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We show that a common component governs volatility dynamics across a wide range of traded equity factors. This "common factor volatility" (CFV) exists even among orthogonal factors. CFV occurs in both cash-flow and discount-rate components of factor returns and derives from market responses to fundamental news rather than underlying commonality in news volatility. Incorporating CFV improves factor volatility forecasts relative to models that include only own-factor volatility. CFV allows us to characterize stochastic discount factor (SDF) volatility dynamics in a very general sense and we show that many popular models imply SDFs with time-varying volatility that correlates strongly with CFV. [ABSTRACT FROM AUTHOR]

Preferred shares have high, fixed-dividend rates, often comparable to investment-grade bonds but have become a forgotten asset class for most investors. Preferred shares witnessed a surge of attention during the financial crisis of 2008. Because of their high and steady dividend rates, they should be considered as an asset class for portfolios that seek income. The current analysis shows that when added to a diversified portfolio, preferred shares can increase returns and reduce variance over standard equity/ fixed-income portfolios, including those that include some exposure to real estate investment trusts (REITs) for income production. [ABSTRACT FROM AUTHOR]

An enduring trait of modern corporations is their propensity to diversify into multiple lines of business. Penrosian theories conceptualize diversification as a strategy to exploit a firm's fungible, yet "untradeable," resources and point to the redeployment of technological know-how as an important driver thereof. However, less understood are the characteristics of technological assets that underlie firms' diversification decisions and the impact that diversification has on firms' subsequent development of technologies. In this paper, we expand the existing theories in two ways. First, we argue that central to understanding firms' diversification decisions is a distinction between their technological assets that are applicable to many markets and ones that are useful in only a limited number of contexts. To this end, we develop a novel way to characterize technologies along a continuum from highly general-purpose to highly market-specific. Second, we explore empirically the idea that diversification is an adaptive learning process involving both the exploitation of existing capabilities and the creation of novel ones. Using data on three decades of patenting and diversification histories of 28,376 firms, we find that (i) a firm's possession of general-purpose technological assets is positively associated with its decision to diversify and (II) firms that enter a new industry through diversification develop technologies that are specialized to the target industry. Our findings have implications for understanding firm growth, diversification, and evolution. [ABSTRACT FROM AUTHOR]

Purpose: This paper studies diversification and value in the investment portfolios of (non-listed) Real Estate Investment Funds (REIFs) exploring how the value of diversification is captured by the market and by investors (beyond reported valuations). Design/methodology/approach: We apply the Herfindahl-Hirschman Index (HHI) to study the level of concentration versus diversification in the investment portfolios of REIFs (both in terms of segment and geographical diversification). We use a dataset from INREV with data from 62 investment portfolios, with an average of 86 REIFs per portfolio for the period of 2008–2020 (to study segment diversification). We use a second dataset from INREV with data from 30 investment portfolios with an average of 79 REIFs per portfolio for the period of 2005–2020 (to study geographical diversification). We employ a cluster analysis approach to identify common features among the investment funds. Findings: We conclude that (segment diversified) portfolios with higher degrees of leverage exhibit higher income yields, albeit diversification is captured indirectly through asset choices – more diversified portfolios tend to exhibit a stronger risk and return relationship. Also, geographical diversification creates value (more significantly by for the correct combination of countries carefully choosing what different geographies to group in the diversified portfolio). Research limitations/implications: One limitation of our study is that our portfolios are funds of funds, since the available data could not reach the asset detail, but we believe this does not compromise our results. Practical implications: Diversification leads to higher risk-adjusted returns which suggests that properties may be undervalued (market value) in the framework of the Gordon Model, contrary to expectations (regarding investment value). Originality/value: Investors capture the value of diversification differently, suggesting a gap between market value and investment value that can be explored. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to scrutinize the safe haven benefits of 13 individual commodities for the USA and Chinese equity sectors during the financial turmoil period. Therefore, sectoral investors in the USA and China could invest in those specific commodities that provide stable returns during the health crisis and financial turmoil periods. Design/methodology/approach: The daily data spans from February 1, 2015, to July 28, 2022. The present study applies several different approaches to analyzing the data set. The author apply the cross-quantilogram (C.Q) methodology to capture the lead-lag bivariate quantile interdependence between two stationary time series variables during the bearish, bullish and normal periods. Then the study used the hedging effectiveness (HE) and conditional diversification benefits (CDB) approaches to capture the hedging and diversification benefits of commodity classes and individual commodities. Findings: The noteworthy findings of the quantilogram methodology reveal that livestock and agriculture commodities serve as better refuges as compared to the precious metals and energy index in both countries. On average, precious metals failed to serve as safe haven investments for the USA and Chinese equity market sectors. All energy commodities except soybean oil had strong comovements with China and the US equity sectors during bearish, bullish and normal periods. Lean hogs, fiddler cattle and live cattle are perfect hedging assets for both countries due to the presence of blue color at normal and bullish periods in all C.Q heat-maps. The HE table depicts that commodity indices and individual commodities failed to serve as hedging assets for the Chinese equity sectors. But commodities are semistrong hedging assets for the US equity sectors and the S&P 500 due to the average HE values being 0.7 and above. The CDB values depict that precious metals provide diversification benefits in both equity markets. Practical implications: The present study results have important implications for equity sector investors of the USA and China in suggesting particular commodity during the financial turmoil period. During the bearish market condition, risk averse equity sector investors can invest in livestock commodities and agriculture commodities, due to their relatively stable returns. In addition, policymakers can use the analysis insights to formulate policy tools and monitoring mechanisms, effectively mitigating the unfavorable effects arising from asymmetric dependence between commodities and equity sectors during the upper tail, middle and lower tail. Policymakers can suggest equity investors to invest in which commodity during extreme conditions. Originality/value: The current study has the following points of originality. First, to the best of the author's knowledge, this is the first study to investigate the individual commodities' roles as safe havens taken from all four major commodity classes. More importantly, it is also noticeable that the safe haven abilities of commodities are usually tested for the stock market, but the equity sectors are ignored. Therefore, the present study used both stock market and sectoral indices data. [ABSTRACT FROM AUTHOR]

