Diversification Benefits Research Articles

The first map of crop sequence types in Europe over 2012–2018

Abstract. Crop diversification is considered a key element of agroecological transition, whereas current dominant cropping systems are known to rely on only a few crop species – like cereals in Europe. To assess the benefits of crop diversification at a large scale, an accurate description of current crop sequences is required as a baseline. However, such a description is lacking at the scale of Europe. Here, we developed the first map of dominant crop sequences in Europe for the period 2012–2018. We used the Land Use Cover Area frame statistical Survey (LUCAS) dataset that provides temporally incomplete (2012, 2015 and 2018) land cover information from a stable grid of points covering Europe. Eight crop sequence types were identified using hierarchical clustering implemented on LUCAS data and mapped over Europe. We show, in France, that the relative importance of these eight crop sequence types (as estimated from LUCAS data) was highly consistent with those derived from an almost spatially exhaustive temporally complete national dataset (the French Land Parcel Identification System) for the same period, thus validating the method and typology for this country. Land use (i.e. crop production area) derived from our map of dominant crop sequences was also highly consistent with land use reported by official statistics at both national and European levels, validating the approach at a European scale. This first map of dominant crop sequences in Europe should be useful for future studies dealing with agricultural issues that are sensitive to crop rotations. The map of dominant crop sequence types in Europe derived from our work is available at https://doi.org/10.5281/zenodo.7016986 (Ballot et al., 2022).

Green cryptocurrencies and portfolio diversification in the era of greener paths

The shift towards cleaner fuels from hydrocarbons has influenced nearly all market types and asset classes, and cryptocurrencies are no exception. The complex mechanism of blockchain and mining consumes high levels of electricity and surges environmental footprints in electronic waste generation. Existing studies that examine green and sustainable investments are limited to sustainable equities or green bonds; therefore, this study opens up a new research direction by considering green (energy-efficient) cryptocurrencies. First, this study develops a four-step screening process to systematically select cryptocurrencies that are greener than others. A comprehensive set of green and non-green assets and a battery of empirical tests are then employed to examine the diversification benefits of selected green cryptocurrencies against several well-diversified equity portfolios at the global, regional, and country levels. The diversification benefits of green cryptocurrencies are compared with non-green cryptocurrencies using (i) the four-moment modified value at risk and conditional value at risk, (ii) four different portfolio optimization strategies, and (iii) dynamic correlation-based hedge and safe-haven regression analyses. The results show that green cryptocurrencies provide diversification benefits that are at least comparable to, and in some cases, superior to, non-green (energy-intensive) cryptocurrencies. Cardano and Tezos are identified as green cryptocurrencies offering the most diversification benefits to investors, followed by EOS, Steller, and IOTA. This study provides valuable insights to investors and policymakers, specifically those concerned with achieving sustainability and ESG-compliance (environmental-social-governance) goals and seeking green assets to hedge and diversify various traditional investments.

Dynamic conditional correlation between green and grey energy ETF markets using cDCC-MGARCH model

ABSTRACTUsing the cDCC form of the multivariate GARCH models (MGARCH), this paper examines the time-varying conditional correlations among green renewable, grey non-renewable, and the conventional investment strategy in the exchange-traded funds (ETFs) markets. Daily excess returns for the largest energy ETFs are used as proxies for the US energy sector over the period of 25 June 2008 to 9 May 2023. The empirical results find that the AR(1)-GARCH(1, 1)-cDCC model with t-distribution to be the best fit. The results indicate that the time-varying correlations between green and grey energy ETFs are between 0.42 and 0.55 and statistically significant at 10%, with lesser degree of persistence in green energy, while there is a high significant co-movement between the grey energy and the traditional investment strategy. This, in turn, implies that investing in green energy ETFs provides better diversification. These results provide important implications for policymakers, portfolio managers and investors on the benefits of portfolio diversification in energy markets amid the current global energy crisis.

