PurposeCOVID-19 evolved from a local health crisis to a pandemic and affected countries worldwide accordingly. Similarly, the impacts of the pandemic on the performance of global stock markets could be time-varying. This study applies a dynamic network analysis approaches to evaluate the evolution over time of the impact of COVID-19 on the stock markets' network.Design/methodology/approachDaily closing prices of 55 global stock markets from August 1, 2019 to September 10, 2020 were retrieved. This sample period was further divided into nine subsample periods for dynamic analysis purpose. Distance matrix based on long-range correlations was calculated, using rolling window's length of 100 trading days, rolled forward at an interval of one month's working days. These distance matrices than used to construct nine minimum spanning trees (MSTs). Network characteristics were figured out, community detection and network rewiring techniques were also used for extracting meaningful from these MSTs.FindingsThe findings are, with the evolution of COVID-19, a change in co-movements amongst stock markets' indices occurred. On the 100th day from the date of reporting of the first cluster of cases, the co-movement amongst the stock markets become 100% positively correlated. However, the international investor can still get better portfolio performance with such temporal correlation structure either avoiding risk or pursuing profits. A little change is observed in the importance of authoritative node; however, this central node changed multiple times with change of epicenters. During COVID-19 substantial clustering and less stable network structure is observed.Originality/valueIt is confirmed that this work is original and has been neither published elsewhere, nor it is currently under consideration for publication elsewhere.
The selection criteria play an important role in the portfolio optimization using any ratio model. In this paper, the authors have considered the mean return as profit and variance of return as risk on the asset return as selection criteria, as the first stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been considered to be the optimization ratio model. In this regard, the historical data taken from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique has been developed, with financial tool box available in MATLAB and the particle swarm optimization (PSO) algorithm. Hence, called as the hybrid particle swarm optimization (HPSO) or can also be called as financial tool box particle swarm optimization (FTB-PSO). In this model, the budgets as constraint, where as two different models i.e. with and without short sale, have been considered. The obtained results have been compared with the existing literature and the proposed technique is found to be optimum and better in terms of profit.
Social computing and online groups have accompanied in a new age of the network, where information, networking and communication technologies are enabling systematized human efforts in primarily innovative ways. The social network communities working on various social network domains face different hurdles, including various new research studies and challenges in social computing. The researcher should try to expand the scope and establish new ideas and methods even from other disciplines to address the various challenges. This idea has diverse academic association, social links and technical characteristics. Thus it offers an ultimate opportunity for researchers to find out the issues in social computing and provide innovative solutions for conveying the information between social online groups on network computing. In this research paper we investigate the different issues in social media like users' privacy and security, network reliabilities, and desire data availability on these social media, users' awareness about the social networks and problems faced by academic domains. A huge number of users operated the social networks for retrieving and disseminating their real time and offline information to various places. The information may be transmitted on local networks or may be on global networks. The main concerns of users on social media are secure and fast communication channels. Facebook and YouTube both claimed for efficient security mechanism and fast communication channels for multimedia data. In this research a survey has been conducted in the most populated cities where a large number of Facebook and You-Tube users have been found. During the survey several regular users indicate the certain potential issues continuously occurred on these social web sites interfaces,
Objective: To compare the effects of antiviral therapy such as sofosbuvir and daclatasvir in HCV patients which were diagnosed by HCV-RNA PCR without Diabetes Melitis. Study Design: Cross-sectional comparative study Inclusion Criteria: HCV Positive patients after PCR test conformation between 20-75 years age. Methodology: In this cross-sectional analysis total of 100 Hepatitis c infected patients selected, Sofosbuvir plus Daclatasvir treatment given for 03 months period. Different parameters were recorded such as Total Bilirubin, Direct Bilirubin, Indirect Bilirubin, Hb levels, Serum ALT levels, and Serum ALP level. The statistical relation of the mentioned variables was analyzed through SPSS version 15. Results: Out of a total of 100 patients, 47% (47) were males, 53% (53) were females, 44% (44) patients had a history of prior interferon therapy, 23% (23) patients were having low hemoglobin levels before starting treatment. Both groups completed oral antiviral treatment for 12 weeks & resulting data showed the equality of treatment on group B and group A as no decrease in hemoglobin (p=0.799), ALT normalization (p=1.000) & no rise in serum bilirubin (p=0.817) during 1st month of treatment was noted in both groups while the SVR noted of both groups also showed no significant difference to each other i.e. 92% & 94 % (p=0.696). Conclusion: This study concluded to monitor the anti-viral drug response against HCV patients.
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