Risk parity portfolio optimization, using expected shortfall as the risk measure, is investigated when asset returns are fat‐tailed and heteroscedastic with regime switching dynamic correlations. The conditional return distribution is modeled by an elliptical multi‐variate generalized hyperbolic distribution, allowing for fast parameter estimation via an expectation‐maximization algorithm, and a semi‐closed form of the risk contributions. A new method for efficient computation of non‐Gaussian risk parity weights sidesteps the need for numerical simulations or Cornish–Fisher‐type approximations. Accounting for fat‐tailed returns, the risk parity allocation is less sensitive to volatility shocks, thereby generating lower portfolio turnover, in particular during market turmoils such as the global financial crisis or the COVID shock. While risk parity portfolios are rather robust to the misuse of the Gaussian distribution, a sophisticated time series model can improve risk‐adjusted returns, strongly reduces drawdowns during periods of market stress and enables to use a holistic risk model for portfolio and risk management. [ABSTRACT FROM AUTHOR]

This article explores the cointegration, co-movement, and causality relationships amongst the equity, debt, and cryptocurrency markets to determine the risk diversification possibilities of an investment portfolio. We employ daily data extracted from the Bloomberg data terminal from 2 August 2017 to 2 June 2022 to investigate the short- and long-run relationships between these markets. Indices from the U.S.A., Europe, China, Australia, and Japan are selected as the proxies for the analysis. The autoregressive distributed lag (ARDL) model, followed by unit root testing in the presence of structural breaks, indicates no long-run relationship among six financial variables and the cryptocurrency market. Although the Toda Yamamoto causality test does reveal unidirectional causality running from European and Chinese markets to the cryptocurrency market, we find no evidence to prove the existence of any bidirectional causality between markets. Furthermore, we use the R-squared metrics to analyse the market behaviour and co-movement between the cryptocurrency market and other financial markets. The test findings exhibit a lower level of co-movement behaviour. Our overall results suggest potential portfolio diversification possibilities between cryptocurrency and financial markets based on Modern Portfolio Theory (MPT). [ABSTRACT FROM AUTHOR]

Managing economic risk is a challenging endeavor for fishers. One of the ways to mitigate such risk is through income diversification spanning even beyond fishing activities. However, the role of non-fishing income on risk management has been poorly understood. Here we investigate the relationship between fishing risk levels and secondary incomes by analyzing risk levels of fishers' incomes from fishing, non-fishing, and partner income sources for Swedish fisheries from 2004 to 2015. We find that fishers with a balanced share of fishing and secondary incomes have lower risk levels than fishers who primarily rely on fishing income. Both non-fishing income and partner income reduce risk levels. [ABSTRACT FROM AUTHOR]

This paper investigates the role of local human capital in facilitating the export diversification improvement effect of foreign direct investment (FDI) in African countries. To this end, we use a panel smooth transition regression (PSTR) model which is able to deal with the heterogeneity issue associated with the cross-country data. Based on a sample of 30 African countries over the period 1996–2019, the results show that there is a minimum threshold of human capital beyond which the export diversification enhancing effect of FDI is unlocked in African countries. In other words, only countries located above a certain threshold of human capital benefit from the positive effect of FDI on export diversification. These results suggest that policymakers in African countries should focus on improving the conditions for acquiring local human capital (education and health) in order to extract economic gains from FDI. [ABSTRACT FROM AUTHOR]

The growing prominence of generating a well-diversified portfolio by holding securities from multi-asset markets has, over the years, drawn criticism. Various financial market events have caused asset markets to co-move, especially in emerging markets, which reduces portfolio diversification and enhances return losses. Consequently, this study examines the time–frequency co-movement of multi-asset classes in South Africa by using the Multivariate Generalized Autoregressive Conditional Heteroscedastic–Asymmetrical Dynamic Conditional Correlation (MGARCH-DCC) model, Maximal Overlap Discrete Wavelet Transformation (MODWT), and the Continuous Wavelet Transform (WTC) for the period 2007 to 2024. The findings demonstrate that the equity–bond, equity–property, equity–gold, bond–property, bond–gold, and property–gold markets depict asymmetrical time-varying correlations. Moreover, correlation in these asset pairs varies at investment periods (short-term, medium-term, and long-term), with historical events such as the 2007/2008 Global Financial Crisis (GFC) and the COVID-19 pandemic causing these asset pairs to co-move at different investment periods, which reduces diversification properties. The findings suggest that South African multi-asset markets co-move, affecting the diversification properties of holding multi-asset classes in a portfolio at different investment periods. Consequently, investors should consider the holding periods of each asset market pair in a portfolio as they dictate the level of portfolio diversification. Investors should also remember that there are lead–lag relationships and risk transmission between asset market pairs, enhancing portfolio volatility. This study assists investors in making more informed investment decisions and identifying optimal entry or exit points within South African multi-asset markets. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: The purpose of this study was to explore the motives (especially the agency motives) for corporate diversification from the perspective of corporate executives who make such strategic decisions and manage the diversified firms daily. Design/methodology/approach: A qualitative research approach was adopted, and 12 chief executive officers (CEOs) of diversified firms in Nigeria were interviewed for their perspectives on the motives for corporate diversification. Findings: Stewardship motives – diversification to use excess capacities in assets and resources to exploit opportunities in the market and defend against adverse environmental developments – were the most cited reasons for diversification. The relevant agency problem related to corporate diversification motive in Nigeria is the principal–principal (majority shareholder-minority shareholder) one. CEOs with substantial holdings in their firms indicated that they use diversification to reduce their investment risk and retain control of their portfolio. Practical implications: The findings suggest that in corporate environments such as Nigeria that feature blockholding prominently, the corporate strategy-related agency problem that policymakers should pay greater attention to is the principal–principal conflict rather than the traditional agent–principal problem that has influenced corporate governance over the years. There is also a need to revise the dominant view that diversification is a value-destroying strategy motivated by the self-seeking behavior of managers who have little or no shares in the companies they manage. Originality/value: The few studies on motives for corporate diversification that incorporated the perspectives of corporate executives did not address the agency motives of diversification. To the best of the authors' knowledge, this is the first study that has done so. [ABSTRACT FROM AUTHOR]

