Alexey Mikhaylov | Financial University under the Government of the Russian Federation (original) (raw)
Alexey MIKHAYLOV, Ph.D. holds positions:
Head of laboratory, Financial University under the Government of the Russian Federation, Moscow
Associate Professor, Financial Markets and Financial Engineering Department, Financial University under the Government of the Russian Federation, Moscow
Senior Researcher, Financial Research Institute of Ministry of Finance of the Russian Federation, Moscow
He is an author of many scientific publications and conference papers indexed in SCOPUS and Web of Science and author of 8 scientific monographs. He specializes in Energy; Economics, Econometrics and Finance; Business, Management and Accounting; Environmental Science; Materials Science; Mathematics; Computer Science; Psychology; Social Sciences; Neuroscience.
Awards:
The Best Special Issue Award, "Financial Open Innovations for Sustainable Economic Growth" of Journal of Open Innovation: Technology, Market, and Complexity (2022).
Bronze Poster Award at SOI and Riga Technical University 2021 Conference (2021),
The best scientific publication "Academus" in the category "Economics and Management "(2020),
Rector’s Award of Financial University (2020),
The best scientific publication "Academus" (2019),
Winner in the category " Discovery of the Year "of the publishing house "Knorus" (2019).
Alexey MIKHAYLOV is editor in journals (Web of Science, Scopus, RePec) in 2020-2023:
https://www.hindawi.com/journals/ijer/editors/
https://ojs.bonviewpress.com/index.php/GLCE/ebm
http://systems.enpress-publisher.com/index.php/TSE/about/editorialBoard
https://www.mdpi.com/journal/energies/topic\_editors
https://www.mdpi.com/journal/risks/special\_issues/49C22IDF3F
https://www.mdpi.com/journal/metals/special\_issues/A1YM2M87VZ
http://www.revistaorbis.org/equipoeditorial.html
https://www.finjournal-nifi.ru/en/editorial-board
https://www.mdpi.com/journal/sustainability/special\_issues/economic\_renewable
https://www.mdpi.com/journal/JOItmC/special\_issues/financial\_open\_innovations
https://www.mdpi.com/journal/economies/special\_issues/Emerging\_Economics\_Sustainable\_Growth
https://www.mdpi.com/journal/energies/special\_issues/Sustainable\_Renewable\_Energy\_Trends
https://www.sciencepublishinggroup.com/journal/editorialboard?journalid=297
He has filed patents:
Modified machine learning algorithm based on linear regression for forecasting oil prices, taking into account the influence of macroeconomic indicators.
Automated Information System for Predicting Bitcoin Prices.
He is board member of:
Society of Open Innovation: Technology, Market, and Complexity (SOI)
ACI Russia - Financial Markets Association
Council on professional qualifications at the financial market
Russian Association of Crypto Industry and Blockchain
Registered financial analyst (NFA) https://new.nfa.ru/services/analysts\_register/15679/
Public Health-2023 committee https://www.xpertsmeetings.org/publichealth23/board
less
Uploads
Papers by Alexey Mikhaylov
IEEE Access, 2023
It is essential to supply the necessary electricity for both the increase in the quality of life ... more It is essential to supply the necessary electricity for both the increase in the quality of life of the citizens and the stable growth of the country's economy. For countries to have energy independence, they need to increase their electricity generation capacity. However, all alternatives required to increase electrical capacity have both advantages and disadvantages. Within this scope, it is not easy for countries to make the right investment decisions. Therefore, a comprehensive analysis is needed to determine the right investment policy. The purpose of this study is to evaluate the electricity production capacities of emerging markets. A new fuzzy decision-making model has been constructed to find a solution for this situation. The groups for the electricity production capacities are examined by the extension of DEMATEL with Quantum Spherical fuzzy sets and golden ratio. In the following stage, emerging seven economies are ranked by using QSF TOPSIS technique. This situation helps to understand which of these countries are more successful in generating electricity capacity effectively. The main novelty is to define the most significant electricity generation alternatives by a novel model that integrates DEMATEL and TOPSIS with QSFSs and golden ratio. The results demonstrate that solar photovoltaic is the most optimal way to increase electricity capacity of the countries. Additionally, China is the most successful emerging country to generate electricity in an efficient way. Countries should take some actions to increase their solar energy investments. First, it would be appropriate to provide tax exemptions to solar energy investors so that the costs of these projects can be decreased. Additionally, investments in solar energy technologies need to be further increased.
The performance assessment of renewable energy technologies, such as PV systems, is pivotal in pl... more The performance assessment of renewable energy technologies, such as PV systems, is pivotal in planning for hybrid energy systems. This work clears the way for researchers to construct the best PV-based hybrid systems by first performing performance analysis metrics suggested by IEC 61724 on several PV technology options, and then choosing the most technically sound option. Next, using HOMER Pro software, construct a PV/grid and battery hybrid system with effective PV technology. The performance of three PV technologies, i.e., monocrystalline silicon, polycrystalline silicon, and amorphous silicon is assessed to demonstrate how their performance varies depending on the location. Results showed that (m-Si) has greater performance than the other two PV technologies, with yearly array yields of 5.26 h/day, reference yields of 6.18 h/day, and final yields of 5.18 h/ day, a capacity factor of 14.31%, system losses of 0.076, and a performance ratio (PR) of 83.9%. The most effective configuration of the system under evaluation consists of a 72.8 kW PV connected to the grid and a 59.4 kW converter. The total NPC is expected to be Rs. 397,684fortheoptimalconfiguration,costingRs.397,684 for the optimal configuration, costing Rs. 397,684fortheoptimalconfiguration,costingRs.0,0493/ kWh. The additional electricity in the best situation is 977 kWh, which is insignificant compared to the system capacity. Two sensitivity variables, including changes in the main load, are anticipated to be 10% and 15% higher than the current value (1698.63 kWh) and the battery's minimum state of charge, with 20%, 25%, and 30% uncertainty, are addressed.
