Cryptocurrencies and portfolio diversification in an emerging market

PurposeThis paper examines the effect of cryptocurrencies on the portfolio risk-adjusted returns of traditional and alternative investments within an emerging market economy.Design/methodology/approachThe paper employs daily arithmetic returns from August 2015 to October 2018 of traditional assets (stocks, bonds, currencies), alternative assets (commodities, real estate) and cryptocurrencies. Using the mean-variance analysis, the Sharpe ratio, the conditional value-at-risk and the mean-variance spanning tests.FindingsThe paper documents evidence to support the diversification benefits of cryptocurrencies by utilising the mean-variance tests, improving the efficient frontier and the risk-adjusted returns of the emerging market economy portfolio of investments.Practical implicationsThis paper firmly broadens the Modern Portfolio Theory by authenticating cryptocurrencies as assets with diversification benefits in an emerging market economy investment portfolio.Originality/valueAs far as the authors are concerned, this paper presents the first evidence of the effect of diversification benefits of cryptocurrencies on emerging market asset portfolios constructed using traditional and alternative assets.

Diversification Perspectives of a Single Equity Market: Analysis on the Example of Selected CEE Countries

The study addresses the benefits of a unified stock market in terms of diversification risk for the eight CEE stock markets. For this purpose, each stock market was treated as a separate portfolio based on the companies listed during 2018–2019. Portfolio diversification techniques were used to identify risk linked with the eight Central Eastern European stock markets. The results show that the stock market with the lowest diversification risk was the Bulgarian Stock Exchange, followed by the Prague Stock Exchange, the Ljubljana Stock Exchange, and at the end stands the Zagreb Stock Exchange. The portfolio constructed from the Zagreb Stock Exchange carries the highest portfolio risk, but it also offers the highest weekly weighted average returns. Stock markets that benefit in terms of portfolio risk from unification are the Bratislava Stock Exchange, the Budapest Stock Exchange, the Bucharest Stock Exchange, the Warsaw Stock Exchange, and the Zagreb Stock Exchange. The indexes where the portfolio risk increases at the time of unification are the Bulgarian Stock Exchange, the Ljubljana Stock Exchange, and the Prague Stock Exchange. From a managerial perspective, financial investors get a novel outlook on the diversification possibilities offered within a hypothetical unified CEE stock market.

Decomposition of Natural Catastrophe Risks: Insurability Using Parametric CAT Bonds

Nat Cat risks are not insurable by traditional insurance mainly because of producing highly correlated losses. The source of such correlation among buildings of a region subject to a natural hazard is discussed. A decomposition method is proposed to split Nat Cat risk into idiosyncratic (and hence insurable) risk and systematic risk (carrying the correlated part). It is explained that the systematic risk can be transferred to capital markets using a set of parametric CAT bonds. Premium calculation is presented for insuring the decomposed risk. Portfolio risk-return trade-off measures for investing on the parametric CAT bond are derived. Multi-regional and multi-hazard parametric CAT bonds are introduced to reduce the risk of the investment. The methodology is applied on a region with about 3000 residential buildings subject to flood hazards.

Sustainable Finance and COVID-19: The Reaction of ESG Funds to the 2020 Crisis

We investigated the financial performance of a sample of sustainable investment funds in terms of returns, volatility, and contagion risk during the financial crisis caused by the COVID-19 pandemic. In order to conduct a more reliable analysis, we considered a homogenous sample composed of 30 funds declaring the same benchmark (the MSCI Europe index). The Morningstar Sustainability ESG rating was used to determine the level of sustainability of each fund. Both the GARCH models and the event study suggest that funds with a higher ESG rating were able to outperform other funds during the COVID-19 period. These funds had a greater level of resilience and exhibited a lower level of risk contagion during the pandemic. These instruments appear to assume the role of risk protection and should be considered a means of both promoting sustainable growth and minimizing portfolio risk.

Diversifiable and Non-diversifiable Risk and the Advanced Choice under Ambiguous or Uncertain Conditions

The objective of this paper is to revisit the concepts of diversifiable and non-diversifiable risk, expound the portfolio risk in two ways: mathematically first, and with practical examples, second It also explains lending and borrowing at the risk-free rate of return, in addition to juxtaposing the diversification method to measure the unsystematic risk against utilizing Beta to measure the systematic risk. Furthermore, it briefly examines the mathematical simulation and sensitivity analysis, and mathematically delineates the technique for choices under risk, ambiguity, and uncertainty. The practical implication of this conceptual paper is to offer a further clarification of theoretical terms, especially those which might be interchangeable in financial and economic literature, and further show, by examples, the terms’ applicability.

Diversifiable and Non-diversifiable Risk and the Advanced Choice under Ambiguous or Uncertain Conditions

The objective of this paper is to revisit the concepts of diversifiable and non-diversifiable risk, expound the portfolio risk in two ways: mathematically first, and with practical examples, second It also explains lending and borrowing at the risk-free rate of return, in addition to juxtaposing the diversification method to measure the unsystematic risk against utilizing Beta to measure the systematic risk. Furthermore, it briefly examines the mathematical simulation and sensitivity analysis, and mathematically delineates the technique for choices under risk, ambiguity, and uncertainty. The practical implication of this conceptual paper is to offer a further clarification of theoretical terms, especially those which might be interchangeable in financial and economic literature, and further show, by examples, the terms’ applicability.

Project portfolio risk analysis with the consideration of project interdependencies

PurposeComprehensive project portfolio risk (PPR) analysis is essential for the success and sustainable development of project portfolios (PPs). However, project interdependency creates complexity for PPR analysis. In this study, considering the interdependency effect among projects, the authors develop a quantitative evaluation model to analyze PPR based on a fuzzy Bayesian network.Design/methodology/approachIn this paper, the primary purpose is to comprehensively evaluate project portfolio risk considering the interdependency effect using a systematical model. Accordingly, a fuzzy Bayesian network (FBN) is developed based on the existing studies. Specifically, first, the risks in project portfolios are identified from the project interdependencies perspective. Second, a fuzzy Bayesian network is adopted to model and quantify the interaction relationships among risks. Finally, the model is implemented to analyze the occurrence situation and characteristics of risks.FindingsThe interdependency effect can lead to high-stake risks, including weak financial liquidity, a lack of cross-project members and project priority imbalance. Furthermore, project schedule risks and inconsistency between product supply and market demand are relatively sensitive and should also be prioritized. Also, the validity of this risk evaluation model has been proved.Originality/valueThe findings identify the most sensitive risks for guaranteeing portfolio implementation and reveal interdependency effect can trigger some specific risks more often. This study proposes for the first time to measure and analyze project portfolio risk by a systematical model. It can help systematically assess and manage the complicated and interdependent risks associated with project portfolios.