Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning

We study the co-movement between innovative financial assets (i.e., FinTech-related stocks, green bonds and cryptocurrencies) and traditional assets. We construct a co-movement mode transmission network and discuss the network topology during the pre-COVID-19 and COVID-19 periods. We extract network topology information to predict the co-movement mode by machine learning algorithms. We further propose dynamic trading strategies based on the co-movement mode prediction. The empirical results show that (i) the evolution of co-movement is dominated by some key modes, and the mode transmission relies on intermediate modes and shows certain periodicity;(ii) the co-movement relationships are influenced by the ongoing COVID-19 outbreak;and (iii) the novel approach, which combines complex network and machine learning, is superior in co-movement mode prediction and can effectively bring diversification benefits. Our work provides valuable insights for market participants. © 2022 Elsevier B.V.

Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets

This paper proposes a novel interconnected multilayer network framework based on variance decomposition and block aggregation technique, which can be further served as a tool of linking and measuring cross-market and within-market contagion. We apply it to quantifying connectedness among global stock and foreign exchange (forex) markets, and demonstrate that measuring volatility spillovers of both stock and forex markets simultaneously could support a more comprehensive view for financial risk contagion. We find that (i) stock markets transmit the larger spillovers to forex markets, (ii) the French stock market is the largest risk transmitter in multilayer networks, while some Asian stock markets and most forex markets are net risk receivers, and (iii) interconnected multilayer networks could signal the financial instability during the global financial crisis and the COVID-19 crisis. Our work provides a new perspective and method for studying the cross-market risk contagion. © 2023 Elsevier Inc.

Assessing the management of patients with type 2 diabetes in Bangladesh during preand post-COVID-19 era and the implications: A pilot study

There is growing concern with the management of patients with type 2 diabetes (T2DM) across countries with suboptimal management increasing morbidity, mortality, and costs. In Bangladesh, the number of patients with diabetes will increase to an estimated 22.3 million by 2045, mainly T2DM, unless addressed. Alongside this, continued concerns with high rates of uncontrolled blood glucose levels as well as complication rates, including both microvascular and macrovascular complications in patients with T2DM in Bangladesh. This adds to the cost of care, which can be a concern among patients in Bangladesh with high co-payment rates. Alongside this, concerns with the impact of COVID-19 and associated lockdown measures on the care of these patients. Greater proactivity in managing these patients can help. Consequently, a need to ascertain what data is routinely collected in public hospitals in Bangladesh, including during the pandemic, to guide care. A pilot study was undertaken among eight patients in Chittagong Medical College using purposely designed case report forms to ascertain the extent of clinical information collected and their care against agreed target levels. There was typically poor control of blood glucose levels among the eight patients, which has resulted in increased prescribing of insulin. However, better control of blood pressure, lipids and urinary albumin levels. There were appreciable missing knowledge gaps, especially during the pandemic. This needs addressing. FUNDING There was no funding for this study or the write up of the study. © 2022. Farhana Akter et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

A Survey-based qualitative study to characterize expectations of software developers from five stakeholders

Background. Studies on developer productivity and well-being find that the perceptions of productivity in a software team can be a socio-Technical problem. Intuitively, problems and challenges can be better handled by managing expectations in software teams. Aim. Our goal is to understand whether the expectations of software developers vary towards diverse stakeholders in software teams. Method. We surveyed 181 professional software developers to understand their expectations from five different stakeholders: (1) organizations, (2) managers, (3) peers, (4) new hires, and (5) government and educational institutions. The five stakeholders are determined by conducting semi-formal interviews of software developers. We ask open-ended survey questions and analyze the responses using open coding. Results. We observed 18 multi-faceted expectations types. While some expectations are more specific to a stakeholder, other expectations are cross-cutting. For example, developers expect work-benefits from their organizations, but expect the adoption of standard software engineering (SE) practices from their organizations, peers, and new hires. Conclusion. Out of the 18 categories, three categories are related to career growth. This observation supports previous research that happiness cannot be assured by simply offering more money or a promotion. Among the most number of responses, we find expectations from educational institutions to offer relevant teaching and from governments to improve job stability, which indicate the increasingly important roles of these organizations to help software developers. This observation can be especially true during the COVID-19 pandemic. © 2021 IEEE Computer Society. All rights reserved.