Frontiers in Environmental Science, 2023
The United Nations SDGs Report 2020 revealed that climatic variability victimized masses across t... more The United Nations SDGs Report 2020 revealed that climatic variability victimized masses across the globe in 2018 and the global average temperature would rise to 3.2°C during this century. The GHG emission reduction targets for 2030 were prioritized under the Paris Climate Agreement (PCA) of 2015 to keep the rise in global temperature below 1.5°C. Here, parallel action for climate adaptation is on top of it. However, targets for both adaptation and mitigation are lagging. Climatic variations will continue more likely with similar trends thus influencing the development needs vis-à-vis environmental security and sustainability of resources. It entails climate compatibility, particularly for the water security agenda for SDG-13 and Paris Climate Agreement (PCA), which requires an inclusive governance regime and ownership for national and sub-national scenarios. In this context, this paper aimed to assess existing water sector governance for climate compatible development (CCD) by taking the case of Pakistan which is among the top 10 countries vulnerable to climate change. Considering the limitations of available methodologies due to the involvement of various aspects and concepts of governance, an integrated multivariate mix-method model was formulated by combining rules and rights-oriented approaches. This MCDA-based model integrates six novel climate governance principles against six basic components of the basic institutional governance framework; Simple Multi-attribute Rating Technique (SMART) with a set of sectoral indicators of 09 criteria of climate compatible development (CCD). It proved well for this water sector case study with cross-sectional data from 340 key informant interviews (KIIs) and 17 focus group discussions (FGDs) in Pakistan, validated statistically. It can be used for periodic sectoral governance assessments for CCD.
This research paper analyzes revenue trends in e-commerce, a sector with an annual sales volume o... more This research paper analyzes revenue trends in e-commerce, a sector with an annual sales volume of more than 340 billion dollars. The article evaluates, despite a scarcity of data, the effects on e-commerce development of the ubiquitous lockdowns and restriction measures introduced by most countries during the pandemic period. The analysis covers monthly data from January 1996 to February 2021. The research paper analyzes relative changes in the original time series through the autocorrelation function. The objects of this analysis are Amazon and Alibaba, as they are benchmarks in the e-commerce industry. This paper tests the shock effect on the e-commerce companies Alibaba in China and Amazon in the USA, concluding that it is weaker for companies with small market capitalizations. As a result, the effect on estimated e-trade volume in the USA was approximately 35% in 2020. Another evaluation considers fuzzy decision-making methodology. For this purpose, balanced scorecard-based open financial innovation models for the e-commerce industry are weighted with multistepwise weight assessment ratio analysis based on q-rung orthopair fuzzy sets and the golden cut. Within this framework, a detailed analysis of competitors should be made. The paper proves that this situation positively affects the development of successful financial innovation models for the e-commerce industry. Therefore, it may be possible to attract greater attention from e-commerce companies for these financial innovation products.
SSRN Electronic Journal, 2022
In the world, the concentration of population in urban areas has led to the problem of increasing... more In the world, the concentration of population in urban areas has led to the problem of increasing load on urban infrastructure and greenhouse gases. To solve this problem, cities are being converted into smart cities. This paper presents the optimal operation and capacity planning of a smart city with renewable energy and combined cooling, heating and power system. In this study, clustering is applied to reduce the simulation time while maintaining the accuracy of the solution. Furthermore, the optimal capacity is examined by varying the price of renewable energy with the generation capacity. As a result, the simulation time is reduced from 4,960 [sec] to 2.66 [sec], and the error of the result is 0.4[%]. Compared to the case without renewable energy, the9 Electricity rate is reduced by 67.0[%] and the CO2 emission by 55.9[%]. To further reduce the CO2 emission, the price of renewable energy facilities needs to be reduced. In the last part of the paper, we vary the price of PV equipment and determine the PV equipment price that minimizes the operating cost and CO2 emissions to be less than 240 million yen. The simulations in this paper are performed using the optimization method Mixed integer linear programming (MILP) and the numerical analysis software MATLAB®.
Energy Strategy Reviews, 2023
The sub-Saharan Africa (SSA) region gathers the most vulnerable countries, which are criss-crosse... more The sub-Saharan Africa (SSA) region gathers the most vulnerable countries, which are criss-crossed geographically, making SSA countries extremely vulnerable to the influence of neighbouring countries. However, very few studies have considered the spillover effect of technical assistance in the recipient country. To fill the research gap, a dynamic space Dubin approach based on an asymmetric space weight matrix was developed. The results show the Moran's I value of technical assistance is positive, indicating that there is a positive correlation in space. Technical assistance is not unconditional free help, but with the strong subjective will of donor countries. SDM's estimation results show that the coefficient of the space lag term is greater than the coefficient of the time lag term, indicating that the spatial spillover effect can promote the power development of the recipient country more than the path dependence effect. Technical assistance to neighbouring countries can only improve the power development of the target country in the short term. In the long run, the mismatch effect of aid resources from neighbouring countries inhibits the power development of recipient countries. Therefore, technical assistance should be integrated with the situation of the recipient country in order to reduce energy poverty more effectively.
The purpose of the paper is to identify the factors of financial development that have the greate... more The purpose of the paper is to identify the factors of financial development that have the greatest impact on open innovation in 7 emerging countries. The analysis was performed featuring the MF-X-DMA method, as well as its further verification for autocorrelation and heteroscedasticity. The time period covers years from 2002 to 2020. The article states that the main indicators to improve financial development should enhance the process of bank lending and equity market development. An important area is the development of competition by providing equal access to information to all market participants in a continuously refining technical infrastructure. Regression analysis with the MF-X-DMA method confirms the statistical significance of this influence. The article fills the knowledge gap into the link between open innovations and the relatively low capitalization of the modern emerging countries' financial market, low liquidity in small cap stocks at the financial market and concentration of the banking sector, as well as risks arising in the process of globalization. Another analysis has also been conducted by generating a novel fuzzy decision-making model. In the first stage, the determinants of open innovation-based fintech potential are weighted for the emerging economies. For this purpose, M-SWARA methodology is taken into consideration based on bipolar q-ROFSs and golden cut. The second stage of the analysis includes evaluating the emerging economies with the determinants of open innovation-based fintech potential. In this context, emerging seven countries are examined with ELECTRE methodology. It found the most significant factor is the open innovation-based fintech potential.
