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Special Issue "Mathematical and Statistical Models for Energy with Applications"

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "C: Energy Economics and Policy".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 19094

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Special Issue Editors

Prof. Dr. Wing-Keung Wong

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Guest Editor

1. Department of Finance, College of Management, Asia University, Wufeng, Taichung 407705, Taiwan
2. Department of Medical Research, China Medical University Hospital, Taichung City, Taiwan
3. Department of Economics and Finance, The Hang Seng University of Hong Kong, Hong Kong, China
Interests: behavioral models; mathematical modeling; econometrics; energy economics; equity analysis; investment theory; risk management; behavioral economics; operational research; decision theory; environmental economics; public health; time series analysis; forecasting
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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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Dr. Aviral Kumar Tiwari

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Guest Editor

Indian Institute of Management Bodh Gaya, Bihar 824234, India
Interests: sustainability; SDGs; resource economics; environment and energy economics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to consider research on Mathematical and Statistical Models with applications on following, but not limited to, topics as research issues:

(i) Domestic and international pricing of energy sources, such as oil, coal, gas and nuclear, hydrogen, wind, etc.;

(ii) Modeling domestic and international carbon emissions prices;

(iii) Modeling of financial returns and volatility of energy and natural resources;

(iv) Analyzing the forecasting performance of energy commodities, natural resources, and carbon emissions;

(v) Analyzing the usefulness of inclusion of energy commodities, natural resources, and carbon emissions as financial commodities in financial portfolios and optimal hedging (or insurance) of financial portfolios;

(vi) Impacts on the environment and sustainability of pricing carbon emissions;

(vii) Impacts on the health and agriculture sectors of (pricing) carbon emissions.

For example, authors could provide statistically valid prices for energy commodities, natural resources, and carbon emissions using robust modeling techniques. Furthermore, authors could also explore financial returns, and volatility of energy commodities, natural resources, and carbon emissions. Researchers are also encouraged to consider the energy commodities, natural resources, and carbon emissions as financial commodities in financial portfolios and in optimal hedging (or insurance) of financial portfolios; evaluate the impacts on the environment and sustainability of pricing energy commodities, natural resources, and carbon emissions; and evaluate the effects on health and agriculture costs of pricing carbon emissions, etc.

We invite investigators to contribute original research articles that advance the use of mathematics, probability, and statistics in the areas of Energy and Natural Resources with applications. All submissions must contain original unpublished work not being considered for publication elsewhere.

Prof. Dr. Wing-Keung Wong
Prof. Dr. Faridul Islam
Dr. Aviral Kumar Tiwari
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. Energies 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 2200 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
energy
applications
energy commodities
natural resources
carbon emissions
mathematical modeling
volatility modeling
dependence modeling
risk and portfolio modeling
forecasting

Published Papers (10 papers)

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Editorial

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Open AccessEditorial

Editorial and Ideas for Research Using Mathematical and Statistical Models for Energy with Applications

Faridul Islam

Aviral Kumar Tiwari

and

Wing-Keung Wong

Energies 2021, 14(22), 7611; https://doi.org/10.3390/en14227611 - 15 Nov 2021

Cited by 1 | Viewed by 879

Abstract

Given the mounting evidence favoring quantitative and qualitative analyses, prompted by easy access to data, mathematical and statistical models have gained a formal appreciation for their role in the analytical apparatus of contemporary research methodologies in all fields [...] Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

Research

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Open AccessArticle

Wind Put Barrier Options Pricing Based on the Nordix Index

Yeny E. Rodríguez

Miguel A. Pérez-Uribe

and

Javier Contreras

Energies 2021, 14(4), 1177; https://doi.org/10.3390/en14041177 - 23 Feb 2021

Cited by 12 | Viewed by 1518

Abstract

Wind power generators face risks derived from fluctuations in market prices and variability in power production, generated by their high dependence on wind speed. These risks could be hedged using weather financial instruments. In this research, we design and price an up-and-in European wind put barrier option using Monte Carlo simulation. Under the existence of a structured weather market, wind producers may purchase an up-and-in European wind barrier put option to hedge wind fluctuations, allowing them to recover their investments and maximise their profits. We use a wind speed index as the underlying index of the barrier option, which captures risk from wind power generation and the Autoregressive Fractionally Integrated Moving Average (ARFIMA) to model the wind speed. This methodology is applied in the Colombian context, an electricity market affected by the El Niño phenomenon. We find that when the El Niño phenomenon occurs, there are incentives for wind generators to sell their energy to the system because their costs, including the put option price, are lower than the power prices. This research aims at encouraging policymakers and governments to promote renewable energy sources and a financial market to trade options to reduce uncertainty in the electrical system due to climate phenomena. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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Open AccessArticle

