Special Issue "Wavelet Applications in Finance"

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Economics and Finance".

Deadline for manuscript submissions: 6 December 2021.

Special Issue Editor

Prof. Dr. Alessandra Canepa
E-Mail Website
Guest Editor
Department of Economics and Statistics Cognetti De Martiis, University of Turin, Lungo Dora Siena 100/A, 10153 Turin, Italy
Interests: econometrics; financial econometrics; climate change econometrics

Special Issue Information

Dear Colleagues,

Although wavelet methods have been heavily used in other disciplines such as acoustics, astronomy, engineering, medicine, forensics, and physics, applications in economics and finance are relatively new. Wavelet decomposition methods are robust to nonlinearity and structural breaks in the series under investigation and could be used to analyse market behaviour in situations of market distress. Additionally, a key feature of wavelets relates to their capacity to uncover latent processes that affect the structural behaviour of the series, such as cycle patterns, trends, and lead–lag interactions, which are characteristic features of financial time series.

The aim of the Special Issue is to investigate the usefulness of wavelet methods in financial applications. Potential applications of wavelet analysis in finance are in density estimation, time scale decomposition, and forecasting. Empirical studies analysing the forecasting properties of models generated using wavelet decomposition would be particularly welcome.  The study of financial contagion and risk management using wavelet methodology is also of interest.

Prof. Dr. Alessandra Canepa
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 papers will be 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. Journal of Risk and Financial Management is an international peer-reviewed open access monthly 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 1200 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

  • wavelet decomposition
  • wavelet forecasting
  • financial market contagion
  • risk management using wavelet.

Published Papers (2 papers)

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Research

Article
Evidence of Stock Market Contagion during the COVID-19 Pandemic: A Wavelet-Copula-GARCH Approach
J. Risk Financial Manag. 2021, 14(7), 329; https://doi.org/10.3390/jrfm14070329 - 15 Jul 2021
Cited by 1 | Viewed by 441
Abstract
In this study, we propose a wavelet-copula-GARCH procedure to investigate the occurrence of cross-market linkages during the COVID-19 pandemic. To explore cross-market linkages, we distinguish between regular interdependence and pure contagion, and associate changes in the correlation between stock market returns at higher [...] Read more.
In this study, we propose a wavelet-copula-GARCH procedure to investigate the occurrence of cross-market linkages during the COVID-19 pandemic. To explore cross-market linkages, we distinguish between regular interdependence and pure contagion, and associate changes in the correlation between stock market returns at higher frequencies with contagion, whereas changes at lower frequencies are associated with interdependence that relates to spillovers of shocks resulting from the normal interdependence between markets. An empirical analysis undertaken on six major stock markets reveals evidence of long-run interdependence between the markets under consideration before the start of the COVID-19 pandemic in December 2019. However, after the health crisis began, strong evidence of pure contagion among stock markets was detected. Full article
(This article belongs to the Special Issue Wavelet Applications in Finance)
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Article
Time-Varying Nexus between Investor Sentiment and Cryptocurrency Market: New Insights from a Wavelet Coherence Framework
J. Risk Financial Manag. 2021, 14(6), 275; https://doi.org/10.3390/jrfm14060275 - 18 Jun 2021
Viewed by 451
Abstract
This study attempts to investigate the nexus between investor sentiment and cryptocurrencies prices. Our empirical investigation merges bivariate and multivariate wavelet tools to examine the investor sentiment nexus to inter-cryptocurrencies prices. The study outcomes show that the Sentix Investor Confidence index provides significant [...] Read more.
This study attempts to investigate the nexus between investor sentiment and cryptocurrencies prices. Our empirical investigation merges bivariate and multivariate wavelet tools to examine the investor sentiment nexus to inter-cryptocurrencies prices. The study outcomes show that the Sentix Investor Confidence index provides significant information in explaining long-term changes in Bitcoin and Litecoin prices. Moreover, the findings generated from the multiple wavelet coherence illustrate the simultaneous contribution of cryptocurrencies and the Sentix Investor Confidence index in explaining the Bitcoin index movement across frequencies and over horizons, especially during bubble burst periods. The study also suggests a time-dependent relationship of Bitcoin prices with alternative cryptocurrencies and the Sentix Investor Confidence index, mostly pronounced during the Bitcoin bubble. We discuss our results using GSV-based investor sentiment. Our findings remain robust and confirm the strong predictive power of investor sentiment in cryptocurrencies price movements over time and across scales. Full article
(This article belongs to the Special Issue Wavelet Applications in Finance)
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