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Applied Econometrics and Time Series Analysis (Volume II)
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Applied Econometrics and Time Series Analysis (Volume II)

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

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 7219

Special Issue Editor

Prof. Dr. Gulasekaran Rajaguru

E-Mail Website
Guest Editor
Bond Business School, Bond University, Gold Coast, QLD 4229, Australia
Interests: econometrics; time series analysis; irregular frequency models
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to publish a collection of papers that use cutting-edge econometric methods, using time series, cross-section, and panel data, to address issues in economics and finance. Both theoretical papers as well as papers with a focus on economic or financial applications are most welcome. Papers that develop new methods or validate the existing or new methods through simulation exercises or an applications of modern time series econometrics techniques will be particularly suitable for this Special Issue. The papers could also compare and contrast the traditional econometrics techniques with modern machine learning techniques with an application to economics and finance. 

Prof. Dr. Gulasekaran Rajaguru
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. 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 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

  • applied econometrics
  • time series analysis
  • panel data models
  • Monte Carlo simulation
  • bootstrapping
  • response surface functions
  • irregular frequency models
  • machine learning
  • causality and exogeneity
  • financial econometrics

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

16 pages, 5838 KiB  
Article
Assessing the Predictive Power of Transformers, ARIMA, and LSTM in Forecasting Stock Prices of Moroccan Credit Companies
by Karima Lahboub and Mimoun Benali
J. Risk Financial Manag. 2024, 17(7), 293; https://doi.org/10.3390/jrfm17070293 - 9 Jul 2024
Cited by 2 | Viewed by 4085
Abstract
In this paper, we present a data-driven approach to forecasting stock prices in the Moroccan Stock Exchange. Our study tests three predictive models: ARIMA, LSTM, and transformers, applied to the historical stock price data of three prominent credit companies (EQD, LES, and SLF) [...] Read more.
In this paper, we present a data-driven approach to forecasting stock prices in the Moroccan Stock Exchange. Our study tests three predictive models: ARIMA, LSTM, and transformers, applied to the historical stock price data of three prominent credit companies (EQD, LES, and SLF) listed on the Casablanca Stock Exchange. We carefully selected and optimized hyperparameters for each model to achieve optimal performance. Our results showed that the LSTM model achieved high accuracy, with R-squared values exceeding 0.99 for EQD and LES and surpassing 0.95 for SLF. These findings highlighted the effectiveness of LSTM in stock price forecasting. Our study offers practical insights for traders and investors in the Moroccan Stock Exchange, demonstrating how predictive modeling can aid in making informed decisions. This research contributes to advancing stock market forecasting in Morocco, providing valuable tools for navigating the Casablanca Stock Exchange. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis (Volume II))
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16 pages, 589 KiB  
Article
Financial Development, Financial Openness, and Policy Effectiveness
by Niraj P. Koirala, Hassan Anjum Butt, Jeffrey Zimmerman and Ahmed Kamara
J. Risk Financial Manag. 2024, 17(6), 230; https://doi.org/10.3390/jrfm17060230 - 29 May 2024
Cited by 1 | Viewed by 2700
Abstract
This study explores how financial development and openness influence the effectiveness of fiscal and monetary policies. An analysis of data from about 100 countries between 1980 and 2018 reveals that both financial openness and development weaken the impact of monetary and fiscal policies. [...] Read more.
This study explores how financial development and openness influence the effectiveness of fiscal and monetary policies. An analysis of data from about 100 countries between 1980 and 2018 reveals that both financial openness and development weaken the impact of monetary and fiscal policies. Our results further show that financial development in a country diminishes policy effectiveness depending on the country’s level of financial development; specifically, the more developed a country, the less effective the policies would be. Additionally, through a detailed examination employing a dynamic panel GMM approach, the study investigates the global repercussions of economic downturns in the US and how financial maturity shapes policy effectiveness during these times. We also discuss some policy implications that show that the positive impacts of monetary policy on output growth are lessened during crisis periods, and policymakers should act accordingly. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis (Volume II))
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