Quantile connectedness of oil price shocks with socially responsible investments

We use a new method to disentangle various sources of oil price shocks and find how these sources are connected to major global environmental, social, and governance (ESG) equity indices under extreme market movements using daily data from October 2007 to March 2022. Our quantile-based connectedness analysis shows that return connectedness considerably amplifies with the size of the shock for both positive and negative shocks, indicating that oil shocks spread more intensely during extreme market movements. We also find that oil shocks originating from unexpected variation in demand and risk substantially contribute to the variation in the ESG returns while supply shocks have relatively little effect when estimated at the median level but the contribution of all different types of shocks remain extremely high when analyzed at the tails. Our results indicate that socially responsible investments are prone to contagion and thus offer limited portfolio diversification benefits under extreme market movements. One clear implication of our study is that investors need to carefully design their risk management and diversification strategies to account for not only the source of the oil shocks but also the magnitude of the oil shock on their green equity investments. We also show that total dynamic connectedness significantly increased during the global financial crisis, European debt crisis, the Brexit episode and the recent COVID-19 outbreak.

Do Asian Islamic Equities Offer Diversification Benefits in Cryptocurrency Portfolio in Times of Increased Uncertainty?

This study explores whether Islamic equities offer portfolio diversification benefits to cryptocurrency investors. It employs the Continuous Wavelet Transform model to examine the nature of coherence between major cryptocurrency asset classes and major Asian Islamic equity markets on different investment horizons. We consider a range of Islamic equity indices for multiple countries and a basket of three prominent cryptocurrencies: Bitcoin, Ethereum and Ripple. Findings suggest that Asian Islamic equities offer portfolio diversification opportunities. Our findings also imply that Asian Islamic equities are not efficient and are prone to short-term speculative activities.

Operational challenges with complex assets : Navigating technology solutions for diversified institutional investment portfolios

In recent years, institutional investors have begun diversifying into asset classes previously deemed too complex or high-risk to suit their objectives. While these investments may hold the potential for exceptional returns, they also pose significant challenges from an operations and accounting perspective due to their bespoke nature. This paper explores the diversification trend and investment categories that are attracting attention (and capital) from institutions. It outlines the key operational issues these investments raise, as well as some strategies that can help investors overcome those issues and optimise the benefits of diversification.

Mixing things up! Identifying early diversity benefits and facilitating the development of improved variety mixtures with high throughput field phenotyping

AbstractCrop diversification is a potential strategy to increase the stability and productivity of crops, while reducing pathogen pressures and pesticide requirements. Crop variety mixtures provide some of these diversification benefits and their cultivation is fully compatible with current mechanized agronomic practices. However, the development of optimal variety mixtures is a long, labour‐intense process requiring extensive field trials. High throughput field phenotyping (HTFP) methods provide promising applications in field testing because they allow for precise, repeatable, and rapid measurements of crop properties. Here, we evaluated the use of HTFP for developing high‐performing oat (Avena sativa) variety mixtures by testing its suitability to predict diversity yield benefits from repeated canopy measurements across the growing season. Analyzing 26 mixtures of five varieties, we found significant overyielding at harvest, that is, mixtures were on average more productive than expected based on component pure stands. This grain yield overyielding was well predicted from deviations between mixture and pure stand canopy cover estimations, derived from HTFP mid‐way through the growing season. This shows that (i) positive interactions between oat varieties occur already at an early stage, (ii) such interactions lead to increased potential for light interception, (iii) HTFP offers rapid, scalable methods to screen for performant variety mixtures.

PERFORMANCE OF MSCI ISLAMIC INDICES: A COMPARATIVE STUDY OF MALAYSIA AND GULF COUNTRIES

Introduction: The Islamic finance industry has attracted increasing research interest, particularly in Islamic equity markets, in both academia and the corporate world during the past few decades. However, COVID-19 has caused a downturn in the Islamic stock markets. This study empirically explores and compares the performance of the MSCI Indices of Malaysia and each of the other MSCI Islamic indices in Gulf Cooperation Council (GCC) countries. Methods: To address the research questions, time series techniques, namely, the unit root test, cointegration, long-Run Structural Model (LRSM), Vector Error Correction Model (VECM), variance decomposition, impulse response, and persistence profile techniques, were used as the main method by utilizing monthly data from August 15, 2011, to November 15, 2020. Results: The results show that cointegration exists between the Malaysian Islamic indices and the six Islamic indices of GCC countries, which indicates that diversification benefits are limited in the long run because the indices move together. Additional results show a significant causality among the indices in both the short-run and long-run. (as shown in the LRSM and VECM tests). Conclusion and suggestion: The findings may have significant implications for portfolio diversification of Islamic indices among investors interested in Shariah-compliant securities in Malaysia and GCC countries, particularly in the COVID-19 era. Further research can be conducted for an in-depth analysis to examine the performance of these indices in terms of risk and return after the COVID-19 era using a more advanced technique.