In book: Eco-Friendly and Agile Energy Strategies and Policy Development, 2022
This chapter presents re-engineering environmental sustainability opportunities within constraine... more This chapter presents re-engineering environmental sustainability opportunities within constrained pandemic situations that suggest solutions. Climate change disaster and COVID-19 socioeconomic impacts are leading nations to dramatic tragedy. Simultaneously, increasing demand for energy are due to population, political competition, and industrial growth globally. At present, the pandemic attracts more attention due to its immediate effect. Ignoring climate change can have a worse consequence not only on the present but for the future generation in the long run. Therefore, re-engineering the current pandemic situation with a futurism outlook for saving the world will enable nations to transform and rethink strategies, policies, procedures, processes, and any actions that can cope with present and possible future pandemics and climate change tragedies.
Computational Economics, 2022
This article is dedicated analyzing the interdependence of oil prices and exchange rate movements... more This article is dedicated analyzing the interdependence of oil prices and exchange rate movements of oil exporting countries (the Russian ruble, Euro, Canadian dollar, Chinese yuan, Brazil real, Nigerian naira, Algerian dinar). The study also considers risk-based oil market spillovers in global crisis periods with integrated decision recommendation systems. For this purpose, a fuzzy decision-making model is created by considering the bipolar model and imputation of expert evaluations with collaborative filtering. The main contribution of this study is both its econometric analysis and evaluations based on expert opinions. This helps reach more crucial results. All three of the recent shocks (2008, 2012, 2020) in the oil market are transmitted to foreign exchange markets of oil-producing countries. At the same time, the last shock of 2020 caused by the COVID-19 pandemic has not yet been fully reflected on the Russian ruble exchange rate. Correlation parameters became weaker in the last year, as the Russian ruble correlation coefficient fluctuates between − 0.5 and 0.5. However, before 2020 the spillover effect had a higher significance (in the range from − 0.8 to − 0.1). Nigerian naira and Algerian dinar were showing almost the same movements, while the Russian Ruble was in a different trading range.
COVID-19 pandemic has made the future uncertain for many in general, but students in particular b... more COVID-19 pandemic has made the future uncertain for many in general, but students in particular because institutes suddenly shutting down, while this new transition has hit everyone differently. Still, it has left significant pressure on the students specifically. This pandemic has changed the ways of living-financially, physically, emotionally, and mentally. This study analyses the impact of COVID-19 on students' mental health. It covers the globe, how they have been dealing with it, and which coping mechanisms worked best for them during this time. The study also discussed how different financial backgrounds had left a different psychological impact on the students. The methodology adopted utilizes all the previous research and their data, which helped us determine the most worked solution vs the least worked solution. In addition to literature, data from UNICEF about education and COVID-19 are utilized to determine the adverse impact of COVID-19. This study has also briefly touched on the impact of remote learning on students' mental health and how students have coped with this sudden yet uncertain new change. The research has come up with some proven solutions for students to perform better academically during this uncertain time without compromising their mental health.
SSRN Electronic Journal, 2022
In the world, the concentration of population in urban areas has led to the problem of increasing... more In the world, the concentration of population in urban areas has led to the problem of increasing load on urban infrastructure and greenhouse gases. To solve this problem, cities are being converted into smart cities. This paper presents the optimal operation and capacity planning of a smart city with renewable energy and combined cooling, heating and power system. In this study, clustering is applied to reduce the simulation time while maintaining the accuracy of the solution. Furthermore, the optimal capacity is examined by varying the price of renewable energy with the generation capacity. As a result, the simulation time is reduced from 4,960 [sec] to 2.66 [sec], and the error of the result is 0.4[%]. Compared to the case without renewable energy, the9 Electricity rate is reduced by 67.0[%] and the CO2 emission by 55.9[%]. To further reduce the CO2 emission, the price of renewable energy facilities needs to be reduced. In the last part of the paper, we vary the price of PV equipment and determine the PV equipment price that minimizes the operating cost and CO2 emissions to be less than 240 million yen. The simulations in this paper are performed using the optimization method Mixed integer linear programming (MILP) and the numerical analysis software MATLAB®.
Modern methods of lichen indication allow assessing the impact of climate change and air pollutio... more Modern methods of lichen indication allow assessing the impact of climate change and air pollution on ecosystem health. The purpose of this study was to evaluate the general state of atmospheric air in urban ecosystems of cities and towns using lichen indication methods. The objectives of the study included identifying lichen indicator species, as well as assessing the response of these species to various pollutants (e.g., lead, iron, manganese). The study was conducted in 2017 in the Bryansk region of the Russian Federation (9 settlements in total) and the Oryol region (1 settlement-the city of Oryol). Four hundred samples belonging to epiphytic lichens were collected. Additional 300 and 137 samples of epiphytic lichens were used for chemical and toxicological analyses, respectively. The following two generally accepted lichen indicator indices were calculated: poleotolerance index (PI) and atmospheric purity index (API). When calculating the latter, the lichen species Xanthoria parietina was used as the baseline. Epiphytic lichens in small settlements were represented by 50 species (28 genera, 8 families). In large cities, 55 (Bryansk) and 53 (Oryol) species of epiphytic lichens were detected. The number of species in small settlements was 1.5 times lower than that of large cities. There were 8-15 and 25-32 species of epiphytic lichens in the central region and in the periphery of Bryansk, respectively. The number of epiphytic lichen species detected in the parks was 41. Within the territory of large cities, 17 species of lichens were identified as potential indicators, since they were found in every second or fourth sample. Maximum concentrations of lead were recorded in industrial areas of cities, as well as near major roads with traffic intersection and bridges and in some dormitory suburbs. This is a distinctive feature of large cities-the predominance of lead in lichen thalli, which is primarily associated with vehicles. In small cities in which there are no specific industrial enterprises (metallurgical plants, etc.), other heavy metals-manganese and iron-prevail in the thalli of lichens. In this work, new methods are adopted-mapping pollution with the use of nitrophilous epiphytic lichens that reflect the ongoing macro processes of nitrification in urban areas. The authors have proposed and tested the following lichen indicator methods: the use of indicator species (epiphytesnitrophytes) of various sensitivities and the study of their distribution within the territory. The mapping method has been substantiated, which takes into account the API and zoning of territories according to the level of general pollution. Among the indicator species, Xanthoria parietina turned out to be the most suitable one.