This study evaluates the links between representative indices of companies with high environmental performance and the propensity of such indices to economic and financial shocks. Five indices, representing environmental segments and four global macroeconomic and financial variables, were analyzed over a thirteen-year period, which included various crisis moments, such as the sovereign debt crisis, the COVID-19 pandemic and the onset of the Russia/Ukraine conflict. Using dynamic and nonlinear models, our research reveals statistically significant and consistent relationships between the variables under investigation, particularly during periods of global financial and pandemic crises. The analysis revealed that the VIXCLS is the most influential global risk factor, with certain risk factors being influenced by environmental segments, particularly Alternative Energy. This influence can create conditions conducive to contagion risk and diminish the benefits of portfolio diversification. This study contributes to a deeper understanding of the connection between environmental investments and their vulnerability to significant global events and risks. [ABSTRACT FROM AUTHOR]

This study addresses how and why the stock return volatility of REITs changes over time and identifies which mechanisms influence it at a firm level. Using U.S. equity REIT data from 1997 to 2018, we provide evidence that systematic risk and the underlying market for a REIT's properties affect their stock return volatility. The results suggest that both equity and property markets can contribute to an increase in REITs' stock return volatility. Portfolio diversification can reduce their sensitivity to property market risk. REITs with more asymmetric information and financial constraints are more vulnerable to property market risk. [ABSTRACT FROM AUTHOR]

Purpose: Farmland is an important property sector that has attracted the attention of institutional investors globally in recent years. This paper examines the risk-adjusted performance and portfolio diversification benefits of Australian farmland in a portfolio over the eight-year period of Q2:2015–Q2:2023, highlighting the unique property management dimensions to this property sector for its effective role in an institutional investor's property portfolio. Design/methodology/approach: Using the quarterly ANREV Australian farmland index over Q2:2015–Q2:2023, the risk-adjusted performance and portfolio diversification potential of Australian farmland is assessed. Constrained mixed-asset portfolios are used to assess the potential added-value role of Australian farmland in a mixed-asset portfolio. Analyses are also done for the farmland sub-sectors of annual farmland and permanent farmland. Findings: Australian farmland is seen to show strong risk-adjusted performance but at a much higher risk level than that seen for direct property. Diversification benefits from Australian farmland are also evident, with an important role by Australian farmland seen in the mixed-asset portfolio. Specific farmland property management strategies are identified for the effective inclusion of farmland in an institutional investor's property portfolio, including the potential benefits towards net zero carbon strategies. Originality/value: This is the first research that provides an independent empirical examination of the strategic importance of Australian farmland property for institutional investors using the institutional investment-grade ANREV Australian farmland database, from both an investment and environmental perspective. The unique property management implications for Australian farmland property are also highlighted, including the potential role of Australian farmland in net zero carbon strategies by institutional investors. [ABSTRACT FROM AUTHOR]

Copyright of Gazi Journal of Economics & Business is the property of Gazi Journal of Economics & Business and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This survey aims to provide insightful and objective perspectives on the research history of quantitative portfolio management strategies with suggestions for the future of research. The relevant literature can be clustered into four broad themes: portfolio optimization, risk-parity, style integration, and machine learning. Portfolio optimization attempts to find the optimal trade-off of future returns per unit of risk. Risk-parity attempts to match the exposure of various asset classes such that no single asset class dominates portfolio risk. Style integration combines risk factors on a security level such that rebalancing differences cancel out. Finally, machine learning utilizes large arrays of tunable parameters to predict future asset behavior and solve non-convex optimization problems. We conclude that machine learning will likely be the focus of future research. [ABSTRACT FROM AUTHOR]

Purpose –Tourism development can provide a sustainable path through which to diversify the economy. The aim of this research is 1) to assess the current economic diversification of a potential tourism region in an emerging economy, that of the Ulytau region of Kazakhstan; 2) to detail the impediments to economic diversification through tourism development, and 3) to recommend ways to foster economic diversification. Methodology/Design/Approach – The research uses secondary data to assess the current situation of the region and in-depth interviews with tourism and economic development experts to understand the current obstacles to economic diversification. Findings – This rural region of Kazakhstan is relatively concentrated in terms of its economic diversification and investment in infrastructure such roads, airports, and telecommunication as well as marking and promotion of the natural and cultural attractions will be a path to diversify the economy through tourism development. Originality of the research – This research uses evolutionary economic geography as a useful framework through which to view how destinations change over time. The research provides a model through which other destinations, dominated by non-renewable resource extraction can pivot towards tourism as a way to diversify the economy. [ABSTRACT FROM AUTHOR]

Purpose – This study aims to evaluate the performance of the Czech spa industry within a dynamically changing external environment, specifically in the context of the COVID-19 pandemic. Considering the relationship between tourist attractiveness and fiscal policy effectiveness, the research explores the divergences existing among spa companies functioning across discrete spa resort categories within the Czech Republic. Methodology/Design/Approach – The research employs secondary data obtained from the State Statistical Office and the Business Register. The analysis entails an examination of the relationship between the level of tourist attractiveness and alterations in sales. Findings – The study reveals that spa resorts with higher levels of tourist attractiveness encountered a more pronounced decline in sales. Despite the notable allocation of public funds, the impact of subsidies on economic outcomes remained limited. Originality of the research – A contribution lies in its revelation of the adverse implications of over-reliance on tourism for the spa industry. The study highlights the imperative for diversification in resort portfolios. Moreover, the research offers valuable insights into the optimal allocation of subsidies, suggesting directions for more effective utilization and distribution in a manner that supports the industry's long-term sustainability and resilience. [ABSTRACT FROM AUTHOR]

