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Mathematics
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Applied Time Series and Artificial Intelligence in Economics and Finance
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Applied Time Series and Artificial Intelligence in Economics and Finance

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Financial Mathematics".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 5733

Special Issue Editor

Dr. Manuel Monge

E-Mail Website
Guest Editor
Faculty of Law, Business and Government, Universidad Francisco de Vitoria, 28223 Madrid, Spain
Interests: time series econometrics; applied econometrics; time series analysis; econometric modeling; financial economics

Special Issue Information

Dear Colleagues,

We would like to invite you to submit your latest research to this Special Issue, “Applied Time Series and Artificial Intelligence in Economics and Finance”, in the journal Mathematics. After suffering a pandemic (COVID-19) and with the current war that exists in Europe, between Russia and Ukraine, this Special Issue will provide an opportunity for researchers to present new trends and new concerns in the field of economics and finance by applying advanced techniques of time series and artificial intelligence that provide useful answers in the form of research papers.

Dr. Manuel Monge
Guest Editor

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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • applied mathematical and statistical approaches to economics and finance
  • applied econometrics
  • time series analysis
  • structural changes
  • artificial intelligence and machine learning algorithm
  • predictive models
  • economic and financial data analysis

Published Papers (5 papers)

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Research

14 pages, 1900 KiB  
Article
Consumer Sentiment and Luxury Behavior in the United States before and after COVID-19: Time Trends and Persistence Analysis
by Berta Marcos Ceron and Manuel Monge
Mathematics 2023, 11(16), 3612; https://doi.org/10.3390/math11163612 - 21 Aug 2023
Cited by 2 | Viewed by 1410
Abstract
This paper analyzes the stochastic properties of consumer sentiment to understand how they affected the luxury sector in the United States before and after COVID-19. The results were derived using fractional integration methodologies and suggest that, before the pandemic episode, both variables were [...] Read more.
This paper analyzes the stochastic properties of consumer sentiment to understand how they affected the luxury sector in the United States before and after COVID-19. The results were derived using fractional integration methodologies and suggest that, before the pandemic episode, both variables were expected to be mean reverting and the shocks were transitory, having similar behavior. However, after the appearance of COVID-19, results suggest that consumer sentiment recovered before the luxury sector. Results from the use of cointegration methodologies show that the effects of COVID-19 disappeared in the short-run. Finally, the sentiment of consumers acts as a leading indicator of the behavior of the luxury sector according to wavelet analysis. Thus, an increase in consumer sentiment implies an increase of 3.6% in the luxury sector. Full article
(This article belongs to the Special Issue Applied Time Series and Artificial Intelligence in Economics and Finance)
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10 pages, 307 KiB  
Article
Consumer Sentiment in the United States and the Impact of Mental Disorders on Consumer Behavior—Time Trends and Persistence Analysis
by Jesús Tomás Monge Moreno and Manuel Monge
Mathematics 2023, 11(13), 2981; https://doi.org/10.3390/math11132981 - 04 Jul 2023
Viewed by 722
Abstract
This paper analyzes the stochastic properties in clinical disorders to understand how they have manifested in consumer sentiment in the USA since 1990. The results obtained via fractional integration methodologies exhibit a high degree of persistence, finding non-mean reversion behavior in all of [...] Read more.
This paper analyzes the stochastic properties in clinical disorders to understand how they have manifested in consumer sentiment in the USA since 1990. The results obtained via fractional integration methodologies exhibit a high degree of persistence, finding non-mean reversion behavior in all of the time series analyzed, except for depressive disorder. Using a causality test, we find that mental and substance use disorders, anxiety disorder, schizophrenia, and alcohol use disorder influence consumer sentiment. Focusing on the cointegrating part, we conclude that an increase in the previously cited mental disorders produces a decrease in the Consumer Sentiment Index. Full article
(This article belongs to the Special Issue Applied Time Series and Artificial Intelligence in Economics and Finance)
12 pages, 310 KiB  
Article
Evidence of Inflation Using Harmonized Consumer Price Indices in Some Euro Countries: France, Germany, Italy, and Spain, along with the Euro Zone
by Raquel Ayestarán, Juan Infante, Juan José Tenorio and Luis Alberiko Gil-Alana
Mathematics 2023, 11(10), 2365; https://doi.org/10.3390/math11102365 - 19 May 2023
Viewed by 1080
Abstract
This paper deals with the analysis of the persistence in the Harmonized Indices of Consumer Prices in France, Germany, Italy, and Spain. The degree of persistence is measured through fractional integration or I (d) techniques, using monthly data from January 2010 to February [...] Read more.
