Muhammad Tahir Suleman, Umaid A Sheikh, Emilios C. Galariotis, David Roubaud
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引用次数: 0
Abstract
This article is the first one to examine the moderating role of bitcoin sentiment indices on the short term and long-term time–frequency-based good and bad network connectedness of all US sectors. In more detail, the paper quantifies the above relationship between the 11 US sectoral high frequency returns and then identifies the moderating impact of bitcoin investors’ fear and greed sentiment on good and bad network connectedness during pre-Covid-19 and Covid-19. For the said purpose, we decompose the returns into good and bad volatility, and rely on time and frequency dependent spillover measures and quantify a spillover symmetrical and asymmetrical measure for network connectedness for different investment horizons. Furthermore, we also quantify the NET good–bad volatility transmission and reception capability of all our sectors within the frequency dependent network. The extracted good and bad network connectedness indices are then regressed on multiple thresholds of bitcoin sentiment indices. Quantile regression results revealed that fear, extreme fear, greed and extreme greed moderate the short term and long term good and bad volatility spillovers within the network connectedness. Finally, we also utilize hedge ratios and optimal portfolio weight selection strategies to explain whether short positioning in the US sectoral returns can be used to hedge against bitcoin sentiment risk.
期刊介绍:
The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications.
In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.