning several crises. The econometric approach that we use is a VAR-asymmetric BEKK-GARCH model which accounts for structural breaks. On the basis of the VAR-asymmetric BEKK-GARCH model estimation results, we calculate portfolio weights and hedge ratios, and discuss their risk management implications. The empirical results confirm the presence of unilateral return spillovers running from mid- to small-cap stocks, while multilateral volatility spillovers are documented, albeit substantially weakened when accounting for structural breaks. The time-varying conditional correlations display clear spikes around crises, which translate to higher hedge ratios, increasing the cost of hedging during turbulent times. The optimal portfolio weights suggest that investors generally overweight large caps in their portfolios during uncertain times to minimize risk without lowering expected returns. The main takeaway from our results is that passively confining fund managers to a particular size category regardless of the prevailing market conditions may lead to suboptimal performance.

Artificial intelligence-based tokens: Fresh evidence of connectedness with artificial intelligence-based equities

The main focus of this research is to investigate the potential spillover effects between AI-based stocks and tokens by using the quantile connectedness approach developed by Ando et al. (2022). The study aims to investigate both static and dynamic spillovers at the lower and upper tails of the return distribution. AI-based stocks and tokens may have relatively low levels of connectedness, which also varies over time and increases during periods of economic turbulence. In addition, in line with previous work analysing other financial markets and assets, this research finds that the system is more sensitive to the tails of the distribution (i.e., the lower and upper quantiles) than to the median (Q = 0.50). This finding is consistent with expectations, and measures of dynamic connectedness change over time, with the intensity of spillovers increasing at the extremes of the distribution. These results have practical implications for portfolio managers, as they can use the results to adjust their investment portfolios according to the evolution of the dynamic spillovers observed in the system. Overall, this study sheds light on the potential tail spillovers in the AI-based stock and token market and provides valuable insights for investment decisions.

Subsample analysis of stock market – cryptocurrency returns tail dependence: A copula approach for the tails

This paper describes the extremal and tail dependence between G7 stock market returns (USA, Canada, UK, Japan, Germany, France, Italy) and cryptocurrency returns (Bitcoin, Ethereum, Dash, Monero, Ripple) on the basis of the bivariate extremal dependence model (Padoan and Stupfler, 2022) and the bivariate test for equality of tail copulas (Can et al., 2023). Over a daily data period from January 1, 2016 through January 5, 2023, the findings reveal significant differences in tail risk between the categories of G7 stock market returns and cryptocurrency returns, highlighting the need to find an appropriate asset to hedge individual financial asset tail risks. The results also demonstrate a time-invariant tail dependence between G7 stock market returns and cryptocurrency returns, as the Wald test supports the null of an equal tail dependence structure between stock market and cryptocurrency returns during both calm and crises times. The finding offer important policy implications for portfolio managers and investors.

Green financing for renewable energy development: Driving the attainment of zero-emission targets

The study focuses on China's efforts to achieve net-zero carbon emissions targets and examines how the country's use of renewable energy and financing has mitigated greenhouse gas emissions. To understand the impact of these efforts, the study employs panel regression models and analyses panel data from 1990 to 2020. The study finds that even a minimally significant rise in greenhouse gas emissions elevates the development of carbon emissions. However, increasing funding for net-zero emissions encourages the use of renewable energy and lowers greenhouse gas emissions. The use of renewable energy is also found to lessen the impact of funding for climate-related greenhouse gas emissions. The research underscores the importance of renewable energy and green finance projects in promoting consistent growth and sustainable development. The findings have implications for portfolio managers, individual investors, and environmental law professionals. Moreover, the study provides insights into the implementation of COP26 guidelines and goals.