Journal of Air Transport Management, 2021
The classical revenue management problem consists of allocating a fixed network capacity to diffe... more The classical revenue management problem consists of allocating a fixed network capacity to different customer classes, so as to maximize revenue. This area has been widely applied in service industries that are characterized by a fixed perishable capacity, such as airlines, cruises, hotels, etc. It is traditionally assumed that demand is uncertain, but can be characterized as a stochastic process (See Talluri and van Ryzin (2005) for a review of the revenue management models). In practice, however, airlines have limited demand information and are unable to fully characterize demand stochastic processes. Robust optimization methods have been proposed to overcome this modeling challenge. Under robust optimization framework, demand is only assumed to lie within a polyhedral uncertainty set (Lan et al. (2008); Perakis and Roels (2010)). In this paper, we consider the multi-fare, network revenue management problem for the case demand information is limited (i.e. the only information available is lower/upper bounds on demand). Under this interval uncertainty, we characterize the robust optimal booking limit policy by use of minimax regret criterion. We present an LP (Linear Programming) solvable mathematical program for the maximum regret so our model is able to solve large-scale problems for practical use. A genetic algorithm is proposed to find the booking limit control to minimize the maximum regret. We provide computational experiments and compare our methods to existing ones. The results demonstrate the effectiveness of our robust approach.
The paper proposes the pricing in the oil market and the impact of oil prices on world stock indi... more The paper proposes the pricing in the oil market and the impact of oil prices on world stock indices. There is analysis of major trends in the oil market. We develop a model to predict the impact of oil prices on stock market indices for developed economies and Russia. This work propose a probit-model for forecasting capital markets trends using Brent pricing, three-month interest rates of the money market, consumer price index, GDP growth rate as a binary dependent variables. The trends of pricing in different stages of development of the oil market make the on stock indices, as developed countries and Russia. The practical significance of this work lies in the structuring of existing knowledge on the applicability of the probit-models in the context of the Russian economy. The paper also outlines the macroeconomic trends of supply and demand in the oil market and the characteristics of the modeling in the conditions of unstable economic situation in Russia. This work fills a gap in the use and implementation of the probit-models for the Russian economy. We make the forecast of supply and demand in the oil market in the next 1-3 years. We believe that oil prices are not likely to go up. The effect of oil prices on the stock markets is generally asymmetrical, except of the Russian and Canadian stock markets, because Russian and Canadian economies depend on oil export indeed.
Предмет. Особенности ценообразования на рынке криптоактивов и взаимосвязь с ценами на активы на ф... more Предмет. Особенности ценообразования на рынке криптоактивов и взаимосвязь с ценами на активы на фондовых рынках
Цели. Изучение факторов влияния на динамику цены биткойна: существует ли корреляция с финансовыми индексами, такими как S&P 500, за счет наличия эффекта перетока волатильности (spillover effect), характерного для финансовых рынков.
Методология. Используется традиционный частотный подход в квантильной регрессии на основе Байесовского метода.
Результаты. Волатильность цены биткойна имеет заметную корреляцию с волатильностью финансовых индексов, таких как S&P 500 за счет наличия эффекта перетока волатильности (spillover effect), характерного для финансовых рынков. Но четкой взаимосвязи между поисковыми запросами в системе Google и динамикой цены биткойна не обнаружено. Цены на биткойн движутся прежде всего под влиянием интереса инвесторов к криптовалюте как альтернативному инструменту сбережения.
Выводы и значимость. Практическая значимость работы заключаются в структуризации существующих знаний о факторах влияния на цену биткойна. Приведенные методики позволили определить наиболее влиятельные факторы, объясняющие динамику биткойна в 2017 г. В частности, выделены основные группы детерминант. Изменение цены было обусловлено увеличением полезности биткойна как инструмента для проведения расчетов, чему способствовала утрата доверия к национальным валютам и неопределенность относительно выхода Великобритании
из ЕС и провал многих начинаний Д. Трампа.
Finance Theory and Practice, 2018
The article analyzes the carry trade strategy in which, according to common definition, traders b... more The article analyzes the carry trade strategy in which, according to common definition, traders borrow a currency that has a low-interest rate and use the funds to buy a different currency that is paying a higher interest rate. The aim of this work is to form the optimal strategies and carry trade portfolio. The task of our study was to study the interdependence between the yield of the carry trade strategy and the USA stock market on the basis of a mathematical approach and offer a portfolio of currencies with the highest historical yield over the past
five years. The author used the model of relative risk aversion. We analyzed data on exchange rates, forward premium and real exchange rates for the Eurozone, as well as for countries of the Organization for Economic Cooperation and Development (OECD) such as Australia, Brazil, China, Japan, New Zealand, Russia, Switzerland, the United Kingdom and the United States of America. Carry trade’s yield is not tied to standard risk factors. Popular funding currency — the yen has experienced a strong jump of volatility as a result of the 2008–2009 crisis. A possible explanation for this reversal is investors’ appetite for risk. The author concluded that the most common carry trade strategies in the period from 2009 to 2014 were formed on the basis of two financing currencies (Japanese yen and the US dollar) and three investment currencies (Australian dollar, New Zealand dollar and Chinese yuan). After 2014, the US dollar ceases to be the funding currency, giving way to the Euro.