Bitcoin is regarded as a remarkable achievement of the Fourth Industrial Revolution and ranks among the most intricate technological and financial creations. It has long been the focus of attention of investors who are looking for a safe-haven asset. The purpose of this study is to check whether Bitcoin plays the role of a safe-haven asset (hedge). To achieve this, the impact of economic and political uncertainty (EPU) on the return and variation of Bitcoin is investigated. It is being analyzed whether, in comparison with the development of EPU, the returns and variations of Bitcoin show characteristics typical of safe-haven assets or those of ordinary speculative assets. As EPU levels elevate, it is anticipated that safe-haven assets like gold will see a rise in both their returns and variation, whereas typical speculative assets will experience heightened variation and diminished returns. The study uses ordinary linear regression and quantile regression models that cover data for the period between February 2013 and July 2023. These models play a crucial role in ascertaining if Bitcoin functions as a safe-haven asset during turbulent times and if it holds the capacity to serve as a hedge against economic uncertainty. The results of the study are of paramount importance for investors, as they help them decide whether to include Bitcoin in their portfolios for diversification and protection of their capital during unstable economic conditions. [ABSTRACT FROM AUTHOR]

In this study, we apply a novel approach of portfolio diversification—the robust maximum diversified (RMD)—to a small and developing economy's stock market. Using monthly returns data from August 2019 to May 2024 of 18/19 stocks listed on Fiji's South Pacific Stock Exchange (SPX), we construct the RMD portfolio and simulate with additional constraints. To implement the RMD portfolio, we replace the covariance matrix with a matrix comprising unexplained variations. The RMD procedure diversifies weights, and not risks, hence we need to run a pairwise regression between two assets (stocks) and extract the R-square to create a P-matrix. We compute each asset's beta using the market-weighted price index, and the CAPM to calculate market-adjusted returns. Next, together with other benchmark portfolios (1/N, minimum variance, market portfolio, semi-variance, maximum skewness, and the most diversified portfolio), we examine the expected returns against the risk-free (RF) rate. From the simulations, in terms of expected return, we note that eight portfolios perform up to the RF rate. Specifically, for returns between 4 and 5%, we find that max. RMD with positive Sharpe and Sortino (as constraints) and the most diversified portfolio offer comparable returns, although the latter has slightly lower standard deviation and downside volatility and contains 94% of all the stocks. Portfolios with returns between 5% and the RF rate are the minimum-variance, the semi-variance, and the max. RMD with positive Sharpe; the latter coincides with the RF rate and contains the most (94%) stocks compared to the other two. An investor with a diversification objective, some risk tolerance and return preference up to the RF rate can consider the max. RMD with positive Sharpe. However, depending on the level of risk-averseness, the minimum-variance or the semi-variance portfolio can be considered, with the latter having lower downside volatility. Two portfolios offer returns above the RF rate—the market portfolio (max. Sharpe) and the maximum Sortino. Although the latter has the highest return, this portfolio is the least diversified and has the largest standard deviation and downside volatility. To achieve diversification and returns above the RF rate, the market portfolio should be considered. [ABSTRACT FROM AUTHOR]

In this paper, we investigate whether the VC institutions' position in the network affects their investment strategies and performance. Our results show that network location has a negative correlation with geographic concentration index, industry concentration index, and stage concentration index, which indicates that the higher the network position of the cross-border VC institutions, the higher the degree of geographical diversification, the wider the industry diversification, and the higher the investment stage diversification of their investments. In addition, our results show that the relationship between network position and the VC's performance is not simply linear but rather an inverted U-shaped correlation. When the network location is lower than the critical value, higher network location positively improves the VC's investment performance; however, when the network location is higher than the critical value, then the relationship is reversed. [ABSTRACT FROM AUTHOR]

Since the Global Financial Crisis, central banks have created an environment in which risk taking and leveraging were the predominant strategies in the markets. Unprecedented central bank stimulus has led to market dynamics in which the availability of market liquidity has replaced the fundamentals of the economy as a driver of investment returns. The COVID crisis ended a 40-year period of low inflation, declining interest rates, and decreasing macro volatility in developed markets. The rise of inflation changed the market dynamics, and the diversification effect between liquid bonds, credit, and equity markets weakened significantly. As the investment market has become less diversified, it has become necessary to find new sources of diversification in portfolios. The author proposes a functional framework for asset allocation under uncertainty of correlation regimes. The functional categories for the asset classes in a portfolio are return-seeking assets, diversifiers, and tail risk hedges. The framework exploits the characteristics of defensive and diversifying alternative risk premium strategies, as well as the artificial diversification effect of illiquid asset classes. [ABSTRACT FROM AUTHOR]

The Journal of Portfolio Management has published a special issue that includes in-depth interviews with four chief investment officers (CIOs) and five theme-oriented articles on critical investment topics. The interviews provide insights into the decision-making processes and strategies of influential asset management companies. The CIOs emphasize the importance of long-term strategies, technology, risk management, client expectations, and leadership styles. The theme-oriented articles cover topics such as fixed-income investing, portfolio diversification in the post-COVID era, leadership in investment management, and the complexities of integrating environmental, social, and governance (ESG) factors into investment portfolios. The articles offer valuable insights into the evolving investment landscape and provide practical knowledge for market professionals. [Extracted from the article]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study conducts an empirical analysis of the impact of climate risk on Environmental, Social, and Governance (ESG) investments in Asia. Using monthly data from 2015 to 2022 for 11 Asian countries and applying wavelet coherence analysis with a panel Auto-regressive Distributed Lag Model (ARDL) cointegration approach, the study concludes that (1) ESG and stock market returns are positively correlated during economic turmoil in China and Malaysia; (2) climate risk positively influences ESG returns, suggesting that it enhances returns during uncertain times rather than having a detrimental effect; (3) returns on conventional assets are negatively impacted by climate risk; and (4) ESG investments serve as an effective hedge against climate risk and provide a sound strategy for portfolio diversification in the Asian market. [ABSTRACT FROM AUTHOR]

