Scientific Diversification Research Articles

Estimation of an efficient benchmark portfolio for the Eastern European market

Purpose: This paper explores the mean-variance inefficiency of cap-weighted indices based on the CECE index as a benchmark. Methodology: For the period from March 2014 to September 2021, several proxies of efficient portfo-lios were estimated: the Global Minimum Variance (GMV) portfolio, the Maximum Sharpe Ratio (MSR) portfolio and the portfolio with equal weights of constituents (EW). Diversification of strategies was also considered by analyzing the performance of a portfolio consisting of GMV and MSR that were weighted equally. Based on monthly data, 90 out-of-sample estimations were made for each strategy in order to com-pare their risk-return characteristics. Furthermore, to confirm the differences in the riskiness and returns of the estimated portfolios, the F-test and the Welch test were performed, respectively. Results: The results show that all analyzed portfolios achieved superior performance compared to the CECE index with the GMV portfolio leading the way. Conclusion: Research findings highlight the importance of market development and liquidity when pursu-ing popular scientific diversification methods.

Risk optimizations on basis portfolios: The role of sorting

This paper investigates the mean–variance and diversification properties of risk-based strategies executed on style or basis portfolios. We show that the performance of these risk strategies is highly sensitive to the sorting procedure used to form the basis assets. Whereas the extant literature provides mixed support for the outperformance of smart beta strategies based on scientific diversification, our designed strategies outperform both the market model and multifactor model. Our testing framework is based on bootstrapped mean–variance spanning tests and shows valid conclusions when controlling for multiple testing, transaction costs, and luck from random basis portfolio construction rules. Economically, our results are supported by diversification-based properties. • The dependent sorting procedure improves the efficiency of basis portfolios. • Low-risk optimizations on dependent basis portfolios outperform traditional portfolios. • Maximum diversification and minimum variance deliver very strong outperformance. • Smart betas on dependent portfolios span a larger set of traditional portfolios.

A methodology for developing scientific diversification strategy of countries

Identifying the strengths and weaknesses of the scientific system is a concern of scientific policymakers in each country. This research aimed to present a methodology to detect the strong and weak points of science in various countries by adopting the method of economic complexity. Subsequently, the formulation mode of scientific diversification strategies of different countries is introduced using the complexity approach. In this method, first the scientific diversity of each country and the ubiquity of scientific domains are calculated, and the fitness of the countries and the scientific complexity of the domains are accordingly estimated. Subsequently, the scientific domains creating the highest level of complexity, the least distance from the country and the most opportunity gain for that country are introduced as scientific productivity and strategy border of the country to diversify the scientific system of the country. Moreover, the strengths and weaknesses as well as diversification strategies of the Iranian scientific system have been presented as a case study. The findings showed that the scientific domains that emerge as the efficiency frontier of scientific capabilities can be used by countries’ policymakers for scientific diversification.

Knowledge and social relatedness shape research portfolio diversification

Scientific discovery is shaped by scientists’ choices and thus by their career patterns. The increasing knowledge required to work at the frontier of science makes it harder for an individual to embark on unexplored paths. Yet collaborations can reduce learning costs—albeit at the expense of increased coordination costs. In this article, we use data on the publication histories of a very large sample of physicists to measure the effects of knowledge and social relatedness on their diversification strategies. Using bipartite networks, we compute a measure of topic similarity and a measure of social proximity. We find that scientists’ strategies are not random, and that they are significantly affected by both. Knowledge relatedness across topics explains approx 10% of logistic regression deviances and social relatedness as much as approx 30%, suggesting that science is an eminently social enterprise: when scientists move out of their core specialization, they do so through collaborations. Interestingly, we also find a significant negative interaction between knowledge and social relatedness, suggesting that the farther scientists move from their specialization, the more they rely on collaborations. Our results provide a starting point for broader quantitative analyses of scientific diversification strategies, which could also be extended to the domain of technological innovation—offering insights from a comparative and policy perspective.

Learning and loving of nature in the Anthropocene

What does “belonging to nature” mean today and how can children and young people be inspired to experience this? What basic dilemmas and challenges arise between the requirement for critical thinking on the one side, and the experience of belonging and coexisting in nature on the other? In this article we will scrutinize the ideal of rational arguments and norms as stated in current policy documents and discuss how this best can promote curiosity and wonder, as well as a sense of relatedness and responsibility with nature that can inspire normative actions, We claim that critical thinking informed by a value-based ecology is needed to reveal the hidden curriculum of sustainable education; that is, a loss of “holistic” view in the footsteps of scientific diversification, a lack of curiosity and training of critical thinking, and a “denial of nature” characterized by a missed opportunity to raise the urgent attention towards environmental risks, that today should be a main mission in natural science education .

Bond Portfolio Optimization in the Presence of Duration Constraints

Although there exists an abundant literature on the benefits and limits of scientific diversification in the equity universe, little is known about the out-of-sample performance of portfolio optimization models in the fixed-income universe. In this article, the authors address two key challenges that are specific to bond portfolio optimization, namely, the presence of duration constraints and the presence of no-arbitrage restrictions on risk parameter estimates, for which no equivalent exists in the equity universe. In an application to sovereign bonds in the eurozone, they find that the use of portfolio optimization techniques based on robust estimators for risk parameters generates an improvement in investor welfare compared with the use of ad hoc bond benchmarks such as equally weighted or cap-weighted portfolios. These results are robust with respect to changes in the number of constituents in the portfolio and the rebalancing period, and in the presence of duration or weight constraints. <b>TOPICS:</b>Fixed income and structured finance, fixed-income portfolio management, statistical methods

Smart Equity Investing: Implementing Risk Optimization Techniques on Strategic Beta Portfolios

This paper investigates the mean-variance and diversification properties of risk-based strategies executed on style or basis portfolios. We show that the performance of these risk strategies is highly sensitive to the sorting procedure used to form the basis assets. Whereas the extant literature provides mixed support for the outperformance of smart beta strategies based on scientific diversification, our designed strategies outperform both the market model and multifactor model. Our testing framework is based on bootstrapped mean-variance spanning tests and shows valid conclusions when controlling for multiple testing, transaction costs, and luck from random basis portfolio construction rules. Economically, our results are supported by diversification-based properties.

The Scientific Competitiveness of Nations.

We use citation data of scientific articles produced by individual nations in different scientific domains to determine the structure and efficiency of national research systems. We characterize the scientific fitness of each nation—that is, the competitiveness of its research system—and the complexity of each scientific domain by means of a non-linear iterative algorithm able to assess quantitatively the advantage of scientific diversification. We find that technological leading nations, beyond having the largest production of scientific papers and the largest number of citations, do not specialize in a few scientific domains. Rather, they diversify as much as possible their research system. On the other side, less developed nations are competitive only in scientific domains where also many other nations are present. Diversification thus represents the key element that correlates with scientific and technological competitiveness. A remarkable implication of this structure of the scientific competition is that the scientific domains playing the role of “markers” of national scientific competitiveness are those not necessarily of high technological requirements, but rather addressing the most “sophisticated” needs of the society.