Modeling underwriting risk: A copula regression analysis on U.S. property-casualty insurance byline loss ratios

This article evaluates underwriting risks for U.S. property-casualty insurance company using a by-line multivariate framework. We propose a regression system with copula structure to estimate the dynamics and dependences of by-line loss ratio changes. The dynamics are characterized by autoregressive, macroeconomic, and line-specific variables. The dependences are characterized by symmetric, asymmetric, and vine copulas to manifest the contemporaneous risk. Both positive and negative dependence of loss ratio changes are found, and the lines of business contribute distinct diversification effects from the Risk-based Capital (RBC) R5 formula suggested. Based on empirical studies of industry-wide data, we confirm that the choice of copula structure and marginal estimation method affects the model's performance in the stress testing of catastrophic events. The proposed approach can be regarded as an internal model calculating the diversification benefits across business lines, based on a statistical hypothesis in contrast to a regulatory base. These findings help insurers and regulators to evaluate their capital requirements more precisely and reduce liability-side risk.

Quantifying Portfolio Diversification Benefit via Return Indifference Curves

Quantifying Portfolio Diversification Benefit via Return Indifference Curves

Mean and volatility spillover in Asian economies: Evidence from trade war.

This study aims to assess the mean and volatility spillover due to trade war between US and China on the Asian markets using GARCH, evidencing that portfolio opportunity exists for the investors in these markets. These markets may offer diversification benefits to investors who fear the negative ramifications of stock markets of the economies in US and China. The study creates a composite variable to test the impact of trade war. The composition of the variable is based on Bilateral Tariffs, Trade policy and Economic policy uncertainty of US only. It means the study covers the US side only for creating a trade war variable. The findings of the study reveal no mean or volatility spillover exists. The study has implications for investors and policymakers.

Frequency connectedness between DeFi and cryptocurrency markets

This study investigates the time-frequency spillovers across main DeFi (AVA, POWR, DOGE, MED, BAT, Link, Maker, and SNX) and four leading cryptocurrency markets (Bitcoin, Ethereum, Litecoin, and Ripple). The results show using the time-domain spillover index of Diebold and Yilmaz (2012) high connectedness across markets, underlying forecasting opportunities. Ethereum and Litecoin are the largest contributors and receivers of spillovers while MED is the lowest contributors of shocks in the system. Using the time-frequency spillover index by Baruník and Křehlík (2018), we show that the spillover at long term is higher than those at the short- and medium terms. BAT, LINK, and LTC are net contributors of spillovers at different time investment horizons while AVA, POWR, DOGE, and MED are net receivers irrespective of the time horizons. For the remaining market, they switch from net receiver to net contributor and vice versa. The major events (COVID-19, COVID-19 vaccination, and Ukraine-Russia tensions) intensify the dynamic of return spillovers at short-, medium-, and long-terms, implying contagion effects and a decline in the diversification benefits.

Production Diversification as a Tool for Agricultural Risk Management: The Case of Northern Kazakhstan

This paper addresses the impacts of degree of risk aversion on optimal farm plans in Kazakh agriculture. The results obtained during the field research in the region of Northern Kazakhstan are presented. Calculations were carried out using data from 145 peasant farms in the region for 2017-2022 based on a risk model. It has been found that the choice of a portfolio is influenced not only by considerations of profitability and riskiness of crops, but also by grain production traditions deeply rooted among the farmers of the region, and the skills and knowledge associated with them, as well as the existing infrastructure. These circumstances constrain the wider spread of oilseed crops in the region. It seems that the size of the farm does not significantly affect the choice of portfolio, while the degree of risk aversion by the farmer affects the optimal farming plan. The potential benefits of the farming diversification are an empirical issue, and it should be addressed on a case-by-case basis. The question is to choose the utility function and its parameters that most accurately reflect the preferences of a particular farmer, the authors conclude.

