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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).

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.

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).

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.

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).

Investors capture the value of diversification differently, suggesting a gap between market value and investment value that can be explored.

This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.

The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.

First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.

This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.

The purpose of this paper is to provide theory for some popular models and strategies used by practitioners in constructing optimal portfolios. King (2007), for example, advocated adding a diversification term to mean-variance problems to create better portfolios and provided clear empirical evidence that this is beneficial.

The authors provide an analytical framework to help us understand different portfolio construction practices that may incorporate diversification and conviction strategies; this allows us to connect our analysis to ideas in psychophysics and behavioural finance. The critical psychological ideas are cognitive dissonance and entropy; the economics are based on expected utility theory. The empirical section uses the theory outlined and provides the basis for constructing such portfolios.

The model presented allows the incorporation of different strategies within a mean-variance framework, ranging from diversification and conviction strategies to more ESG-oriented ones. The empirical analysis provides a practical application.

To the best of the authors’ knowledge, this model is the first to bridge the gap between portfolio optimisation and the psychological ideas mentioned in a coherent analytical framework.

The purpose of this study is to evaluate whether a diversification by grape varieties may help wine producers reduce uncertainty in quantity and quality variations due to increasingly erratic climate conditions.

This study hand-collects granular quantity and quality data from wine harvest reports for vintages 2003 to 2017 for the Valais region in Switzerland. The data allows us to obtain detailed data on harvested kilograms/liters and Oechsle/Brix degrees. It is then merged with precise meteorological data over the same sample period. The authors use this data set to capture weather conditions and their impact on harvested quantities and quality. Finally, they build portfolios including different grape varieties to evaluate whether this reduces variations in quality and quantity over vintages.

The findings highlight that the weather varies relatively strongly over the sample period and that climate hazards such as hail, frost or ensuing vine diseases effectively occur. These strongly impact the harvested quantities but less the quality of the wine. The authors further show that planting different grape varieties allows for a significant reduction in the variation of harvested quantities over time and thus acts as a good solution against climate risk.

The effect of climate change on viticulture is becoming increasingly important and felt and bears real economic and social consequences. This study transposes portfolio diversification which is central to reducing risk in the finance industry, into the wine industry and shows that the same principle holds. The authors thus propose a novel idea on how to mitigate climate risk.

This paper investigates potential safe haven assets for Middle East and North Africa (MENA) stock markets during the uncertainty period of the COVID-19 pandemic.

This study applies the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic (DCC-GARCH) model and the Diebold–Yilmaz spillover index for ten MENA stock markets, three precious metals and Bitcoin for the period 2013–2021.

Empirical results show, on the one hand, that the COVID-19 crisis risk has been transmitted to MENA stock markets through volatility spillover across markets. This has increased the conditional volatility for all markets. On the other hand, findings point out that the dynamic correlation between the precious metals/Bitcoin and stock markets is not stable and switches between low positive and negative values during the period under studies. Extending analysis to portfolio management, results reveal that investors should include precious metals/Bitcoin in their portfolio of stocks in order to reduce the risk of the portfolio. Finally, for the period of COVID-19, the analysis concludes that gold preserves its traditional role as a safe haven for MENA stock markets during the pandemic, while Bitcoin fails to provide this property.

These results have several implications for international investors, risk managers and financial analysts in terms of portfolio diversifications and hedging strategies. Indeed, the exploration of the volatility connectedness between financial, commodity and cryptocurrency markets becomes an essential task for all market participants during the COVID-19 outbreak. Such analysis can help investors and portfolio managers to evaluate the risk of investments in the MENA stock markets during the crisis period and to achieve the optimal diversification strategy and hedging instruments.

The paper interests MENA stock markets that experienced the last decade a substantial development in terms of market capitalization and number of listed firms. To the author’s knowledge, this is the first study that investigates the dynamic correlation between MENA stock markets and four potential safe haven assets, including three precious metals and Bitcoin. In addition, the paper employs two types of models, namely the DCC-GARCH model and the Diebold-Yilmaz spillover index.

This study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and during different market conditions, and their implications for portfolio management.

We use Time-varying parameter vector autoregressive and quantile frequency connectedness approach models for the connectedness framework, in conjunction with Diebold and Yilmaz’s connectivity approach. Additionally, we use the minimum connectedness portfolio model to highlight implications for portfolio management.

Regarding the uncertainty of the whole system, we show a small contribution from Bitcoin and Fintech, with a higher contribution from the four Asian Tigers (Taiwan, Singapore, Hong Kong and Thailand). The quantile and frequency analyses also demonstrate that the link among assets is symmetric, with short-term spillovers having the largest influence. Finally, Bitcoins and Fintech stocks are excellent diversification and hedging instruments for Asian equity investors.

There is an instantaneous, symmetric and dynamic return and volatility spillover between Asian stock markets, Fintech and Bitcoin. This conclusion should be considered by investors and portfolio managers when creating risk diversification strategies, as well as by policymakers when implementing their financial stability policies.

The study’s major contribution is to analyze the volatility spillover between Bitcoin, Fintech and Asian stock markets, which is dynamic, symmetric and immediate.

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.

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.

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.

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.

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.

This study aims to investigate the impact of Internet use on household financial market participation and portfolio choice.

Based on the Chinese General Social Survey 2017 (CGSS2017), this study empirically explores whether Internet use affects household financial market participation in China with an Endogenous Switching Probit model.

The results show that households using the Internet are more likely to invest in financial markets. Further research shows that households with high Internet use are significantly more likely to participate in financial markets than households with low Internet use. From the perspective of household portfolio choice, Internet use has a certain role in increasing the probability of portfolio diversification. However, among households that have invested in financial markets, those with a high-frequency use of the Internet do not show an impact on portfolio diversification.

This study complements existing research about the impact of Internet use or not on household financial market decisions and portfolio choice, expands the knowledge on the household financial market choice from the respective of the degree of Internet use.

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.

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.

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.

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.

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.

We examined the dynamic volatility connectedness and diversification strategies among US real estate investment trusts (REITs) and green finance indices.

The DCC-GARCH dynamic connectedness framework and he DCC-GARCH t-copula model were employed in this study.

Using daily data from 2,206 observations spanning from 2 January 2015 to 31 January 2023 this paper presents the following findings: (1) cross-market spillovers exhibited a high correlation and significant fluctuations, particularly during extreme events; (2) our analysis confirmed that REIT acted as net receivers from other green indices, with the S&P North America Large-MidCap Carbon Efficient Index dominating the in-network volatility spillover; (3) this observation suggests asymmetric spillovers between the two markets and (4) a portfolio analysis was conducted using the DCC-GARCH t-copula framework to estimate hedging ratios and portfolio weights for these indices. When REIT and the Dow Jones US Select ESG REIT Index were simultaneously added to a risk-hedged portfolio, our findings indicated that no risk-hedging effect could be achieved. Moreover, the cost and performance of hedging green assets using REIT were found to be comparable.

We first examined the dynamic volatility connectedness and diversification strategies among US REITs and green finance indices. The outcomes of this study carry practical implications for market participants.