The optimal carry trade strategy is borrowing in the currencies of developed countries (EUR, JPY) and investing in the currencies of energy producing countries (RUB, BRL). There is a negative relationship between the volume of transactions based on the carry trade strategy and the yield of shares in the financing country. There is also a significant link between the yield of the carry trade strategy and the profitability of the USA stock market.
International Journal of Energy Economics and Policy, 2018
This paper proposes the degree of interdependence between the prices of crude oil and gross domes... more This paper proposes the degree of interdependence between the prices of crude oil and gross domestic product (GDP) of leading of countries such as Saudi Arabia and as the main suppliers of crude oil to the world market. The paper examines the theoretical aspects of oil pricing and investigation between the oil prices and GDP of leading oil producing countries. The main focus was on the results of empirical studies, which showed the strong relationship between prices for crude oil and GDP. Mutual dependence between prices and GDP was observed in Russia and Saudi Arabia.The developing the alternative sources of energy the countries will make the possibility to reform their own economy and make them less vulnerable to fluctuations in oil prices.
Journal of Reviews on Global Economics, 2018
Optimal investment strategy depends on the loan in currencies of developed economies (EUR, JPY) a... more Optimal investment strategy depends on the loan in currencies of developed economies (EUR, JPY) and lending in currency of energy economies (RUB, BRL). Since 2014, there has been a shift to euro funding as the currency of financing for carry trade against the backdrop of the European Central Bank (ECB) not changing the volume of incentives to accelerate economic growth. There is some evidence to support the use of euro as a funding currency for carry trade, such as the irrational behavior of the currency during the Greek shock in the middle of 2015. Thus, the impact of yen-based trading strategies on the Japanese stock market is unconventional. It also became evident that the relationship between the dynamics of US dollar and S&P 500 index is extremely uncertain. When risk appetite waned due to the high volatility, the money was back. The ECB's zero-rate monetary policy has some impact on the global stock market.
International Journal of Energy Economics and Policy, 2019
This paper proposes the effect of oil price shocks on the Russian economic indicators using time ... more This paper proposes the effect of oil price shocks on the Russian economic indicators using time series for the period 1991-2016 year to cover all of oil price shocks. The vector autoregressive and the Dickey-Fuller test were utilized to investigate the long-run and the short-run relationships between variables. From the results shows that one of the most important external impact factor is the world price of oil. The research suggests a positive and significant long-term relationship between oil prices and Russian GDP dynamics.
International Journal of Energy Economics and Policy, 2019
The paper proposes modification of auto-regressive integrated moving average model for finding th... more The paper proposes modification of auto-regressive integrated moving average model for finding the parameters of estimation and forecasts using exponential smoothing. The study use data Brent crude oil price and gas prices in the period from January 1991 to December 2016. The result of the study showed an improvement in the accuracy of the predicted values, while the emissions occurred near the end of the time series. It has minimal or no effect on other emissions of this data series. The study suggests that investors can predict prices analyzing the possible risks in oil futures markets.
IEEE Access, 2023
It is essential to supply the necessary electricity for both the increase in the quality of life ... more It is essential to supply the necessary electricity for both the increase in the quality of life of the citizens and the stable growth of the country's economy. For countries to have energy independence, they need to increase their electricity generation capacity. However, all alternatives required to increase electrical capacity have both advantages and disadvantages. Within this scope, it is not easy for countries to make the right investment decisions. Therefore, a comprehensive analysis is needed to determine the right investment policy. The purpose of this study is to evaluate the electricity production capacities of emerging markets. A new fuzzy decision-making model has been constructed to find a solution for this situation. The groups for the electricity production capacities are examined by the extension of DEMATEL with Quantum Spherical fuzzy sets and golden ratio. In the following stage, emerging seven economies are ranked by using QSF TOPSIS technique. This situation helps to understand which of these countries are more successful in generating electricity capacity effectively. The main novelty is to define the most significant electricity generation alternatives by a novel model that integrates DEMATEL and TOPSIS with QSFSs and golden ratio. The results demonstrate that solar photovoltaic is the most optimal way to increase electricity capacity of the countries. Additionally, China is the most successful emerging country to generate electricity in an efficient way. Countries should take some actions to increase their solar energy investments. First, it would be appropriate to provide tax exemptions to solar energy investors so that the costs of these projects can be decreased. Additionally, investments in solar energy technologies need to be further increased.
The performance assessment of renewable energy technologies, such as PV systems, is pivotal in pl... more The performance assessment of renewable energy technologies, such as PV systems, is pivotal in planning for hybrid energy systems. This work clears the way for researchers to construct the best PV-based hybrid systems by first performing performance analysis metrics suggested by IEC 61724 on several PV technology options, and then choosing the most technically sound option. Next, using HOMER Pro software, construct a PV/grid and battery hybrid system with effective PV technology. The performance of three PV technologies, i.e., monocrystalline silicon, polycrystalline silicon, and amorphous silicon is assessed to demonstrate how their performance varies depending on the location. Results showed that (m-Si) has greater performance than the other two PV technologies, with yearly array yields of 5.26 h/day, reference yields of 6.18 h/day, and final yields of 5.18 h/ day, a capacity factor of 14.31%, system losses of 0.076, and a performance ratio (PR) of 83.9%. The most effective configuration of the system under evaluation consists of a 72.8 kW PV connected to the grid and a 59.4 kW converter. The total NPC is expected to be Rs. 397,684fortheoptimalconfiguration,costingRs.397,684 for the optimal configuration, costing Rs. 397,684fortheoptimalconfiguration,costingRs.0,0493/ kWh. The additional electricity in the best situation is 977 kWh, which is insignificant compared to the system capacity. Two sensitivity variables, including changes in the main load, are anticipated to be 10% and 15% higher than the current value (1698.63 kWh) and the battery's minimum state of charge, with 20%, 25%, and 30% uncertainty, are addressed.