Rank-Based Multivariate Sarmanov for Modeling Dependence between Loss Reserves

The interdependence between multiple lines of business has an important impact on determining loss reserves and risk capital, which are crucial for the solvency of a property and casualty (P&C) insurance company. In this work, we introduce the two-stage inference method using the Sarmanov family of multivariate distributions to the actuarial literature. In fact, we study rank-based methods using the Sarmanov distribution to adequately estimate the loss reserves and properly capture the dependence between lines of business. An inadequate choice of the dependence structure may negatively impact the estimation of the marginals and, hence, the reserve. Thus, we propose a two-stage inference strategy in this research to address this, while taking advantage of the flexibility of the Sarmanov distribution. We show that this strategy leads to a more robust estimation, and better captures the dependence between the risks. We also show that it generates smaller risk capital and a better diversification benefit. We extend the model to the multivariate case with more than two lines of business. To illustrate and validate our methods, we use three different sets of real data from both a major US property–casualty insurer and a large Canadian insurance company.

Risk and return in the biotech industry

PurposeBiotech companies stand as key actors in pharmaceutical innovation. The high risk and long timelines inherent with their R&D investments might hinder their access to funding, potentially stifling innovation. This study aims to explore into the appeal of biotech companies to capital market investors, whose financial backing could bolster the growth of the biotechnology sector.Design/methodology/approachThis paper uses a dataset of 774 US publicly listed biotech firms to investigate their risk and return characteristics by comparing them to pharmaceutical firms and a sample of matched non-biotech R&D-intensive firms over the sample period 1980–2021. Tests show that the conclusions remain consistent across diverse methodological approaches.FindingsThe paper shows that biotech companies are riskier than the average firm in the market index but outperform on a risk-adjusted basis both the market and a matched group of R&D-intensive firms. This is particularly true for large capitalization biotech, which is also shown to provide a diversification benefit by reducing the downside risk in past crisis periods.Originality/valueThis paper provides insight relevant to the current debate about the overall performance of the biotech industry in terms of policy changes and their impact on small, early-stage biotech firms. While small and early-stage biotech firms are playing an increasing role in scientific innovation, this study confirms their greater vulnerability to financial risks and the importance of access to capital markets in enabling those companies to survive and evolve into larger biotech.

Enhancing portfolio resilience during crisis periods: Lessons from BRICS indices and multi asset strategies

This paper uses Markowitz’s mean-variance model to construct an investment portfolio incorporating multiple assets – BRICS equity indices, Gold, crude oil, bonds, and cryptocurrencies. The optimally created risky portfolios outperform alternative portfolio optimization methods – the naive portfolio and the equal risk contribution portfolio; and established indices – the S&P 500 and the MSCI Emerging Equity Index in terms of metrics – adjusted Sharpe ratio, modified Sharpe ratio, and the modified Value at Risk. The findings are validated across different periods, including the COVID-19 period and the Russian invasion of Ukraine, including various in and out of sample periods. The findings highlight the benefits of portfolio diversity, mainly using BRICS indices, Gold, and Brent Crude oil, and challenge the notion of limited diversification benefits in BRICS indices found in previous studies. This paper further suggests the potential of emerging market bonds ETF as a diversification option during turbulent economic periods and highlights the limitations of cryptocurrencies in optimizing multi asset portfolios. By adopting the recommended multi asset portfolios, investors can enhance their risk-return trade-offs and achieve superior performance compared to the S&P500 and MSCI emerging indices. Lastly, the paper recommends future research opportunities in measuring portfolio performance and hedging strategies considering risk-adjusted return measurements, transaction expenses, and dynamic rebalancing techniques.

Foreign Equity Portfolio Investments and Market Returns at the NSE20 Share Index; Kenya

