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We investigate institutional investors’ trading behavior of acquiring firm stocks surrounding merger activities for the period 1992–2001. We label investment companies and…
We investigate institutional investors’ trading behavior of acquiring firm stocks surrounding merger activities for the period 1992–2001. We label investment companies and independent investment advisors as active institutions and banks, nonbank trusts, and insurance companies as passive institutions. We analyze the trading behavior of active and passive institutions surrounding merger announcements and their eventual resolution. Our results indicate that active institutions significantly increase their holdings of acquiring firm stocks for mergers with higher announcement period abnormal return and this increase is more pronounced for stock mergers than cash mergers. Active institutions display preference for stock proposals at the merger announcement on the basis of their prior beliefs and this is explained by the “overreaction phenomenon.” However, they update their beliefs between announcement and final resolution as more information arrives into the market. Finally, active institutions appear to correct their overreaction behavior by displaying their greater preference for cash proposals as compared to stock proposals at the quarter of eventual outcome. The trading behavior of passive institutions suggests that these institutions disregard the market response of merger announcement in trading acquiring firm stocks at the announcement quarter. The passive institutions gradually update their beliefs and utilize the information released at the announcement in rebalancing their portfolios at the final resolution.
The setting up of e-university has been slow-going. Much of e-university slow progress has been attributed to poor business models, branding, disruptive technologies, lack…
The setting up of e-university has been slow-going. Much of e-university slow progress has been attributed to poor business models, branding, disruptive technologies, lack of organisational structure that accommodates such challenges, and failure to integrate a blended approach. One of the stumbling blocks, among many, is the handling of evaluation process. E-university models do not provide much automation compared to the original brick-and-mortar classroom model of delivery. The underlining technologies may not have been supportive; however, the conditions are changing, and more evaluation tools are becoming available for academics. The paper aims to discuss these issues.
This paper identifies the extent of current online evaluation processes. In this process, the team reviews the case study of a UK E-University using Adobe Connect learning model that mirrors much of the physical processes as well as online exams and evaluation tools. Using the Riva model, the paper compares the physical with the online evaluation processes for e-universities to identify differences in these processes to evaluate the benefits of e-learning. As a result, the models can help us to identify the processes where improvements can take place for automating the process and evaluate the impact of this change.
The paper concludes that this process can be significantly shortened and provide a fairer outcome but there remain some challenges for e-university processes to overcome.
This paper examines the vital quality assurance processes in academia as more universities move towards process automation, blended or e-university business models. Using the case study of Arden University online distance learning, the paper demonstrates, through modelling and analysis that the process of online automation of the evaluation process is achieved with significant efficiency.
This paper aims to examine the impact of the daily growth rate of COVID-19 cases in the USA (COVIDg), the Federal Fund Rate (FFR) and the trade-weighted US dollar index…
This paper aims to examine the impact of the daily growth rate of COVID-19 cases in the USA (COVIDg), the Federal Fund Rate (FFR) and the trade-weighted US dollar index (USDX) on S&P500 index daily returns and its 11 constituent sectors’ indices for the time period between January 22, 2020, until June 30, 2020.
The study uses the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model to gauge the impacts over the whole period of study, as well as over two sub-periods; first, January 22, 2020, until March 30, 2020, reflecting uncertainty in the US markets and second, from April 1, 2020, until June 30, 2020, reflecting the lockdown.
Results of the MGARCH model reveal a negative and significant relation between COVIDg and S&P500 index daily returns over the first sub-period and the whole study period in the following sectors, namely, communications, consumer discretionary, consumer staples, health, technology and materials. Yet, COVIDg showed a positive and significant relation with S&P500 index daily returns during the second time period in the following sectors, namely, communication, consumer discretionary, financial, industrial, information technology (IT) and utilities. Besides, USDX showed a negative significant effect on S&P500 index daily returns and on the daily return on each of its 11 constituent sectors over the second sub-period and the whole period. Further, FFR showed a significant effect only in the second sub-period, specifically, a negative effect on the daily return of the financial sector and a positive effect on the daily return of the technology sector index. Nevertheless, FFR had a positive significant effect on the daily return of the utilities sector index for the whole period under study.
The impact of the crisis on the S&P500 index can be assessed only with some limitations owing to available global data and the limited time frame of the lock-down.
The study proposes supporting a smooth, functioning and resilient financial system; increasing fiscal measures by the US Government to increase liquidity on constraints; measures by The Federal Reserve to alleviate US dollar funding shortages; support market integrity; ensure continuous transparency and sharing of information; support the health sector, as well as consumer-based sectors that faced demand shocks and facilitate investments in the technology sector.
The originality of this paper lies in the examination of the impact of the novel COVID-19 pandemic on each of the 11 sectors constituting the S&P500 index separately, reflecting how the main economic sectors formulating the US economy reacted to the shock during the peak time of the pandemic to observe a full picture of the economic consequences amid the pandemic.