Frontiers in Environmental Science, 2023
The United Nations SDGs Report 2020 revealed that climatic variability victimized masses across t... more The United Nations SDGs Report 2020 revealed that climatic variability victimized masses across the globe in 2018 and the global average temperature would rise to 3.2°C during this century. The GHG emission reduction targets for 2030 were prioritized under the Paris Climate Agreement (PCA) of 2015 to keep the rise in global temperature below 1.5°C. Here, parallel action for climate adaptation is on top of it. However, targets for both adaptation and mitigation are lagging. Climatic variations will continue more likely with similar trends thus influencing the development needs vis-à-vis environmental security and sustainability of resources. It entails climate compatibility, particularly for the water security agenda for SDG-13 and Paris Climate Agreement (PCA), which requires an inclusive governance regime and ownership for national and sub-national scenarios. In this context, this paper aimed to assess existing water sector governance for climate compatible development (CCD) by taking the case of Pakistan which is among the top 10 countries vulnerable to climate change. Considering the limitations of available methodologies due to the involvement of various aspects and concepts of governance, an integrated multivariate mix-method model was formulated by combining rules and rights-oriented approaches. This MCDA-based model integrates six novel climate governance principles against six basic components of the basic institutional governance framework; Simple Multi-attribute Rating Technique (SMART) with a set of sectoral indicators of 09 criteria of climate compatible development (CCD). It proved well for this water sector case study with cross-sectional data from 340 key informant interviews (KIIs) and 17 focus group discussions (FGDs) in Pakistan, validated statistically. It can be used for periodic sectoral governance assessments for CCD.
This research paper analyzes revenue trends in e-commerce, a sector with an annual sales volume o... more This research paper analyzes revenue trends in e-commerce, a sector with an annual sales volume of more than 340 billion dollars. The article evaluates, despite a scarcity of data, the effects on e-commerce development of the ubiquitous lockdowns and restriction measures introduced by most countries during the pandemic period. The analysis covers monthly data from January 1996 to February 2021. The research paper analyzes relative changes in the original time series through the autocorrelation function. The objects of this analysis are Amazon and Alibaba, as they are benchmarks in the e-commerce industry. This paper tests the shock effect on the e-commerce companies Alibaba in China and Amazon in the USA, concluding that it is weaker for companies with small market capitalizations. As a result, the effect on estimated e-trade volume in the USA was approximately 35% in 2020. Another evaluation considers fuzzy decision-making methodology. For this purpose, balanced scorecard-based open financial innovation models for the e-commerce industry are weighted with multistepwise weight assessment ratio analysis based on q-rung orthopair fuzzy sets and the golden cut. Within this framework, a detailed analysis of competitors should be made. The paper proves that this situation positively affects the development of successful financial innovation models for the e-commerce industry. Therefore, it may be possible to attract greater attention from e-commerce companies for these financial innovation products.
SSRN Electronic Journal, 2022
In the world, the concentration of population in urban areas has led to the problem of increasing... more In the world, the concentration of population in urban areas has led to the problem of increasing load on urban infrastructure and greenhouse gases. To solve this problem, cities are being converted into smart cities. This paper presents the optimal operation and capacity planning of a smart city with renewable energy and combined cooling, heating and power system. In this study, clustering is applied to reduce the simulation time while maintaining the accuracy of the solution. Furthermore, the optimal capacity is examined by varying the price of renewable energy with the generation capacity. As a result, the simulation time is reduced from 4,960 [sec] to 2.66 [sec], and the error of the result is 0.4[%]. Compared to the case without renewable energy, the9 Electricity rate is reduced by 67.0[%] and the CO2 emission by 55.9[%]. To further reduce the CO2 emission, the price of renewable energy facilities needs to be reduced. In the last part of the paper, we vary the price of PV equipment and determine the PV equipment price that minimizes the operating cost and CO2 emissions to be less than 240 million yen. The simulations in this paper are performed using the optimization method Mixed integer linear programming (MILP) and the numerical analysis software MATLAB®.
Energy Strategy Reviews, 2023
The sub-Saharan Africa (SSA) region gathers the most vulnerable countries, which are criss-crosse... more The sub-Saharan Africa (SSA) region gathers the most vulnerable countries, which are criss-crossed geographically, making SSA countries extremely vulnerable to the influence of neighbouring countries. However, very few studies have considered the spillover effect of technical assistance in the recipient country. To fill the research gap, a dynamic space Dubin approach based on an asymmetric space weight matrix was developed. The results show the Moran's I value of technical assistance is positive, indicating that there is a positive correlation in space. Technical assistance is not unconditional free help, but with the strong subjective will of donor countries. SDM's estimation results show that the coefficient of the space lag term is greater than the coefficient of the time lag term, indicating that the spatial spillover effect can promote the power development of the recipient country more than the path dependence effect. Technical assistance to neighbouring countries can only improve the power development of the target country in the short term. In the long run, the mismatch effect of aid resources from neighbouring countries inhibits the power development of recipient countries. Therefore, technical assistance should be integrated with the situation of the recipient country in order to reduce energy poverty more effectively.
The purpose of the paper is to identify the factors of financial development that have the greate... more The purpose of the paper is to identify the factors of financial development that have the greatest impact on open innovation in 7 emerging countries. The analysis was performed featuring the MF-X-DMA method, as well as its further verification for autocorrelation and heteroscedasticity. The time period covers years from 2002 to 2020. The article states that the main indicators to improve financial development should enhance the process of bank lending and equity market development. An important area is the development of competition by providing equal access to information to all market participants in a continuously refining technical infrastructure. Regression analysis with the MF-X-DMA method confirms the statistical significance of this influence. The article fills the knowledge gap into the link between open innovations and the relatively low capitalization of the modern emerging countries' financial market, low liquidity in small cap stocks at the financial market and concentration of the banking sector, as well as risks arising in the process of globalization. Another analysis has also been conducted by generating a novel fuzzy decision-making model. In the first stage, the determinants of open innovation-based fintech potential are weighted for the emerging economies. For this purpose, M-SWARA methodology is taken into consideration based on bipolar q-ROFSs and golden cut. The second stage of the analysis includes evaluating the emerging economies with the determinants of open innovation-based fintech potential. In this context, emerging seven countries are examined with ELECTRE methodology. It found the most significant factor is the open innovation-based fintech potential.
