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A special issue of Economies (ISSN 2227-7099).

Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 14949

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Prof. Dr. Wing-Keung Wong

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Guest Editor

Department of Finance, Fintech & Blockchain Research Center, and Big Data Research Center Asia University, Taichung 41354, Taiwan
Interests: Financial Economics; Econometrics; Mathematical Finance; Mathematical Economics; Equity Analysis; Investment Theory; Risk Management; Behavioral Finance; Behavioral Economics; International Business; International Finance
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Prof. Dr. Faridul Islam

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Guest Editor

Department of Economics, Morgan State University, Baltimore, MD 21251, USA
Interests: energy; mathamatical modelling; energy finance; energy pricing; carbon pricing; time series analysis; forecasting
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Special Issue Information

Dear Colleagues,

Mathematics and computation play a vital role in Finance and Economics, providing widely used theories and tools.

Most mathematical and computational models are developed by using advanced mathematics, probability, and statistics. Mathematical and computational models are essential for developing theories in Financial Economics; their validity is tested through the analysis of empirical real-world data.

“Financial Economics: theory and applications”, edited by Wing-Keung Wong, will be devoted to advancements in the theories of Financial Economics, with applications in different areas of this field. This Special Issue will also bring together practical, state-of-the-art applications of mathematics, probability, statistics, and computational techniques in Financial Economics.

We invite investigators to contribute original research articles that advance the use of mathematics, probability, statistics, and computational techniques in the area of Financial Economics. All submissions must contain original unpublished work that is not being considered for publication elsewhere.

Prof. Dr. Wing-Keung Wong
Prof. Dr. Faridul Islam
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. Economies 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

Mathematics
Probability
Statistics
Computation
Finance
Economics
Applications

Published Papers (6 papers)

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Research

Open AccessArticle

Analysing Monetary Policy Shocks by Sign and Parametric Restrictions: The Evidence from Russia

Bünyamin Fuat Yıldız

Korhan K. Gökmenoğlu

and

Wing-Keung Wong

Economies 2022, 10(10), 239; https://doi.org/10.3390/economies10100239 - 26 Sep 2022

Cited by 1 | Viewed by 1075

Abstract

Most, if not all, of the studies in the existing literature that have examined the impacts of monetary policy implications on macroeconomic aggregates suffered from misleading impulse responses. To overcome the limitations in the existing literature and to fill the gap in the literature, this study applies the new Keynesian model by imposing the sign and parametric restrictions to investigate the effects of policy shocks on the economic aggregates for Russia by implementing SVARs, yielding a better understanding of the impacts of monetary policy shocks on the Russian economy and proving superior to other existing methods. Our approach avoids impulse response anomalies such as the price puzzle and eludes implausible overshooting responses to the subjected innovations by using prior information. Our findings indicate that although monetary policy shocks create a significant decrease in inflation in the short run within both median target responses and median responses, they have a tolerable negative effect on the output gap. On the other hand, demand shocks do not generate a significant rise in output but create inflation, while cost–push shocks generate significantly detrimental results in both inflation and output. The results draw a further step towards validating the new Keynesian theory in the Russian case by revealing the short-run nonneutrality of monetary policy intervention. Our findings also showed that the cost–push shocks have significant damaging effects on both inflation and output and that interest rates strongly respond to both cost–push and demand shocks. Our findings successfully solve the price puzzle problem, justify the new Keynesian theory that holds that monetary policy shocks only have a short-run effect, and imply that Volcker–Greenspan’s rule could be a useful guide for policy makers to solve the problem efficiently. In addition, our findings can be used to make important policy recommendations for policy makers as discussed in the conclusion section. Full article

(This article belongs to the Special Issue Financial Economics: Theory and Applications)

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Open AccessArticle

Corporate Social Responsibility and Product Market Power

Chong-Chuo Chang

Han Yang

and

Kun-Zhan Hsu

Economies 2022, 10(6), 151; https://doi.org/10.3390/economies10060151 - 20 Jun 2022

Cited by 1 | Viewed by 1271

Abstract

This study explores the impact of corporate social responsibility (CSR) on the product market power by examining listed firms on the Taiwan Stock Exchange and Taipei Exchange from 2005 to 2017. We use CSR awards as a social responsibility indicator, and the results show a positive relationship between CSR and excess price-cost margins (market share), supporting the thesis that firms that value CSR activities can strengthen the competitive advantage of products in the market. Full article

(This article belongs to the Special Issue Financial Economics: Theory and Applications)

Open AccessArticle

Sustainable Growth Rate and ROE Analysis: An Applied Study on Saudi Banks Using the PRAT Model

and

Economies 2022, 10(3), 70; https://doi.org/10.3390/economies10030070 - 21 Mar 2022