To the best of our knowledge, this article is the first to present a conceptual approach for a private market-based direct index. Based on the growing data availability of capital table management vendors, the authors propose a new way of determining a start-up's fair value. Using hedonic methods as an enabler, the authors consider changing value-determining components, thus creating a dynamic valuation model. Finally, the authors outline several implications for the index constituents, such as increased information efficiency and benefits from decreasing capital costs. In this way, the authors introduce a new niche for direct indexing (DI) applications that pressures indexing vendors and creates extended investment diversification opportunities for preliminary institutional investors. This allows the creation of major benchmarks that act as private equity (PE) proxies. [ABSTRACT FROM AUTHOR]

Purpose: The main objective of this study is to analyze the mediating role of intellectual capital in the relationship between diversification, financial stability, and efficiency of the banking sector in Ethiopia. Design/methodology/approach: Secondary data for this study was obtained from audited financial statements of 17 Ethiopian commercial banks for a decade starting in 2013. A descriptive and explanatory research design with a quantitative research approach was employed. The seemingly unrelated Hierarchical regression analysis is used to estimate diversification's effect on banks' financial stability and efficiency, considering the interaction between diversification and intellectual capital as a mediating variable. Findings: The Mediation analysis reveals that asset diversification improves the financial stability of commercial banks when mediated by intellectual efficiency. Investment diversification negatively impacts risk-adjusted return on asset and Z score. Intellectual capital significantly enhances commercial banks' efficiency and financial stability in Ethiopia and mediates the relationship between geographic diversification, financial stability, and efficiency. The mediation analysis also indicates that intellectual capital significantly mediates the relationship between income diversification and efficiency. Practical implications: This study highlights the importance of intellectual capital and promotes its strategic allocation by management and regulatory bodies to enhance the financial stability and operational effectiveness of the banking industry in Ethiopia. Originality/value: To the best of the researcher's knowledge, this study is one of the rare attempts to investigate the mediating role of intellectual capital on the nexus between diversification, financial stability, and efficiency of commercial banks in Ethiopia. [ABSTRACT FROM AUTHOR]

This study employs the Maximal Overlap Discrete Wavelet Transform technique to analyze the wavelet-based correlations between Bitcoin, bond markets, and thirteen sectoral stock indices in India over the period from 2O17 to 2O23, focusing on the comparison of pre -and post-COVID-19 pandemic effects. The aim is to investigate the dynamic interrelationships and to understand the impact of the COVID - 19 pandemic on these financial assets. The study period is divided into pre-COVID-19 and post-COVID-19. Findings from the study reveal a minimal negative correlation between Bitcoin, bond markets, and the sectoral stock indices in the pre -COVID era, indicating a lack of significant interdependence among these assets. However, the scenario changes markedly in the post-COVID period, shifting towards a positive correlation. This shift suggests that the COVID-19 pandemic has altered the relationship dynamics, leading to a more interconnected financial environment where movements in Bitcoin have begun to show a significant positive correlation with the movements in bond and sectoral stock indices in India. The study contributes to the existing literature by providing empirical evidence of how external shocks, such as the COVID-19 pandemic, can influence the correlation patterns among different financial assets. It highlights the importance of considering the changing dynamics in financial market correlations for investors, policymakers, and researchers in portfolio diversification, risk management, and financial stability analysis. Further, it underscores the role of alternative investments like Bitcoin in the evolving market landscape, particularly in response to global crises. [ABSTRACT FROM AUTHOR]

The extent of correlation or co-movement among the returns of developed and emerging stock markets remains pivotal for efficiently diversifying global portfolios. This correlation is prone to variation over time as a consequence of escalating economic interdependence fostered by international trade and financial markets. In this study, the time-varying correlation and co-movement between the JSE.JO stock market of South Africa and its developed and developing stock market partners are analyzed. The dynamic conditional correlation–exponential generalized autoregressive conditional heteroscedasticity (DCC-EGARCH) methodology is employed with different multivariate distributions to explore the time-varying correlation and volatilities between the JSE.JO stock market and its partners. Based on the conditional correlation results, the JSE.JO stock market is integrated and co-moves with its partners, and the conditional correlation for all markets exhibits time-variant behavior. The conditional volatility results show that the JSE.JO stock market behaves differently from other markets, especially after 2015, indicating a positive sign for investors to diversify between the JSE.JO and its partners. The highest value of conditional volatility for markets was in 2020 during the COVID-19 pandemic, representing the riskiest period that investors should avoid due to the lack of diversification opportunities during crises. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study examines the hedging and safe-haven characteristics across the various segments of non-fungible tokens (NFTs). It adopts the case study approach to blend the key study findings on the risk and return aspects of different NFT segments. The study finds that various segments of NFTs have mixed levels of correlations with traditional financial assets. Online games and metaverse segments of NFTs display a link to the crypto assets. Similarly, only the metaverse segment shows an association with the market sentiment. Art, online games, and collectibles segments within the NFTs space show mixed levels of hedging. However, all NFT segments under consideration show ambiguous safe-haven facets. Overall, the present study highlights some of the important aspects to consider while investing in the different segments of NFTs with respect to portfolio optimization, market dynamics, and risk management. JEL Codes: C12, C13, J64 [ABSTRACT FROM AUTHOR]

Integration in financial markets offers opportunities for free flow of information and capital for international investments. However, this also poses challenges for maintaining effective international portfolio diversification due to heightened market correlations. This study aims to analyze the diversifying potential of Islamic financial assets and undertake a dynamic analysis of their correlation with volatility indices. In this context, the study explores the interaction between the Dow Jones Islamic Market Developed Markets Quality and Low Volatility Index (DJIDVI) and such volatility indices including the CBOE Volatility Index (VIX), CBOE Oil Volatility Index (OVX), CBOE Gold Volatility Index (GVZ), and Euro Currency Volatility Index (EVZ). The Dynamic Correlation-Multivariate Stochastic Volatility (DC-MSV) model is employed to assess of how volatility shocks in one asset influence the volatility of others. The findings reveal that DJIDVI demonstrates the highest volatility clustering among the considered series. Moreover, DJIDVI exhibits mutual interactions with VIX and EVZ, and shocks increasing DJIDVI volatility also contribute to heightened volatility in VIX and OVX. Notably, the correlation between DJIDVI and volatility indices is influenced by global events. The study emphasizes the enhanced predictability of DJIDVI and its negative correlation with other series establishing its potential as a diversifier. The findings of this study contribute to advancing the understanding of international portfolio diversification emphasizing the importance of incorporating Islamic financial assets.

