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M. Ángeles López-Cabarcos

Researcher at University of Santiago de Compostela

Publications -  48
Citations -  950

M. Ángeles López-Cabarcos is an academic researcher from University of Santiago de Compostela. The author has contributed to research in topics: Computer science & Stock market. The author has an hindex of 14, co-authored 36 publications receiving 427 citations. Previous affiliations of M. Ángeles López-Cabarcos include University of A Coruña.

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Bitcoin volatility, stock market and investor sentiment. Are they connected?

TL;DR: In this article, the authors analyzed the Bitcoin behavior and the effect that investor sentiment, S&P 500 returns, and VIX returns have on Bitcoin volatility using GARCH and EGARCH models.
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The influence of investor sentiment on the green bond market

TL;DR: In this article, the influence of social networks on the green bond market was analyzed using panel data analysis, and the results of this study should lead investors and markets to consider social networks as relevant sources of information not only for the equity market but also for the bond market.
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The Influence of Organizational Justice and Job Satisfaction on Organizational Commitment in Portugal’s Hotel Industry:

TL;DR: In this article, a survey of employees at four and five-star hotels in the north of Portugal found that employees who feel they are treated fairly may develop higher levels of job satisfaction, and, in turn, higher level of organizational commitment.
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All that glitters is not gold. The rise of gaming in the COVID-19 pandemic

TL;DR: In this paper, a logit-probit model was used to analyze the relationship between financial (VIX, S&P GSCI Gold Index) and social (worldwide daily variation in total deaths from COVID-19 and worldwide Google attention on coronavirus) variables.
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Innovation, entrepreneurship and knowledge in the business scientific field: Mapping the research front

TL;DR: In this paper, the authors analyze the current research front at the intersection of the three concepts in business research, through a bibliometric study based on performance metrics, bibliographic coupling and word co-occurrence analysis.