In book: Eco-Friendly and Agile Energy Strategies and Policy Development, 2022
This chapter presents re-engineering environmental sustainability opportunities within constraine... more This chapter presents re-engineering environmental sustainability opportunities within constrained pandemic situations that suggest solutions. Climate change disaster and COVID-19 socioeconomic impacts are leading nations to dramatic tragedy. Simultaneously, increasing demand for energy are due to population, political competition, and industrial growth globally. At present, the pandemic attracts more attention due to its immediate effect. Ignoring climate change can have a worse consequence not only on the present but for the future generation in the long run. Therefore, re-engineering the current pandemic situation with a futurism outlook for saving the world will enable nations to transform and rethink strategies, policies, procedures, processes, and any actions that can cope with present and possible future pandemics and climate change tragedies.
Computational Economics, 2022
This article is dedicated analyzing the interdependence of oil prices and exchange rate movements... more This article is dedicated analyzing the interdependence of oil prices and exchange rate movements of oil exporting countries (the Russian ruble, Euro, Canadian dollar, Chinese yuan, Brazil real, Nigerian naira, Algerian dinar). The study also considers risk-based oil market spillovers in global crisis periods with integrated decision recommendation systems. For this purpose, a fuzzy decision-making model is created by considering the bipolar model and imputation of expert evaluations with collaborative filtering. The main contribution of this study is both its econometric analysis and evaluations based on expert opinions. This helps reach more crucial results. All three of the recent shocks (2008, 2012, 2020) in the oil market are transmitted to foreign exchange markets of oil-producing countries. At the same time, the last shock of 2020 caused by the COVID-19 pandemic has not yet been fully reflected on the Russian ruble exchange rate. Correlation parameters became weaker in the last year, as the Russian ruble correlation coefficient fluctuates between − 0.5 and 0.5. However, before 2020 the spillover effect had a higher significance (in the range from − 0.8 to − 0.1). Nigerian naira and Algerian dinar were showing almost the same movements, while the Russian Ruble was in a different trading range.
COVID-19 pandemic has made the future uncertain for many in general, but students in particular b... more COVID-19 pandemic has made the future uncertain for many in general, but students in particular because institutes suddenly shutting down, while this new transition has hit everyone differently. Still, it has left significant pressure on the students specifically. This pandemic has changed the ways of living-financially, physically, emotionally, and mentally. This study analyses the impact of COVID-19 on students' mental health. It covers the globe, how they have been dealing with it, and which coping mechanisms worked best for them during this time. The study also discussed how different financial backgrounds had left a different psychological impact on the students. The methodology adopted utilizes all the previous research and their data, which helped us determine the most worked solution vs the least worked solution. In addition to literature, data from UNICEF about education and COVID-19 are utilized to determine the adverse impact of COVID-19. This study has also briefly touched on the impact of remote learning on students' mental health and how students have coped with this sudden yet uncertain new change. The research has come up with some proven solutions for students to perform better academically during this uncertain time without compromising their mental health.
SSRN Electronic Journal, 2022
In the world, the concentration of population in urban areas has led to the problem of increasing... more In the world, the concentration of population in urban areas has led to the problem of increasing load on urban infrastructure and greenhouse gases. To solve this problem, cities are being converted into smart cities. This paper presents the optimal operation and capacity planning of a smart city with renewable energy and combined cooling, heating and power system. In this study, clustering is applied to reduce the simulation time while maintaining the accuracy of the solution. Furthermore, the optimal capacity is examined by varying the price of renewable energy with the generation capacity. As a result, the simulation time is reduced from 4,960 [sec] to 2.66 [sec], and the error of the result is 0.4[%]. Compared to the case without renewable energy, the9 Electricity rate is reduced by 67.0[%] and the CO2 emission by 55.9[%]. To further reduce the CO2 emission, the price of renewable energy facilities needs to be reduced. In the last part of the paper, we vary the price of PV equipment and determine the PV equipment price that minimizes the operating cost and CO2 emissions to be less than 240 million yen. The simulations in this paper are performed using the optimization method Mixed integer linear programming (MILP) and the numerical analysis software MATLAB®.
Modern methods of lichen indication allow assessing the impact of climate change and air pollutio... more Modern methods of lichen indication allow assessing the impact of climate change and air pollution on ecosystem health. The purpose of this study was to evaluate the general state of atmospheric air in urban ecosystems of cities and towns using lichen indication methods. The objectives of the study included identifying lichen indicator species, as well as assessing the response of these species to various pollutants (e.g., lead, iron, manganese). The study was conducted in 2017 in the Bryansk region of the Russian Federation (9 settlements in total) and the Oryol region (1 settlement-the city of Oryol). Four hundred samples belonging to epiphytic lichens were collected. Additional 300 and 137 samples of epiphytic lichens were used for chemical and toxicological analyses, respectively. The following two generally accepted lichen indicator indices were calculated: poleotolerance index (PI) and atmospheric purity index (API). When calculating the latter, the lichen species Xanthoria parietina was used as the baseline. Epiphytic lichens in small settlements were represented by 50 species (28 genera, 8 families). In large cities, 55 (Bryansk) and 53 (Oryol) species of epiphytic lichens were detected. The number of species in small settlements was 1.5 times lower than that of large cities. There were 8-15 and 25-32 species of epiphytic lichens in the central region and in the periphery of Bryansk, respectively. The number of epiphytic lichen species detected in the parks was 41. Within the territory of large cities, 17 species of lichens were identified as potential indicators, since they were found in every second or fourth sample. Maximum concentrations of lead were recorded in industrial areas of cities, as well as near major roads with traffic intersection and bridges and in some dormitory suburbs. This is a distinctive feature of large cities-the predominance of lead in lichen thalli, which is primarily associated with vehicles. In small cities in which there are no specific industrial enterprises (metallurgical plants, etc.), other heavy metals-manganese and iron-prevail in the thalli of lichens. In this work, new methods are adopted-mapping pollution with the use of nitrophilous epiphytic lichens that reflect the ongoing macro processes of nitrification in urban areas. The authors have proposed and tested the following lichen indicator methods: the use of indicator species (epiphytesnitrophytes) of various sensitivities and the study of their distribution within the territory. The mapping method has been substantiated, which takes into account the API and zoning of territories according to the level of general pollution. Among the indicator species, Xanthoria parietina turned out to be the most suitable one.
