Applied Econometrics and Time Series Analysis

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 March 2023) | Viewed by 11517

Special Issue Editor


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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. 

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

Published Papers (5 papers)

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Research

16 pages, 1907 KiB  
Article
Re-Examining Bitcoin’s Price–Volume Relationship: A Time-Varying Spectral Analysis
by Clement Moyo and Andrew Phiri
J. Risk Financial Manag. 2023, 16(7), 324; https://doi.org/10.3390/jrfm16070324 - 6 Jul 2023
Cited by 1 | Viewed by 2171
Abstract
This study employs continuous wavelet transforms to model the relationship between Bitcoin volume and prices across time and frequency space using daily data for the period between 17 September 2014 and 10 April 2023. The results show that Bitcoin price and volume have [...] Read more.
This study employs continuous wavelet transforms to model the relationship between Bitcoin volume and prices across time and frequency space using daily data for the period between 17 September 2014 and 10 April 2023. The results show that Bitcoin price and volume have a long-term relationship at low frequency cycles mostly during the period after 2019. A statistically insignificant relationship between the price and volume of Bitcoin is observed prior to 2019 which coincides with a time of limited regulatory oversight of Bitcoin markets globally. Positive correlation is observed in the aftermath of this period, with stronger correlation recorded during and post the period of the Covid-19 pandemic. Furthermore, the findings reveal that fluc-tuations in the Bitcoin volume tends to affect the price at higher frequency synchronizations (short-term); whereas, at lower frequencies (long-term), a feedback loop is observed, whereby the price changes lead to alterations in the volume. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis)
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25 pages, 1601 KiB  
Article
How Do Financial Market Outcomes Affect Gambling?
by Cyrus A. Ramezani and James J. Ahern
J. Risk Financial Manag. 2023, 16(6), 294; https://doi.org/10.3390/jrfm16060294 - 7 Jun 2023
Viewed by 2520
Abstract
A large literature in behavioral finance explores how gambling sentiments influences trading in stocks. This paper considers the reverse phenomena; the impact of financial market outcomes on aggregate gambling expenditures. We expect the wealth effect of higher realized stock returns will increase gambling [...] Read more.
A large literature in behavioral finance explores how gambling sentiments influences trading in stocks. This paper considers the reverse phenomena; the impact of financial market outcomes on aggregate gambling expenditures. We expect the wealth effect of higher realized stock returns will increase gambling (entertainment good). Similarly, we expect rising volatility will attract gamblers to equity markets seeking thrill and skewed payouts. Utilizing novel horse wagering data (1934–2020), we study the impact of these forces on gambling expenditures. Using corporate bond spreads as a proxy for business cycles, we find that, in addition to financial market outcomes, price of wagering, incomes, and availability of competing betting products are important drivers of gambling. We also find that, ceteris paribus, gambling rises during recessions. Our findings will be of interest to policy makers and the finance industry, particularly as day trading, sports betting, online casinos, and other gambling gains broad public acceptance. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis)
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13 pages, 618 KiB  
Article
Revisiting the Determinants of Consumption: A Bayesian Model Averaging Approach
by Pinar Deniz and Thanasis Stengos
J. Risk Financial Manag. 2023, 16(3), 190; https://doi.org/10.3390/jrfm16030190 - 10 Mar 2023
Viewed by 1268
Abstract
This study revisits the widely researched area of the consumption function using Bayesian Model Averaging (BMA) for a panel of EU countries to deal with the uncertainty of potential determinants, using the convergence club analysis to construct homogeneous groups by income. BMA suggests [...] Read more.
This study revisits the widely researched area of the consumption function using Bayesian Model Averaging (BMA) for a panel of EU countries to deal with the uncertainty of potential determinants, using the convergence club analysis to construct homogeneous groups by income. BMA suggests that income is the only variable that is found to be a strong determinant across different country groups, whereas other variables have varying importance for different country groups. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis)
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25 pages, 1803 KiB  
Article
An Empirical Examination of Asymmetry on Exchange Rate Spread Using the Quantile Autoregressive Distributed Lag (QARDL) Model
by Goktug Sahin and Afsin Sahin
J. Risk Financial Manag. 2023, 16(1), 38; https://doi.org/10.3390/jrfm16010038 - 6 Jan 2023
Cited by 3 | Viewed by 2783
Abstract
In economics, some transactions are conducted by the bid rate, and some are conducted by the ask rate. The spread between these two rates creates an essential cost and inefficiency for the economy. Taking these problems into account, the purpose of this study [...] Read more.
In economics, some transactions are conducted by the bid rate, and some are conducted by the ask rate. The spread between these two rates creates an essential cost and inefficiency for the economy. Taking these problems into account, the purpose of this study was to analyze the effects of macroeconomic and financial variables on the USD/TL exchange rate bid–ask spread for Türkiye using daily data spanning the period between 2 January 1990 and 2 August 2022. The quantile autoregressive distributed lag (QARDL) model was drawn upon to capture possible asymmetry in parameters and distinguish the results between different locations. The results obtained in this study may differ from the linear model and may change by the location, implying that the spread is reduced by the volume while it is increased by volatility and interest rates in the long run for some quantiles. Stock prices stir it in the long run, yet they decline it in the short run, indicating an asymmetry. Following the examples from the literature that analyzed the relationship via linear models, this paper employed a QARDL model for exploring location and sign asymmetry in the results for some quantiles. As the results indicate, efficiency in the bid–ask exchange rate spread can be controlled; therefore, it is our suggestion for policymakers to consider the extreme levels and asymmetry of the bid–ask exchange rate spread while evaluating its penetrating macro-financial variates. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis)
9 pages, 667 KiB  
Article
Stock Market Volatility Response to COVID-19: Evidence from Thailand
by Suthasinee Suwannapak and Surachai Chancharat
J. Risk Financial Manag. 2022, 15(12), 592; https://doi.org/10.3390/jrfm15120592 - 9 Dec 2022
Cited by 5 | Viewed by 2295
Abstract
This study investigated how stock market volatility responded dynamically to unexpected changes during the COVID-19 pandemic and the resulting uncertainty in Thailand. Using a multivariate GARCH-BEKK model, the conditional volatility dynamics, the interlinkages, and the conditional correlations between stock market volatility and the [...] Read more.
This study investigated how stock market volatility responded dynamically to unexpected changes during the COVID-19 pandemic and the resulting uncertainty in Thailand. Using a multivariate GARCH-BEKK model, the conditional volatility dynamics, the interlinkages, and the conditional correlations between stock market volatility and the increasing rate of COVID-19 infection cases are examined. The increased rate of COVID-19 infections impacts stock returns detrimentally; in Thailand, stock market volatility responses are asymmetric in the increase and decline situations. This disparity is due to the unfavourable impact of the pandemic’s volatility. Finally, we acknowledge that directional volatility spillover effects exist between the increase in COVID-19 cases and stock returns, suggesting that time-varying conditional correlations occur and are generally positive. Using this study’s results, governments and financial institutions can devise strategies for subsequent recessions or financial crises. Furthermore, investment managers can manage portfolio risk and forecast patterns in stock market volatility. Academics can apply our methodology in future investment trend studies to analyse additional variables in the economic system, such as the value of the US dollar, the price of commodities, or GDP. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis)
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