The study investigates the connectedness between commodities and ESG stocks of India using the extended joint connectedness approach. The study found a time-varying relationship between commodities and ESG stocks. It also discovered that there is a low spillover between the two. However, the total connectedness increased during the Russia-Ukraine war but remained low. The study found that crude oil and natural gas act as net transmitters, while ESG stocks and gold act as net receivers. ESG stocks are negatively connected with gold and have a low degree of positive correlation with crude oil and natural gas. Therefore, portfolio diversification opportunities exist between commodities and ESG stocks. The study exhibits that investors may derive significant benefits by adjusting their portfolios based on the optimum weights provided by the portfolio construction technique. The study provides valuable insights for portfolio managers, investors, and policymakers.

This paper explores the spillover and leverage effects, as well as trading volume dynamics, of Financial, Technology, and FinTech Exchange-Traded Funds (ETFs) using ARMA-GARCH and ARMA-EGARCH models. The study indicates that these ETF sectors and the stock market index have significant connections and interdependencies, which can transmit shocks and volatility. Market fluctuations significantly impact the ETF sectors, with negative shocks having a more significant impact on volatility. Furthermore, increased volatility is linked to increased trading activity, which indicates active investor adjustments in uncertain periods. The practical implications of these findings for investors, portfolio managers, and policymakers are aimed at supporting portfolio diversification, risk management, and asset allocation decisions. Understanding the effect of market volatility on trading volumes can help improve trading strategies and liquidity management. The paper increases comprehension of spillover and leverage effects and trading volume in ETFs, enabling stakeholders to make well-informed decisions in the financial markets. [ABSTRACT FROM AUTHOR]

Real-estate prices have soared since the start of the COVID-19 pandemic amid historically low mortgage rates and limited supply. The external shock observed in the real-estate market through relief measures may trigger changes in optimal conservation portfolios. The objective of this research is to identify the impacts of the real-estate market shock triggered by the pandemic through low-interest rates and limited real-estate supply on risk-diversification strategies for land conservation investment and to understand the implications of these impacts. We use a case study involving biodiversity conservation in the central and southern Appalachian region of the US by comparing modern portfolio theory (MPT) outputs using future conservation cost predictions with and without the shock. We find that the financial burden to fund the same level of risk-diversifying conservation benefits increases due to the shock and increases at an increasing rate as the return on investment (ROI) objective rises. This finding is alarming since higher conservation costs triggered by the shock decrease the cost-effectiveness of risk diversification, and this effect exacerbates with the goal of achieving higher ROI. Spatial diversification strategies with and without the shock offer risk-diversification information to help conservation organizations determine effective investment strategies. [ABSTRACT FROM AUTHOR]

Past empirical studies demonstrate a positive connection between revenue concentration and organizational efficiency. This supports the idea that concentrating revenue helps minimize transaction costs of nonprofit organizations, resulting in greater efficiency. However, this finding contradicts the belief that revenue concentration increases the risk of revenue volatility, leading to service delivery disruptions and reduced efficiency in nonprofits. Moreover, these studies have used an efficiency measure that might not be suitable. To address this, our study examines the relationship between revenue concentration and organizational efficiency using a more appropriate measure. Analyzing data from Habitat for Humanity, we discover a U-shaped relationship: nonprofits are most efficient when fully diverse or fully concentrated in revenue. These findings contribute to the ongoing debate on nonprofit revenue diversification, with significant implications for nonprofits. They also highlight the importance of using more appropriate efficiency measures in future scholarly research. [ABSTRACT FROM AUTHOR]

The risk of revenue instability is a concern for any nonprofit. Existing research leads to the well-known strategy of equalizing revenues across sources to reduce revenue volatility. This study offers several expansions to this strategy. First, rather than focusing solely on deviations from mean revenue, I incorporate extreme revenue loss, or downside risk, as it threatens organizational survival and occurs more frequently than expected. Second, while revenue equalization is indifferent to the type of revenue source, I incorporate portfolio diversification that seeks a negative correlation between sources to avoid simultaneous losses. Using 2008 to 2012 financial data, results of fixed-effects regression suggest that portfolio diversification can reduce revenue volatility and downside risk. Moreover, the relationships between financial flexibility, growth potential, and revenue risk are more nuanced compared to existing research focused solely on deviation risk. The results can help nonprofits consider incorporating downside risk in revenue portfolio management to enhance financial security. [ABSTRACT FROM AUTHOR]

This study investigates the interdependent structure between Nigeria and developed stock market using directed acyclic graph with Bayesian estimation techniques for the period of March 11, 2020 to July 31, 2021. The dynamic Granger causal test of both the contemporaneous and autoregressive estimation were done using the Markov Chain Monte Carlo (MCMC) simulation method with Metropolis-Hasting (MH) sampling technique. The graphical structure of the instantaneous and autoregressive results shows returns correlation for Nigeria's stock market and both China and India's stock market while absence of return correlation are found for both US and UK stock market. The result implies that Nigeria's stock market has potential diversification benefit for the US and UK investors during pandemic crises. In addition, US stock market returns is found to depend on China stock market returns while volatility spill over runs from the US stock market to China's stock market. Last, UK stock market tends to depend on India's stock market. The implication of the study is that Nigeria's stock market is integrated with China and India's stock market while China's stock market is linked to the US stock market such that any financial shock from the lead stock markets is transmitted to the lagged stock markets. [ABSTRACT FROM AUTHOR]