A Fuzzy-ANP Approach for Comprehensive Benefit Evaluation of Grid-Side Commercial Storage Project

and

Energies 2021, 14(4), 1129; https://doi.org/10.3390/en14041129 - 20 Feb 2021

Cited by 10 | Viewed by 1229

Abstract

With the increasing demand for clean and low-carbon energy, high proportion of renewable energy has been integrated into the receiving-end grid. The grid-side energy storage project can ensure the safe and stable operation of the grid, but it still faces many problems, such as high initial investment, difficult operation and maintenance, unclear profit model, lack of business mode. Therefore, it is of great significance to evaluate the comprehensive benefit of energy storage projects in order to guide the sustainable development of large-scale energy storage projects and power system. By studying the technical and economic characteristics of energy storage, this paper establishes a comprehensive evaluation system from four dimensions of energy efficiency, economic, social, and environmental benefit. Combined with typical business modes and determining the subdivision index system of different modes, the comprehensive benefit evaluation model of grid-side commercial storage project based on Fuzzy-Analytic Network Process (ANP) approach is established. Empirical analysis of a 100-megawatt storage project is carried out to evaluate the project benefits comprehensively, the potential problems of the market development and business mode of the grid-side large-scale storage project are discussed, and the future development orientation and suggestions are put forward. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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Open AccessArticle

Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case

Jeyhun I. Mikayilov

Shahriyar Mukhtarov

and

Jeyhun Mammadov

Energies 2020, 13(24), 6752; https://doi.org/10.3390/en13246752 - 21 Dec 2020

Cited by 9 | Viewed by 2974

Abstract

This study investigates the income and price elasticities of gasoline demand for a fuel subsidizing country case, applying three different time-varying coefficient approaches to the data spanning the period from January 2002 to June 2018. The empirical estimations concluded a cointegration relationship between gasoline demand, income, and gasoline price. The income elasticity found ranges from 0.10 to 0.29, while the price elasticity remains constant over time, being −0.15. Income elasticity increases over time, slightly decreasing close to the end of the period, which is specific for a developing country. In the short run, gasoline demand does not respond to the changes in income and price. The policy implications are discussed based on the findings of the study. Research results show that since the income elasticity of demand is not constant, the use of constant elasticities obtained in previous studies might be misleading for policymaking purposes. An increase in income elasticity might be the cause of the inefficiency of the existing vehicles. The small price elasticity allows to say that if policy makers plan to reduce gasoline consumption then increasing its price would not substantially reduce the consumption. The current situation can be utilized to increase energy efficiency and implement eco-friendly technologies. For this purpose, the quality of existing transport modes can be improved. Meanwhile, to meet households’ needs, policies such as providing soft auto loans need to be formed to balance the recent drop in car sales. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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Open AccessArticle

Oil as Hedge, Safe-Haven, and Diversifier for Conventional Currencies

Changyu Liu

Muhammad Abubakr Naeem

Mobeen Ur Rehman

Saqib Farid

and

Syed Jawad Hussain Shahzad

Energies 2020, 13(17), 4354; https://doi.org/10.3390/en13174354 - 24 Aug 2020

Cited by 17 | Viewed by 2434

Abstract

The research investigates the safe-haven, hedging, and diversification function of crude oil for conventional currencies, among which five are major oil exporters, and six are major oil importers. In order to model time-varying dynamic correlations between crude oil and currencies, the study uses the Asymmetric-DCC model. The findings highlight low or negative correlations, especially during the crisis period. Next, we employ a quantile based regression framework and conclude distinct safe-haven and hedge functions of oil for major currencies. We provide additional evidence on the safe-haven, hedging, and diversification function of crude oil using the cross-quantilogram framework. The findings of out of sample analysis illustrate that the hedging effectiveness of oil is greater for oil-exporting countries. In addition, the conditional diversification benefit of oil is higher in the lower quantiles, i.e., when both foreign exchange and oil markets are in a bearish state. Finally, implications for investors, portfolio managers, and policymakers are further discussed. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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Open AccessArticle

Implications of Oil Price Fluctuations for Tourism Receipts: The Case of Oil Exporting Countries

and

Energies 2020, 13(17), 4349; https://doi.org/10.3390/en13174349 - 22 Aug 2020

Cited by 9 | Viewed by 2397

Abstract

This study investigates the influence of oil prices on tourism income in countries that heavily relied on crude oil exports from 2000 to 2017. We found that oil prices and tourism receipts are cointegrated, revealing the existence of their long-run equilibrium relationship. Another significant finding to emerge from this study is the presence of a unidirectional Granger causality that runs from the oil prices to the tourism receipts. The results of the current study are of particular importance for policymakers who operate in oil-exporting countries. The implications provide a systematic understanding of the effect of oil price fluctuations on tourism income which can benefit investors greatly by enabling them to hedge against oil price fluctuations and plan for their tourism business and policymakers by enabling them to set policies to stabilize oil price fluctuations and plan for tourism development, correspondingly. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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Open AccessArticle

Do Oil Price Shocks and Other Factors Create Bigger Impacts on Islamic Banks than Conventional Banks?