Time-Frequency Volatility Spillovers among Major International Financial Markets: Perspective from Global Extreme Events

In the context of the gradual intensification of the Russia-Ukraine conflict and the continuous spread of the COVID-19 pandemic, this paper concentrates on the impact of global extreme events such as the COVID-19 pandemic and the Russia-Ukraine conflict on the risk spillovers among major international financial markets. First, to measure the impact of the extreme events the on the volatility spillovers among major international financial markets in the time-frequency domain, we combine the TVP-VAR-based connectedness method and BK frequency connectedness approach and focus on the total, directional, and net volatility spillovers. Second, the network visualization method is applied to outline the structural change in the risk contagion, paths, and roles among international financial markets during different periods of global extreme events. The empirical results indicate that the risk spillovers (total, directional, and net spillovers) among international financial markets and the roles played by each market in the process of risk contagion have changed significantly in different periods of global extreme events. Furthermore, volatility spillovers among international financial markets are driven mainly by the high-frequency component (short-term spillovers) during the full sample time. However, the effects of the extreme events also persist in the medium and long terms. Our findings may help understand the dynamics among international financial markets under extreme shocks and provide significant implications for portfolio managers, investors, and government agencies in times of extreme events.

Investigating volatility spillover of energy commodities in the context of the Chinese and European stock markets

This paper investigates spillover from energy commodities to Shanghai stock exchange and European Stock market, and identifies possible risks transmission and portfolio diversification opportunities. The study is conducted on daily spot prices of carbon (CO2) emission, natural gas and crude oil from 16 December 2010 to 29 December 2022, employing Granger causality test, dynamic conditional correlation (DCC), Diebold-Yilmaz (2012) and Barunik-Krehlic (2017) models. Results identify higher volatility and imply greater connectedness in the longer run. Additionally, natural gas is witnessed as the highest contributor of the shocks and crude oil as the highest receiver of the shocks from the network connection. Further results suggest for investment in energy commodities in shorter run rather than long run for efficient portfolio diversification. Results from this study are expected to have practical implications for portfolio managers, investors, and market regulators, given the suggestion of this study to incorporate energy stocks for efficient diversification of risk.

Dynamic effects of geopolitical risks and infectious diseases on real estate markets

PurposeGeopolitical risks (GPR) and increase in equity market volatility due to health pandemics have great implications on assets prices around the world. Many empirical studies have focused on the effects of these risks on different financial assets. The purpose of this paper is to contribute to this related literature by examining the dynamic effects of GPRs and infectious diseases–induced equity market volatility on regional and global house price indexes.Design/methodology/approachThis paper explores the asymmetric effects of infectious diseases and GPRs on house prices across different market conditions using the quantile regression approach. This technique enables us to examine the nonlinear asymmetric effects of GPRs and infectious diseases on both global and regional house price indexes using daily data from January 1, 2011, to June 3, 2022. It focuses on both the effects of a composite measure of GPR as well as the disaggregated effects of threats and acts (war) on the real estate markets under different market conditions.FindingsThe main findings of this study demonstrates that the effects of geopolitical and infectious diseases–related risks vary differently across regional real estate markets and the nature of the GPR. In particular, the effects of geopolitical threats are stronger than those of geopolitical acts, especially for the European, Asia-Pacific and North American regions during bullish market periods. Except for the effects of geopolitical threats during real estate market downturns, the African real estate market appears to be insulated from the effects of GPRs across all market conditions. Also, the authors show that infectious diseases increase losses in real estate investments when the market condition is bearish for all markets and could extend toward the normal market period for the North American, Asia-Pacific and European markets. However, across all the market conditions, the effects of the composite index of GPRs are not significant for the Asia-Pacific and European regional markets. Results are mixed for the remaining markets, especially for the global market. Whereas during bearish market periods, the effect is positive, it becomes negative when the market condition become normal and insignificant when it becomes bullish. For the North American and African regional markets, the effect is positive under the bearish market state.Originality/valueIncrease in equity market volatility due to infectious diseases as well as conflicts and tensions among major powers, including potential risks of financial instability, all lead to significant increase in shocks to financial markets. To the best of the authors’ knowledge, this is the first study to analyze the asymmetric and comparative effects of GPRs and infectious diseases–related equity market volatility on real estate investments across different regions and market conditions. Because of the complexity of these risks and policy shifts, and the characteristics and heterogeneity of different regional financial markets, the impacts of shock from these risks are intuitively diverse, with practical implications for portfolio management.