Traditional stochastic optimization in financial operations research applications consist of a two-step process: (1) calibrate parameters of the assumed stochastic processes by minimizing a loss function, and (2) optimize a decision vector by reference to the investor's reward/risk measures. Yet this approach can encounter the error maximization problem. We combine the steps in a single unified feedforward network, called end-to-end. Two variants are examined: a model-free neural network, and a model-based network in which a risk budgeting model is embedded as an implicit layer in a deep neural network. We performed computational experiments with major ETF indices and found that the model-based approach leads to robust performance out-of-sample (2017–2021) when maximizing the Sharpe ratio as the training objective, achieving Sharpe ratio of 1.16 versus 0.83 for a pure risk budgeting model. Simulation studies show statistically significant difference between model-based and model-free approaches as well. We extend the end-to-end algorithm by filtering assets with low volatility and low returns, boosting the out-of-sample Sharpe ratio to 1.24. The end-to-end approach can be readily applied to a wide variety of financial and other optimization problems. [ABSTRACT FROM AUTHOR]

We investigate the out-of-sample diversification benefits of cryptocurrencies from a generalised perspective, a cryptocurrency-factor level, with traditional and machine-learning-enhanced asset allocation strategies. The cryptocurrency factor portfolios are formed in an analogous way to equity anomalies by using more than 2000 cryptocurrencies. The findings indicate that a stock–bond portfolio incorporating size- and momentum-based cryptocurrency factors can achieve statistically significant out-of-sample diversification benefits for investors with different risk preferences. Additionally, machine-learning-enhanced asset allocation strategies can boost the traditional approaches by enriching (shrinking) the distributions of weights allocated to potentially effective cryptocurrency factors. Our findings are robust to (i) the inclusion of transaction costs, (ii) an alternative benchmark portfolio, and (iii) a rolling-window estimation scheme. [ABSTRACT FROM AUTHOR]

The 1/N investment strategy, characterized by equally allocating wealth among available investment options, has garnered significant scholarly attention. Simultaneously, risk assessment and management play a critical role in financial decision-making, leading to the development of a diverse array of risk measure models. This paper aims to synthesize these two strategies and propose a novel approach for constructing a naive diversification strategy by incorporating commonly employed risk measures in financial analysis. The research involves an in-depth exploration of various risk measures utilized by financial professionals to enhance effective risk management. These measures include Mean-Variance (MV), Mean Absolute Deviation (MAD), Semi Standard Deviation (MSV), Value at Risk (VaR), Conditional Value at Risk (CVaR), Entropic Value at Risk (EVaR), Drawdown at Risk (DaR) of uncompounded cumulative returns, Conditional Drawdown at Risk (CDaR) of uncompounded cumulative returns, and Entropic Drawdown at Risk (EDaR) of uncompounded cumulative returns. To validate the efficacy of the proposed model, a real-world empirical case study utilizing the annual financial statements of the NASDAQ100 (NDX) database is conducted. The empirical findings from this study carry practical implications for investors and risk managers engaged in portfolio management. [ABSTRACT FROM AUTHOR]

Integration in financial markets offers opportunities for free flow of information and capital for international investments. However, this also poses challenges for maintaining effective international portfolio diversification due to heightened market correlations. This study aims to analyze the diversifying potential of Islamic financial assets and undertake a dynamic analysis of their correlation with volatility indices. In this context, the study explores the interaction between the Dow Jones Islamic Market Developed Markets Quality and Low Volatility Index (DJIDVI) and such volatility indices including the CBOE Volatility Index (VIX), CBOE Oil Volatility Index (OVX), CBOE Gold Volatility Index (GVZ), and Euro Currency Volatility Index (EVZ). The Dynamic Correlation-Multivariate Stochastic Volatility (DC-MSV) model is employed to assess of how volatility shocks in one asset influence the volatility of others. The findings reveal that DJIDVI demonstrates the highest volatility clustering among the considered series. Moreover, DJIDVI exhibits mutual interactions with VIX and EVZ, and shocks increasing DJIDVI volatility also contribute to heightened volatility in VIX and OVX. Notably, the correlation between DJIDVI and volatility indices is influenced by global events. The study emphasizes the enhanced predictability of DJIDVI and its negative correlation with other series establishing its potential as a diversifier. The findings of this study contribute to advancing the understanding of international portfolio diversification emphasizing the importance of incorporating Islamic financial assets. [ABSTRACT FROM AUTHOR]

This study delves into the critical role of financial literacy in shaping personal investment decisions. As financial markets become increasingly complex, the necessity for individuals to make well-informed investment choices has never been more crucial. Despite this, many individuals lack adequate financial knowledge, which can impede their ability to navigate investment opportunities effectively. This research aims to explore the direct impact of financial literacy on various aspects of investment decision-making. Key areas of focus include investment risk tolerance, portfolio diversification, and long-term financial planning. Through a detailed analysis involving a sample of individual investors, the study seeks to identify which elements of financial literacy are most strongly associated with effective investment practices. By examining the relationship between financial literacy and investment behaviors, the research highlights how enhanced financial knowledge can lead to improved investment outcomes. Specifically, the study investigates how a higher level of financial literacy contributes to greater risk tolerance, more strategic portfolio diversification, and more robust long-term financial planning. The findings are anticipated to demonstrate that individuals with higher financial literacy are more adept at making informed investment decisions, resulting in better-managed portfolios and increased wealth accumulation over time. This research underscores the importance of financial education in empowering investors and fostering more prudent financial decisionmaking. Ultimately, it aims to provide valuable insights for policymakers, educators, and financial advisors seeking to enhance financial literacy and improve investment practices among the general public. [ABSTRACT FROM AUTHOR]

This paper examines the inflation hedging capabilities of stock market and real estate investments in Mumbai, India's financial capital. Using historical data from 1991 to 2022, we analyze the performance of the BSE Sensex and Mumbai property prices relative to inflation rates. Our findings indicate that while both asset classes have provided long-term returns exceeding average inflation, real estate has demonstrated more consistent short-term inflation hedging properties. The BSE Sensex showed higher volatility and a slight negative correlation with inflation, aligning with previous studies on the Indian market. In contrast, Mumbai's real estate market exhibited a moderate positive correlation with inflation and more frequent outperformance of inflation rates. The paper contributes to the existing literature by providing a focused analysis of Mumbai's market and offering insights into the comparative inflation hedging effectiveness of stocks and real estate in an emerging market context. These findings have implications for investors seeking to protect their portfolios against inflation in India's dynamic economic environment. [ABSTRACT FROM AUTHOR]