Cited by 7 | Viewed by 3002

Abstract

This study aims at testing the effect of the components of the PRAT model and the basic model developed by Robert Higgins on the rate of sustainable growth by applying them to a sample of Saudi banks during the period of 2010–2019. Regarding the PRAT model, as Higgins explained, it is that detailed model measuring the sustainable growth rate by profit margin (P), retention rate (R), asset turnover (A), and leverage (T). To test the relation between the study variables, multiple regression analyses were conducted using the Pooled Model (PEM), the Fixed Effect Model (FEM), and the Random Effect Model (REM). The results showed that all the variables of the PRAT model affect sustainable growth (profitability margin, retained earnings, asset turnover, and financial leverage). Moreover, the application of the basic model of Higgins shows that the rate of return on equity and retained earnings affect sustainable growth. When drawing a comparison among statistical measurement models and checking the validity of these models, the validity of the fixed effect model for measuring the relation between the variables of the PRAT model and Higgins basic model is seen. Full article

(This article belongs to the Special Issue Financial Economics: Theory and Applications)

Open AccessArticle

The Effect of Inflation Targeting (IT) Policy on the Inflation Uncertainty and Economic Growth in Selected African and European Countries

Shelter Thelile Nene

Kehinde Damilola Ilesanmi

and

Mashapa Sekome

Economies 2022, 10(2), 37; https://doi.org/10.3390/economies10020037 - 31 Jan 2022

Cited by 3 | Viewed by 3525

Abstract

The study assessed the effect of inflation targeting (IT) policy on inflation uncertainty and economic growth in African and European IT countries. This study contributes to the existing knowledge by analysing and comparing the African IT and European IT countries using two advanced approaches which include the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Panel Vector Autoregressive (PVAR). To determine how the IT policy affects the inflation uncertainty in selected countries, time series techniques were employed. Panel data approaches were used to determine the effect of inflation targeting on economic growth in the selected countries. The results are as follows: (1) Inflation Targeting policy is insignificant in reducing inflation uncertainty in South Africa, and the effect of the policy in Ghana is inconclusive; (2) The IT policy has a significant impact in reducing inflation uncertainty in European countries (i.e., Poland and the Czech Republic); (3) Inflation targeting has a negative impact on economic growth in African Countries; (4) The policy has a positive impact on economic growth in European Countries; (5) In comparison to European countries, the strategy has a negligible impact on economic growth in Africa. Overall, the results suggest that European countries inflation targeting regimes are more credible in terms of reducing the level of inflation uncertainty and sustaining economic growth compared to African countries. In this respect, policymakers must ensure that they assess the economic condition of an individual country before implementing such a policy. Full article

(This article belongs to the Special Issue Financial Economics: Theory and Applications)

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Open AccessArticle

Log Periodic Power Analysis of Critical Crashes: Evidence from the Portuguese Stock Market

Tiago Cruz Gonçalves

Jorge Victor Quiñones Borda

Pedro Rino Vieira

and

Pedro Verga Matos

Economies 2022, 10(1), 14; https://doi.org/10.3390/economies10010014 - 04 Jan 2022

Cited by 1 | Viewed by 2029

Abstract

The study of critical phenomena that originated in the natural sciences has been extended to the financial economics’ field, giving researchers new approaches to risk management, forecasting, the study of bubbles and crashes, and many kinds of problems involving complex systems with self-organized criticality (SOC). This study uses the theory of self-similar oscillatory time singularities to analyze stock market crashes. We test the Log Periodic Power Law/Model (LPPM) to analyze the Portuguese stock market, in its crises in 1998, 2007, and 2015. Parameter values are in line with those observed in other markets. This is particularly interesting since if the model performs robustly for Portugal, which is a small market with liquidity issues and the index is only composed of 20 stocks, we provide consistent evidence in favor of the proposed LPPM methodology. The LPPM methodology proposed here would have allowed us to avoid big loses in the 1998 Portuguese crash, and would have permitted us to sell at points near the peak in the 2007 crash. In the case of the 2015 crisis, we would have obtained a good indication of the moment where the lowest data point was going to be achieved. Full article

(This article belongs to the Special Issue Financial Economics: Theory and Applications)

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Open AccessArticle

A Machine Learning Pipeline for Forecasting Time Series in the Banking Sector

Olga Gorodetskaya

Yana Gobareva

and

Mikhail Koroteev

Economies 2021, 9(4), 205; https://doi.org/10.3390/economies9040205 - 20 Dec 2021

Cited by 1 | Viewed by 2773

Abstract

The problem of forecasting time series is very widely debated. In recent years, machine learning algorithms have been very prolific in this area. This paper describes a systematic approach to building a machine learning predictive model for solving optimization problems in the banking sector. A literature analysis on applying such methods in this particular area is presented. As a direct result of the described research, a universal scenario for forecasting various non-stationary time series in automatic mode was developed. The developed scenario for solving specific banking tasks to improve business efficiency, including optimizing demand for ATMs, forecasting the load on the call center and cash center, is considered. A machine learning methodology in economics that can yield robust and reproducible results and can be reused in solving other similar tasks is described. The methodology described in the article was tested on three cases and showed the ability to generate models that are superior in accuracy to similar predictive models described in the literature by at least three percentage points. This article will be helpful to specialists dealing with the problem of forecasting economic time series and students and researchers due to a large number of links to systematic literature reviews on this topic. Full article

(This article belongs to the Special Issue Financial Economics: Theory and Applications)

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