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.

Reinforcement Learning for Generating Secure Configurations

Many security problems in software systems are because of vulnerabilities caused by improper configurations. A poorly configured software system leads to a multitude of vulnerabilities that can be exploited by adversaries. The problem becomes even more serious when the architecture of the underlying system is static and the misconfiguration remains for a longer period of time, enabling adversaries to thoroughly inspect the software system under attack during the reconnaissance stage. Employing diversification techniques such as Moving Target Defense (MTD) can minimize the risk of exposing vulnerabilities. MTD is an evolving defense technique through which the attack surface of the underlying system is continuously changing. However, the effectiveness of such dynamically changing platform depends not only on the goodness of the next configuration setting with respect to minimization of attack surfaces but also the diversity of set of configurations generated. To address the problem of generating a diverse and large set of secure software and system configurations, this paper introduces an approach based on Reinforcement Learning (RL) through which an agent is trained to generate the desirable set of configurations. The paper reports the performance of the RL-based secure and diverse configurations through some case studies.

Analysis of diversification benefits for cryptocurrency portfolios before and during the COVID-19 pandemic

Purpose This study aims to investigate the diversification benefits attached to the crypto portfolios when combined with stocks, Forex instruments and commodity assets. Design/methodology/approach Markowitz diversification techniques have been used to analyze the risk-return tradeoffs of the individual portfolios. Daily prices on cryptocurrencies and the selected asset classes, cover the period before and during the pandemic COVID-19. The portfolio risk of the portfolios was calculated by identical techniques and analyzed with equal criteria. Findings The results with 270 trails indicate that stocks on average reduce the portfolio risk of crypto portfolios by 36% followed by fiat currency with 30.9% and commodities by 20.8%. Average daily returns stand in line with the standard portfolio theories where riskier portfolios offer higher returns and the other way around. Originality/value The authors contribute to the current literature by investigating the portfolio risk attached to the crypto portfolios when stocks, commodities and Forex instruments were added separately. To this end, results inform not only retail investors but also portfolio managers on the asset classes that generate better optimization for crypto portfolios.

Pemberdayaan Pokdakan Mina Usaha Rumbai Bukit dalam pengolahan mie kaya nutrisi untuk meningkatkan imunitas tubuh di masa pandemi

Pandemic in the form of Covid-19 is a new type of disease caused by SARS-CoV-2 virus or Corona virus which can cause health problems in the form of respiratory system disorders, starting from mild symptoms such as flu, to lung infections, such as pneumonia. To maintain body immunity against Covid 19, nutritious food ingredients in the form of catfish are needed. Catfish is a type of fish that has a high economic value, where apart from being easy to cultivate, this fish also contains very high nutrients, namely 17.63% protein, 1.07% ash, 2.23% fat (DW), 12.14%, fat (WW), moisture content 81.57%, 47.15% saturated fatty acids, MUFA 40.41%, PUFA 12.45%. Therefore, it is very good for consumption during a pandemic. However, not everyone likes to consume catfish fresh, so it is processed in the form of catfish noodles. To increase consumer preference for catfish noodles, natural dyes from spinach and carrots are added which will give green and orange colors and attract consumers, so that ultimately nutrient-rich noodles are produced. This activity was carried out with 10 participants by implementing health protocols that aim to provide insight and practical knowledge to community groups in Rumbai Bukit Village, Rumbai District about fish noodle processing techniques so that they can increase family income, especially during the pandemic. The enthusiasm of the participants was very high so that the activity went smoothly. From the post-test results, it was found that 100% of the participants had understood the diversification techniques of fishery product processing.

Modeling the optimal diversification opportunities: the case of crypto portfolios and equity portfolios

Purpose This study aims to compare the diversification risk of the crypto portfolio with those of equity portfolios. For this purpose, the hypothetical index was constructed with 20 cryptocurrencies that hold the highest market capitalization in the Coin Market Cap database, named as the Crypto-Index 20. Design/methodology/approach The portfolio diversification techniques were used to identify risk linked with the six largest European equity indexes and compared with the Crypto-Index 20. Indexes were considered as an independent portfolio while analysis was completed separately for each of them. Data concerning stock prices and their trade volume were collected from the Thomson Reuters Eikon database while crypto prices and their trade volume from the Coin Market Cap database. The diversification risk of the stock indexes was measured separately for each portfolio with the same risk techniques and the same methodological process. Findings Research results indicate that Crypto-Index 20 on average was 76 times riskier than FTSE 100, 55 times riskier than FTSE MIB, 44 times riskier than IBEX 35, 10 times riskier than CAC 40 and 9 times riskier than DAX and MDAX. Crypto-Index 20 comprises a stronger positive correlation and is exposed to higher volatility than six selected European equity indexes. Originality/value This research provides practical implications for the investors on the diversification benefits and risks attached to the cryptocurrencies portfolio by comparing it with the traditional equity portfolios. From a policy perspective, regulators might obtain information on the risk properties involved into cryptocurrencies and the possibility of creating an optimal portfolio.

Evaluation of Diversification Techniques for Legal Information Retrieval

"Public legal information from all countries and international institutions is part of the common heritage of humanity. Maximizing access to this information promotes justice and the rule of law". In accordance with the aforementioned declaration on Free Access to Law by Legal information institutes of the world, a plethora of legal information is available through the Internet, while the provision of legal information has never before been easier. Given that law is accessed by a much wider group of people, the majority of whom are not legally trained or qualified, diversification techniques, should be employed in the context of legal information retrieval, as to increase user satisfaction. We address diversification of results in legal search by adopting several state of the art methods from the web search, network analysis and text summarization domains. We provide an exhaustive evaluation of the methods, using a standard data set from the Common Law domain that we subjectively annotated with relevance judgments for this purpose. Our results i) reveal that users receive broader insights across the results they get from a legal information retrieval system, ii) demonstrate that web search diversification techniques outperform other approaches (e.g., summarization-based, graph-based methods) in the context of legal diversification and iii) offer balance boundaries between reinforcing relevant documents or sampling the information space around the legal query.