The COVID-19 forced to transform face-to-face mode of teaching to virtual in educational institutions around the globe that not only impact institutional stakeholders, but also posed as a threat to entire humanity because, all parties related to education had to change their activities. The intentions of this study therefore firstly, to determine the content analysis by interviewing tertiary students and secondly, to determine the frequency distribution by questionnaire developed from results of the content analysis. To better understand the consequences of this outbreak, we took an interview from forty respondents, including undergraduate and postgraduate students across Bangladesh. Results of Content analysis revealed that stakeholders of tertiary education are encountering severe problems in mental health, financial, technical, and study. A questionnaire was designed based on results were obtained through content analysis and distributed using email, WhatsApp, LinkedIn, Telegram, Facebook, and Instagram from May 20 to May 30, 2021. A total number of 505 valid questionnaires were received from respondents. Frequency distribution analysis disclosed that 60% respondents have no separate reading rooms. Laptops and desktops are commonly used for online classes, but unfortunately, 21% respondents have no personal electronic gadgets. Moreover, 55% reported spending less time to study during the coronavirus outbreak. Furthermore, 88% respondents reported experiencing mental health-related stress, anxiety, and depression problems. The proportion that suffered financial crisis, family disruptions, internet and technology related problems were 79%, 83% and 72% respectively. Since coronavirus pandemic is a totally new phenomenon in the world, not much empirical literature exist. So we fill the gap, investigating the issue empirically using content and frequency distribution analysis. Policy implications and recommendations are discussed accordingly.

This study explores the effect of fintech-driven inclusive finance on the profitability of banks using an unbalanced panel dataset from 660 banks across 40 developing countries between 2011 and 2021. We start with a fixed-effect estimate and subsequently validate our main findings using two-stage least squares (2SLS-IV), two-step system generalized method of moments (GMM), and generalized least squares (GLS) methodologies. Our analysis centers on three key profitability metrics: ROA, ROE, and NIM. Our findings suggest that fintech-backed inclusive finance boosts ROA by 9.10%, ROE by 18.87%, and NIM by 7.98%, highlighting the growing importance of mobile, internet, and agent banking in these nations. We also note that large banks benefit more from inclusive finance than small ones. Additionally, conventional banks see a more marked improvement in profitability than Islamic and savings banks. The relationship between inclusive finance and bank profitability is stronger in countries with higher GDP growth and those actively advancing financial inclusion through fintech, compared to countries with slower GDP growth and less emphasis on financial inclusion. When examining the interaction effects, the COVID-19 pandemic has further emphasized the positive connection between fintech and bank profitability. This suggests that fintech-driven inclusive finance can play a role in enhancing bank profitability, even in challenging times like the COVID-19 period. The transition towards fintech, however, mandates substantial investments, enhanced financial literacy, and heightened customer security, presenting persistent challenges for governments, policymakers, regulators, and financial institutions.

We examine the soundness of high-frequency trading (HFT) proxies that are widely defined on the limit order book (LOB) information. We use a unique TRTH (Thomson Reuters Tick History) millisecond time-stamped intraday trades and quotes dataset enriched with 10 levels of LOB depth messages for 149 highly fragmented LSE listed stocks for the period 2005 to 2016. We explore a sharp uptrend in HFT activities and accompanying improvement in market liquidity in the European market. We show that alternative HFT proxies built on LOB are not equally powerful. The HFT proxy defined on the five best LOB prices (the mid point of a typical limit order book) provides a better HFT identification than the one popularly defined on the first best prices (BBO). We suggest that picking the LOB information beyond a certain level (e.g., the best five prices) of market depth in developing HFT proxy is counterintuitive. Evidence indicates that high-frequency traders (HFTs) participate in both competitive (narrow) and passive (wider) quoting as a market making strategy; however, they do not participate in passive quoting excessively.