Jabir Esmaeil

Husam Rjoub

and

Wing-Keung Wong

Energies 2020, 13(12), 3106; https://doi.org/10.3390/en13123106 - 16 Jun 2020

Cited by 10 | Viewed by 1477

Abstract

The main aim of this study is to empirically examine and compares the impacts of oil price shocks, Arab revolutions, some macroeconomics, and bank-specific variables on bank profitability indicators between Conventional and Islamic banks in Gulf Cooperation Council (GCC) countries. The study employed panel Autoregressive-Distributed Lag (ARDL) techniques to examine the causal relationship both at the short and long-run. Our results reveal that most of the variables employed in our study significantly influence Return on Asset (ROA), Return on Equity (ROE), and Net Interest Margin (NIM)/ Net Profit Margin (NPM) for both Conventional Banks (CBs) and Islamic Banks (IBs) similarly in the long run. Findings from our study imply that both CBs and IBs have some similar features in nature, which could be because of the structure of the policies for IBs is in line with the regulatory framework for the CBs. The main finding from the study is the significance of oil price shock and the Arab springs that are more pronounced in CBs than IBs. Also, it can be seen that a sustainable profit of IBs is higher than CBs due to the adjustment speed of IBs to equilibrium in the presence of shock is found to be higher than CBs. Hence, our study suggests that oil price shock could be utilized for having a prudent macro regulation for the banks in GCC countries. Our findings are useful to Government officers, bankers, investors, and researchers for their decision making by estimating future trends of the profitability for both Conventional and Islamic banks in the GCC countries. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

Open AccessArticle

A Comparison of the Risk Quantification in Traditional and Renewable Energy Markets

Daniel Velásquez-Gaviria

Andrés Mora-Valencia

and

Javier Perote

Energies 2020, 13(11), 2805; https://doi.org/10.3390/en13112805 - 01 Jun 2020

Cited by 7 | Viewed by 1935

Abstract

The transition from traditional energy to cleaner energy sources has raised concerns from companies and investors regarding, among other things, the impact on financial downside risk. This article implements backtesting techniques to estimate and validate the value-at-risk (VaR) and expected shortfall (ES) in order to compare their performance among four renewable energy stocks and four traditional energy stocks from the WilderHill New Energy Global Innovation and the Bloomberg World Energy for the period 2005-2016. The models used to estimate VaR and ES are AR(1)-GARCH(1,1), AR(1)-EGARCH(1,1), and AR(1)-APARCH(1,1), all of them under either normal, skew-normal, Student’s t, skewed-t, Generalized Error or Skew-Generalized Error distributed innovations. Backtesting performance is tested through traditional Kupiec and Christoffersen tests for VaR, but also through recent backtesting ES techniques. The paper extends these tests to the skewed-t, skew-normal and Skew-Generalized Error distributions and applies it for the first time in traditional and renewable energy markets showing that the skewed-t and the Generalized Error distribution are an accurate tool for risk management in those markets. Our findings have important implications for portfolio managers and regulators in terms of capital allocation in renewable and traditional energy stocks, mainly to reduce the impact of possible extreme loss events. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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Open AccessArticle

An Efficient Analytical Approach for the Solution of Certain Fractional-Order Dynamical Systems

and

Energies 2020, 13(11), 2725; https://doi.org/10.3390/en13112725 - 28 May 2020

Cited by 29 | Viewed by 1591

Abstract

Mostly, it is very difficult to obtained the exact solution of fractional-order partial differential equations. However, semi-analytical or numerical methods are considered to be an alternative to handle the solutions of such complicated problems. To extend this idea, we used semi-analytical procedures which are mixtures of Laplace transform, Shehu transform and Homotopy perturbation techniques to solve certain systems with Caputo derivative differential equations. The effectiveness of the present technique is justified by taking some examples. The graphical representation of the obtained results have confirmed the significant association between the actual and derived solutions. It is also shown that the suggested method provides a higher rate of convergence with a very small number of calculations. The problems with derivatives of fractional-order are also solved by using the present method. The convergence behavior of the fractional-order solutions to an integer-order solution is observed. The convergence phenomena described a very broad concept of the physical problems. Due to simple and useful implementation, the current methods can be used to solve problems containing the derivative of a fractional-order. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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Modified Modelling for Heat Like Equations within Caputo Operator

and

Energies 2020, 13(8), 2002; https://doi.org/10.3390/en13082002 - 17 Apr 2020

Cited by 20 | Viewed by 1555

Abstract

The present paper is related to the analytical solutions of some heat like equations, using a novel approach with Caputo operator. The work is carried out mainly with the use of an effective and straight procedure of the Iterative Laplace transform method. The proposed method provides the series form solution that has the desired rate of convergence towards the exact solution of the problems. It is observed that the suggested method provides closed-form solutions. The reliability of the method is confirmed with the help of some illustrative examples. The graphical representation has been made for both fractional and integer-order solutions. Numerical solutions that are in close contact with the exact solutions to the problems are investigated. Moreover, the sample implementation of the present method supports the importance of the method to solve other fractional-order problems in sciences and engineering. Full article

(This article belongs to the Special Issue Mathematical and Statistical Models for Energy with Applications)

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