In the context of the rapidly growing demand for green investments and the need to combat climate change, this study contributes to the emerging literature on green investments by exploring the time–frequency connectedness between green bonds (GBs) and green equities. Specifically, we examine the degree of connection between GBs and green equities, the extent to which these markets influence each other, and which one is the primary net transmitter versus the net receiver of shocks under diverse market conditions. To accomplish these objectives, we use the wavelet-based Quantile-on-Quantile (QQ), dynamic conditional correlation (DCC), portfolio implications, and Quantile VAR approaches. The results show that GBs and green equities have a strong positive connection, depending on time and frequency domains. However, a negative association between GBs and green equities is observed during periods of crisis, highlighting GBs' ability to hedge green equity portfolios. The portfolio strategies demonstrate that investors require to invest in the Green Economy equity and S&P GB portfolio to reach the highest level of hedging effectiveness. The findings further imply that the Global Water Equity Index transmits the highest spillover to other green assets, while the Green Economy Equity Index receives the most spillover from other assets. The pairwise volatility connectivity reveals that most pairs have minimal quantile dependence, indicating the potential for diversification across the GB and green equity pairs. These findings have significant implications for investors and policymakers concerned with green investments and climate change mitigation. [ABSTRACT FROM AUTHOR]

The aim of the research is to investigate the causality relationship between Bitcoin prices and BIST100 index, Gold Ounce prices, S&P500 index, brent oil prices and dollar index. For this purpose, weekly data set for the period 07.01.2018-12.05.2024 was used. Hatemi-J (2012) asymmetric causality test was used. The results show that there is a unidirectional causality relationship between Bitcoin prices and the BIST100 index, while there is a bidirectional causality relationship between Gold Ounce prices, S&P500 index, dollar index and brent oil prices. According to these results, a negative or positive shock in Bitcoin prices affects the negative or positive shocks of the variables, while a negative or positive shock in the variables affects the negative or positive shocks in Bitcoin prices. Accordingly, it is observed that Bitcoin investors do not have a homogenous structure. Accordingly, BIST100 index, Gold Ounce prices, S&P500 index, brent oil prices and dollar index investors can take a different position against decreasing or increasing Bitcoin prices. As a result, it is concluded that BIST100 index, Gold Ounce prices, S&P500 index, brent oil prices and dollar index investors take a highly sensitive position against Bitcoin prices. [ABSTRACT FROM AUTHOR]

The goal of this article is to look into the movements of two economic powers, the United States America and China, as well as the volatility spillover between the United States of America and China. Furthermore, the objective of this research is to compare and contrast the accuracy of forecasts made using univariate volatility models with those made using the Normal, Student-t, and Generalized Error models. Student t's Distribution with df and GED with Fixed Parameter Distribution, constructs in predicting stock volatility between the United States of America and China, based on 560 daily observations from the United States stock market (S&P 500 Index) and China's stock market (Shanghai Stock Exchange) (SSE Composite index and HANG SENG index).Advanced econometric models are used to achieve the research-based objectives i.e. The EGARCH (exponential generalized autoregressive conditional heteroscedastic) models (Chang, McAleer, & Tansuchat, 2012) have been applied to the data from January 27, 2000, to March 24, 2023. Asymmetry in volatility transmitting patterns, the movement of shocks with higher positive and negative magnitudes, and the model's suitability are all examined in the study. The potential benefits and dangers of investing are another focus of this empirical investigation. The fitness of financial series returns in the EGARCH model is one outcome. Other outcomes include the movement of financial series, volatility sketching, a description of the data and properties of the EGARCH model, and the fitness of series returns. The results show that, in the long run, the market in question is integrated. The results also demonstrate that the Chinese market mirrors the behaviour of the USA market and that investors have limited avenues for diversification at present. The results of the EGARCH model indicate that there were asymmetric volatility spillover effects between the USA and Chinese markets during the studied time periods. Based on a reliable technique that enables the examination of the dependence structure between the sample variables, this study also investigates co-movement in China. For investors looking for global investment diversification options, the findings offer helpful information. [ABSTRACT FROM AUTHOR]

This study analyzes the risk‐adjusted performance of commodity exchange‐traded funds (ETFs) across diverse market conditions. Examining monthly returns from December 2004 to June 2022, our findings suggest that commodity ETFs underperformed US stocks, indicating limited diversification benefits. However, we document positive α during turbulent market periods like the COVID‐19 crisis, signifying potential resilience. Furthermore, our factor regressions reveal that shifts in the global commodity price index and disposable personal income significantly influence commodity ETFs' excess returns, pointing to broader economic and income‐related trends. Commodity ETFs exhibit lower Value‐at‐Risk and Expected Shortfall compared to stock market indices, indicating reduced downside risk exposure for investors. Given the increasing popularity of commodity ETFs, these insights hold substantial significance for market participants. [ABSTRACT FROM AUTHOR]

In the past few decades, India's tech industry has boomed, making it a leader in the digital world. Today, India has many big tech companies, well-trained software developers, and cutting-edge technology like AI and cloud computing. This success shows India's innovative spirit and makes the country a good example for other developing nations. However, global portfolio managers often overlook potential diversification opportunities beyond India's dynamic stock market. This study investigates the viability of MINT (Mexico, Indonesia, Nigeria, and Turkey) as diversification targets, specifically analyzing spillover effects and volatility dynamics between their stock markets and that of India. Leveraging vector autoregressions (VARs) and dynamic conditional correlation (DCC)–GARCH models, we uncover intricate relationships. Further, DCC–GARCH analysis reveals varying degrees of volatility spillover, offering valuable insights for risk management. Our findings suggest that MINT economies, particularly Mexico and Turkey, hold promise for Indian portfolio diversification. By strategically incorporating these markets, investors can potentially mitigate India-specific risks and enhance portfolio returns. We urge global portfolio managers to consider Turkey as a viable diversification avenue, acknowledging the nuanced market growth dynamics highlighted in this study. [ABSTRACT FROM AUTHOR]