This paper deals with the analysis of the persistence in the Harmonized Indices of Consumer Prices in France, Germany, Italy, and Spain. The degree of persistence is measured through fractional integration or I (d) techniques, using monthly data from January 2010 to February 2023. We first conducted the analysis with data ending in December 2019, that is, with data prior to the COVID-19 pandemic. Then, we extended the sample, first up to December 2021 and finally to February 2023. Our results show that the findings of our series are highly persistent, with values of the differencing parameter about one or higher than one in the majority of cases. In fact, mean reversion is only observed in the case of Germany with pre-pandemic data. Generally, we observed an increase in the degree of persistence of the series as a consequence of both the COVID-19 pandemic and the Russia–Ukraine war, with the only exception being Spain, where we observe a reduction in the order of integration when including 2022–2023 data. Full article
(This article belongs to the Special Issue Applied Time Series and Artificial Intelligence in Economics and Finance)
8 pages, 546 KiB  
Article
Coronavirus, Vaccination and the Reaction of Consumer Sentiment in The United States: Time Trends and Persistence Analysis
by Jesús Tomás Monge Moreno and Manuel Monge
Mathematics 2023, 11(8), 1851; https://doi.org/10.3390/math11081851 - 13 Apr 2023
Viewed by 909
Abstract
At the beginning of the COVID-19 pandemic, the entire world was waiting for a medical solution (for example, vaccines) in order to return to normality. Sanitary restrictions changed our consumption behaviors and feelings. Therefore, this paper analyzes the stochastic properties of consumer sentiment [...] Read more.
At the beginning of the COVID-19 pandemic, the entire world was waiting for a medical solution (for example, vaccines) in order to return to normality. Sanitary restrictions changed our consumption behaviors and feelings. Therefore, this paper analyzes the stochastic properties of consumer sentiment during the COVID-19 episode and the appearance of vaccines against the virus in December 2020 in the United States of America. This study adds a new dimension to the literature because it is the first research paper that uses advanced methodologies based on fractional integration and fractional cointegration analysis to understand the statistical properties of these time series and their behavior in the long term. The results using fractional integration methodologies exhibit a high degree of persistence, finding behavior of mean reversion during the pandemic episode. Therefore, the shock duration in consumer sentiment will be transitory, recovering to its previous trend in the short run. Focusing on the cointegrating part, we arrive at two main conclusions. First, an increase in total vaccination produces a positive reaction or impact on the behavior of consumers. On the other hand, an increase in new COVID-19 cases negatively affects the behavior of the consumer. Full article
(This article belongs to the Special Issue Applied Time Series and Artificial Intelligence in Economics and Finance)
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26 pages, 1750 KiB  
Article
Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment
by Rangan Gupta, Jacobus Nel and Christian Pierdzioch
Mathematics 2023, 11(6), 1371; https://doi.org/10.3390/math11061371 - 12 Mar 2023
Viewed by 950
Abstract
We use a quantile machine learning (random forests) approach to analyse the predictive ability of newspapers-based macroeconomic attention indexes (MAIs) on eight major fundamentals of the United States on the realized volatility of a major commodity-exporting emerging stock market, namely South Africa. We [...] Read more.
We use a quantile machine learning (random forests) approach to analyse the predictive ability of newspapers-based macroeconomic attention indexes (MAIs) on eight major fundamentals of the United States on the realized volatility of a major commodity-exporting emerging stock market, namely South Africa. We compare the performance of the MAIs with the performance of a news sentiment index (NSI) of the US. We find that both fundamentals and sentiment improve predictive performance, but the relative impact of the former is stronger. We document how the impact of fundamentals and sentiment on predictive performance varies across the quantiles of the conditional distribution of realized volatility, and across different prediction horizons. Specifically, fundamentals matter more at the extreme quantiles at short horizons, and at the median in the long-run. In addition, we report several robustness checks (involving sample period and alternative definitions of realized volatility), and indicate that the obtained results for South Africa also tend to carry over to other emerging countries such as, Brazil, China, India, and Russia. Our results have important implications for investors with volatility being an input for portfolio allocation decisions. In addition, with stock market variability also capturing financial uncertainty, its accurate prediction based on US fundamentals and sentiment also has a role in policy design to prevent possible collapse. Full article
(This article belongs to the Special Issue Applied Time Series and Artificial Intelligence in Economics and Finance)
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