Purpose: Foreign portfolio investments have continued to play an important role in the world today because investors are more interested in investments that will give them higher returns for their investments. The purpose the study was to establish the effect of foreign portfolio investments and market returns in Kenya. The specific variables studied were foreign equity portfolios, foreign bond portfolios, foreign portfolio of treasury bills and foreign portfolio of exchange traded funds and how they affect the market returns at the NSE20 share index in Kenya.
 Methodology: The research methodology applied panel regression for inferential findings and Langrage multiplier test done to determine the pooled effect with the aid of STATA 18 software. Secondary data was sourced from the NSE annual reports, CMA bulletins, CBK websites of the respective companies listed in the index for the period between 2013 to 2022.
 Findings: The study findings indicated a positive and significant relationship of foreign equity portfolios, foreign portfolio of T Bills and foreign portfolio of ETFs with market returns at the NSE20 share index. Conversely, foreign bond portfolio exhibited a negative significant relationship with market returns at the NSE 20 share index.
 Unique Contribution to Theory, Practice and Policy: The study supported Modern Portfolio Theory(MPT) that suggests that for an investor to maximize returns, an investor will choose from a wide array of portfolios that will suit his needs and risk profiles and Neoclassical Theory of Investment that suggests that investors will take advantage of location differences to profit from arbitrage opportunities and Total portfolio theory that suggests that combination of securities posits a higher performance due to significant diversification benefits linked to a basket of securities. The Modern portfolio theory measuring market return seemed to hold in that it will give an investor an understanding of the most efficient portfolio that will give the largest returns at a given level of risk. The theory was suggested for future related research because it will give an investor a strategy for successful portfolio investments.

Corporate resilience to the COVID-19 pandemic: Evidence from the airline industry

This study investigates whether airline firm characteristics moderate the negative impact of rising COVID-19 confirmed cases on airlines’ stock. 87 listed airlines in 44 countries during 2020 are examined with a panel regression. The findings indicate that airline firm size and the number of destination countries reduce the negative effect of the pandemic. The impact of COVID-19 and firm size are significant only during the early stage of the pandemic due to high uncertainty. While the impact of COVID-19 is significant in the U.S. and other regions, it is not the case in China. In addition, the pandemic has had a greater impact on low-cost airlines than on full-service airlines. The study relates the findings to the size advantages and the benefit of diversification. While mergers and acquisitions are a promising business strategy for survival, governments and regulators are necessary to balance the market power of survival and new entrants in the future.

Spillover of volatility among financial instruments: ASEAN-5 and GCC market study.

The research examines a comovement and spillover of volatility among foreign exchange, conventional and shariah stock markets in Association of South East Asian Nation-5 (ASEAN) countries and Gulf Cooperation Council (GCC) countries. Generalized Autoregressive Conditional Heteroskedasticity-Baba, Engle, Kraft and Kroner (GARCH-BEKK) and Dynamic Conditional Correlation (GARCH-DCC) models are used to capture the correlation and transmission volatility of the markets. The overall results show that both the Shariah and the conventional stock indices respond similarly to each country's currency. A bidirectional (two-way relationship) volatility spillover exists only in Malaysia and a unidirectional (one-way relationship) volatility is observed in Indonesia, Singapore, Thailand, and Bahrain. The rest of the markets-the Philippines, Saudi Arabia, and the United Arab Emirates (UAE)-do not have any volatility spillover evidence. Based on DCC outcomes, the conventional and Shariah stock in ASEAN-5 countries and GCC countries reveal the market efficiency, i.e., a positive high conditional correlation. Only Bahrain shows less efficiency than the other countries. It implies no portfolio diversification advantage in conventional and Shariah stock indices. Contrarily, currency and stock (conventional and Shariah) markets provide portfolio diversification benefits for all ASEAN-5 and GCC countries.

Does commodity exposure benefit traditional portfolios? Evidence from India

Commodities and commodity futures are expected to benefit stock and bond portfolio diversification because traditional asset types like equities and bonds have low correlations with commodities. During periods when stocks and bonds may underperform, commodities may provide a hedge against inflation and other economic uncertainties. This study investigates the diversification benefits of adding commodities to a traditional portfolio of stock and bonds from the perspective of an Indian investor. It employs several commonly used asset allocation strategies such as mean-variance, equal risk contribution, most diversified portfolio, and equal weight portfolio on different commodity derivative groups. The performance of various portfolios indicates that not all commodity groups provide substantial diversification benefits to a traditional portfolio. Agricultural commodities enhance performance (with an Omega ratio of 1.654), whereas metal and energy-related commodities do not diversify the traditional portfolio significantly (Omega ratio of 1.087 and 0.945, respectively). Gold and different equity sectors also provide some diversification benefits. This study also supports the hypothesis that the behavior of different commodity groups is quite different. AcknowledgmentThe infrastructural support provided by the FORE School of Management, New Delhi, in completing this paper is gratefully acknowledged.