The media and election campaign managers conduct several polls in the days leading up to the presidential elections. These preelection polls have a different predictive capacity, despite the fact that under a Big Data approach, sources that indicate voting intention can be found. In this article, we propose a free method to anticipate the winner of the presidential election based on this approach. To demonstrate the predictive capacity of this method, we conducted the study for two countries: the United States of America and Canada. To this end, we analysed which candidate had the most Google searches in the months leading up to the polling day. In this article, we have taken into account the past four elections in the United States and the past five in Canada, since Google first published its search statistics in 2004. The results show that this method has predicted the real winner in all the elections held since 2004 and highlights that it is necessary to monitor the next elections for the presidency of the United States in November 2020 and to have more accurate information on the future results.
Since the 1960s, Halal industry and Islamic Finance have grown in parallel without implementing adequate synergies. Halal tourism is a fast-growing sector of Halal industry, and the connection with Islamic Finance has hardly been researched. The aim of this paper is to analyse whether Islamic Finance can play an active role in developing Halal Tourism. This topic has not been empirically researched in the literature. The methodology is based on a fuzzy hybrid multi-criteria method that satisfactorily handles the imprecise nature associated with the information provided by Likert scales. Our results show how culture has a direct moderating effect on the degree of agreement that respondents have over the active role that IF can play, finding that English respondents agree more than Spanish and Arabs respondents. Similarly, our results also show that the knowledge of the Halal concept makes respondents agree more with the active role of Islamic finance. This study provides insights to the main stakeholders, and it can be strategically used to foster adequate synergy between Islamic Finance and the development of Halal tourist products as a way to specialize in a more sustainable tourism.
This article analyses the impact of Economic Policy Uncertainty (EPU) on the credit risk of US commercial banks considering their size, profitability and solvency. To achieve this goal, a sample of 2994 US commercial banks was selected for the period 2017-2019. Using panel data, the results reveal a statistically significant positive relationship between EPU and credit risk of US commercial banks. Banks of less profitability and less solvency were found to be more vulnerable to the effect of EPU on credit risk. No conclusive results were found regarding the impact of bank size on vulnerability to EPU. Overall, our evidence suggests that policy makers and bank managers should consider the effect of EPU on their decisions.
Summary The attempt to measure investors’ mood to find an early indicator of financial markets has evolved and developed with the advancement of technology over the years. The first attempts were based on surveys, a long and expensive process. Nowadays, big data has made it possible to measure the investor’s mood accurately and almost entirely online. This paper analyzes the explanatory and predictive capacity of Wikipedia pageviews for the Nasdaq index. For this purpose, two econometric models have been developed. In both models, the explanatory variable is the number of Wikipedia visits, and the endogenous variable is Nasdaq index return. As an alternative to this approach, an algorithmic trading system has been developed. It uses Wikipedia visits as investment signals for long and short positions to check the predictability power of this indicator. It is determined that the volume of queries about Nasdaq companies is a statistically significant variable for expressing the evolution of this index. However, it has no predictive capacity. Keeping in mind the capacity of Wikipedia to exemplify Nasdaq trends, further studies should be conducted to determine how to make this indicator profitable.
In recent years, one of the main priorities of companies has been to adapt their business activity and commercial strategy to be aligned with the 17 Sustainable Development Goals (SDGs) established by the United Nations, in its “2030 Agenda”. To overcome this challenge, companies develop and implement Corporate Social Responsibility (CSR) strategies. One of the objectives that have generated the most interest is Goal 5 dedicated to promoting gender equality. This study analyzes the gender equality evolution in companies as part of CSR through Change Management (CM). To do this, a longitudinal study was carried in the last ten years with an analysis of the content of various reports from four of the most important banks in Spain. The results corroborate the growing interest of the largest Spanish financial institutions in gender equality. Being women's access to employment, salary gap information, and the presence of women on the board of directors a priority. Likewise, the CM appears as a lever for the achievement of the SDGs by the entities, gaining relevance in recent years, and being linked to the strategic approach and business objectives for the development of CSR.
This paper examines the predictive power of Google trends on the grain's futures price movement. The aim was to validate if an algorithmic trading system designed was profitable and able of beating the market. In the research was used data from soybean futures and corn futures, both contracts are listed in the Chicago Mercantile Exchange. The results of the research show that its forecasting power is high when predicting soybean futures and corn futures prices. According to the findings, the formulation of such predictive analysis is a good option for individual traders, investors, and commercial firms.
En esta investigación se analiza la utilización de las noticias de actualidad de prensa especializada como herramienta didáctica activa. En el marco del enfoque por competencias, metodología activa y participativa centrada en el estudiante, las rúbricas de evaluación aparecen como herramientas que aportan transparencia al proceso y son idóneas para evaluar las competencias en el aula. En concreto, la competencia transversal de análisis y síntesis permite identificar los elementos clave en una situación y las noticias de actualidad se muestran como una herramienta didáctica que crea un ambiente propicio para el aprendizaje, al tiempo que supone una aproximación constructivista a las competencias. Dados estos tres elementos, se planteó a estudiantes universitarios de Economía de la Empresa una tarea de análisis y síntesis de noticias de actualidad y se valoraron diversos aspectos sobre su grado de conformidad, motivación, interés y utilidad percibida. Los resultados muestran una predisposición de los estudiantes muy favorable a la utilización de noticias que vinculen la realidad socioeconómica con sus conocimientos académicos.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.