Spillovers between positively and negatively affected service sectors from the COVID-19 health crisis: Implications for portfolio management

This study empirically investigates and contributes new evidence to the ongoing topic of potential volatility spillover, efficient portfolio management, and hedging strategies. We investigate the connectedness between the travel and leisure sector (which was negatively affected by the COVID-19 pandemic) and healthcare, technology, and telecommunications sectors (which were positively impacted by the pandemic). We selected these four service sectors because they have been impacted by the pandemic and are also crucial for the world's economy. We separately perform a connectedness analysis for four regions: Europe, Eastern Europe, Asia-Pacific, and North America. The main findings indicate a rise in return and volatility spillovers during the COVID-19 outbreak in the selected sectors. Healthcare, telecommunications, and technology sectors are major transmitters of volatility shocks to the travel and leisure sector during the crisis. The portfolio analysis shows that investors should include healthcare, telecommunications, and technology sectors in their equity portfolios to reduce investment risk and protect expected returns during the pandemic. Hedge ratios vary over crisis and non-crisis periods, highlighting the option of adjusting hedging strategies during turbulent and stable periods. The study also evaluates efficient portfolio management strategies shaped during the COVID-19 pandemic using the estimated results of the DCC-GARCH approach.

Searching hedging instruments against diverse global risks and uncertainties

We evaluate the influence of five major risk and uncertainty factors on four asset classes. Our time-varying findings suggest that each asset hedges only a particular uncertainty factor, whereas gold does more than one factor, especially during COVID-19. Our frequency-based quantile regression (QR) results show that in the raw frequency, gold and Islamic stock can better hedge various uncertainty factors than Bitcoin and crude oil, depending on the market conditions. Additionally, using the frequency bands (e.g., short, medium, and long term) data, we further notice that, depending on the market circumstances and investment horizons, gold and Islamic stock returns are still better hedges for the various risks and uncertainties than Bitcoin and crude oil returns. Our findings have crucial risk and portfolio management implications for investors, portfolio managers, and policymakers.

Quantile-based spillover connectedness among stochastic volatilities of ESG equities, Islamic and conventional stocks with implications for portfolio management

PurposeThis study aims to investigate the relationship between stock markets, environmental, social and governance (ESG) factors and Shariah-compliant in an integrated framework.Design/methodology/approachThe authors employ the multivariate factor stochastic volatility (mvFSV) framework to extract the volatility of the different sectoral indices. Based on this evidence, the authors employ the quantile vector autoregressive (QVAR) approach to examine the dynamic spillover connectedness among the aforementioned indices.FindingsThe study emphasizes the following major findings: (1) significant time-varying spillover connectedness across quantiles, (2) bidirectional and asymmetric spillover effect among the ESG index and the other sectoral indices, (3) the strength of spillover connectedness is time-varying across quantiles, (4) based on the perspective of portfolio optimization, ESG market is a significant strong forecasting contributor to conventional and Shariah-compliant markets, (5) overall, the findings point out serious quantile pass-through effect among ESG index and the other sectoral indices during the COVID-19 health crisis.Originality/valueThis study extends the previous literature in the following ways. First, to the best of the researchers’ knowledge, none of the existing studies have investigated the relationship between stock markets, ESG factors and Shariah-compliant in an integrated framework. Second, this study extends the previous scholarships by applying the mvFSV. Third, the authors propose a new rolling version to estimate dynamic spillovers, namely the rolling-window quantile VAR method. This approach provides a great advantage in computing the dynamics of return and variance spillover between variables in terms not only of the overall factor but also of the net (pairwise) aspect.