Special Issue "Special Issue on Time Series Econometrics"

A special issue of Econometrics (ISSN 2225-1146).

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 1483

Special Issue Editors

Alessandra Luati
E-Mail Website
Guest Editor
Dipartimento di Scienze Statistiche “Paolo Fortunati”, University of Bologna, 40126 Bologna BO, Italy
Interests: time series analysis; frequency domain methods; score-driven models; locally stationary processes; statistical inference for quantum mechanics: information theory
Claudio Morana
E-Mail Website
Guest Editor
Dipartimento di Economia, Metodi Quantitativi e Strategie di Impresa, University of Milano- Bicocca, 20126 Milano, MI, Italy
Interests: linear and nonlinear large-scale time series models; macro, financial, and climate change econometrics; the macrofinance interface and boom–bust macrofinancial cycles
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Special Issue Information

Dear Colleagues,

This Special Issue aims to discuss advances in time series econometrics from both a theoretical and applied perspective. We solicit the submission of papers whose novelty stems from the development and introduction of new time series econometric models. Concerning applied works, the issue is welcoming applications to macroeconomic and financial analysis, their interface, and contributions relevant for policy evaluation. We also welcome papers dealing with the COVID-19 pandemic. We particularly welcome submissions highlighting interesting statistical challenges to which time series econometric methods can contribute.

Prof. Dr. Alessandra Luati
Prof. Dr. Claudio Morana
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Econometrics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • time series analysis
  • frequency and time domain methods
  • univariate and multivariate analysis
  • macroeconomic and financial applications of time series analysis
  • COVID-19 applications of time series analysis

Published Papers (1 paper)

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Research

Article
Impact of COVID-19 Pandemic News on the Cryptocurrency Market and Gold Returns: A Quantile-on-Quantile Regression Analysis
Econometrics 2022, 10(2), 26; https://doi.org/10.3390/econometrics10020026 - 02 Jun 2022
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Abstract
In this paper, we investigate the relationship between the RavenPack news-based index associated with coronavirus outbreak (Panic, Sentiment, Infodemic, and Media Coverage) and returns of two commodities—Bitcoin and gold. We utilized the novel quantile-on-quantile approach to uncover the dependence between the news-based index [...] Read more.
In this paper, we investigate the relationship between the RavenPack news-based index associated with coronavirus outbreak (Panic, Sentiment, Infodemic, and Media Coverage) and returns of two commodities—Bitcoin and gold. We utilized the novel quantile-on-quantile approach to uncover the dependence between the news-based index associated with coronavirus outbreak and Bitcoin and gold returns. Our results reveal that the daily levels of positive and negative shocks in indices induced by pandemic news asymmetrically affect the Bearish and Bullish on Bitcoin and gold, and fear sentiment induced by coronavirus-related news plays a major role in driving the values of Bitcoin and gold more than other indices. We find that both commodities, Bitcoin and gold, can serve as a hedge against pandemic-related news. In general, the COVID-19 pandemic-related news encourages people to invest in gold and Bitcoin. Full article
(This article belongs to the Special Issue Special Issue on Time Series Econometrics)
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