Journal of Air Transport Management, 2021
The classical revenue management problem consists of allocating a fixed network capacity to diffe... more The classical revenue management problem consists of allocating a fixed network capacity to different customer classes, so as to maximize revenue. This area has been widely applied in service industries that are characterized by a fixed perishable capacity, such as airlines, cruises, hotels, etc. It is traditionally assumed that demand is uncertain, but can be characterized as a stochastic process (See Talluri and van Ryzin (2005) for a review of the revenue management models). In practice, however, airlines have limited demand information and are unable to fully characterize demand stochastic processes. Robust optimization methods have been proposed to overcome this modeling challenge. Under robust optimization framework, demand is only assumed to lie within a polyhedral uncertainty set (Lan et al. (2008); Perakis and Roels (2010)). In this paper, we consider the multi-fare, network revenue management problem for the case demand information is limited (i.e. the only information available is lower/upper bounds on demand). Under this interval uncertainty, we characterize the robust optimal booking limit policy by use of minimax regret criterion. We present an LP (Linear Programming) solvable mathematical program for the maximum regret so our model is able to solve large-scale problems for practical use. A genetic algorithm is proposed to find the booking limit control to minimize the maximum regret. We provide computational experiments and compare our methods to existing ones. The results demonstrate the effectiveness of our robust approach.
The paper proposes the pricing in the oil market and the impact of oil prices on world stock indi... more The paper proposes the pricing in the oil market and the impact of oil prices on world stock indices. There is analysis of major trends in the oil market. We develop a model to predict the impact of oil prices on stock market indices for developed economies and Russia. This work propose a probit-model for forecasting capital markets trends using Brent pricing, three-month interest rates of the money market, consumer price index, GDP growth rate as a binary dependent variables. The trends of pricing in different stages of development of the oil market make the on stock indices, as developed countries and Russia. The practical significance of this work lies in the structuring of existing knowledge on the applicability of the probit-models in the context of the Russian economy. The paper also outlines the macroeconomic trends of supply and demand in the oil market and the characteristics of the modeling in the conditions of unstable economic situation in Russia. This work fills a gap in the use and implementation of the probit-models for the Russian economy. We make the forecast of supply and demand in the oil market in the next 1-3 years. We believe that oil prices are not likely to go up. The effect of oil prices on the stock markets is generally asymmetrical, except of the Russian and Canadian stock markets, because Russian and Canadian economies depend on oil export indeed.
Предмет. Особенности ценообразования на рынке криптоактивов и взаимосвязь с ценами на активы на ф... more Предмет. Особенности ценообразования на рынке криптоактивов и взаимосвязь с ценами на активы на фондовых рынках
Цели. Изучение факторов влияния на динамику цены биткойна: существует ли корреляция с финансовыми индексами, такими как S&P 500, за счет наличия эффекта перетока волатильности (spillover effect), характерного для финансовых рынков.
Методология. Используется традиционный частотный подход в квантильной регрессии на основе Байесовского метода.
Результаты. Волатильность цены биткойна имеет заметную корреляцию с волатильностью финансовых индексов, таких как S&P 500 за счет наличия эффекта перетока волатильности (spillover effect), характерного для финансовых рынков. Но четкой взаимосвязи между поисковыми запросами в системе Google и динамикой цены биткойна не обнаружено. Цены на биткойн движутся прежде всего под влиянием интереса инвесторов к криптовалюте как альтернативному инструменту сбережения.
Выводы и значимость. Практическая значимость работы заключаются в структуризации существующих знаний о факторах влияния на цену биткойна. Приведенные методики позволили определить наиболее влиятельные факторы, объясняющие динамику биткойна в 2017 г. В частности, выделены основные группы детерминант. Изменение цены было обусловлено увеличением полезности биткойна как инструмента для проведения расчетов, чему способствовала утрата доверия к национальным валютам и неопределенность относительно выхода Великобритании
из ЕС и провал многих начинаний Д. Трампа.
Finance Theory and Practice, 2018
The article analyzes the carry trade strategy in which, according to common definition, traders b... more The article analyzes the carry trade strategy in which, according to common definition, traders borrow a currency that has a low-interest rate and use the funds to buy a different currency that is paying a higher interest rate. The aim of this work is to form the optimal strategies and carry trade portfolio. The task of our study was to study the interdependence between the yield of the carry trade strategy and the USA stock market on the basis of a mathematical approach and offer a portfolio of currencies with the highest historical yield over the past
five years. The author used the model of relative risk aversion. We analyzed data on exchange rates, forward premium and real exchange rates for the Eurozone, as well as for countries of the Organization for Economic Cooperation and Development (OECD) such as Australia, Brazil, China, Japan, New Zealand, Russia, Switzerland, the United Kingdom and the United States of America. Carry trade’s yield is not tied to standard risk factors. Popular funding currency — the yen has experienced a strong jump of volatility as a result of the 2008–2009 crisis. A possible explanation for this reversal is investors’ appetite for risk. The author concluded that the most common carry trade strategies in the period from 2009 to 2014 were formed on the basis of two financing currencies (Japanese yen and the US dollar) and three investment currencies (Australian dollar, New Zealand dollar and Chinese yuan). After 2014, the US dollar ceases to be the funding currency, giving way to the Euro.
The optimal carry trade strategy is borrowing in the currencies of developed countries (EUR, JPY) and investing in the currencies of energy producing countries (RUB, BRL). There is a negative relationship between the volume of transactions based on the carry trade strategy and the yield of shares in the financing country. There is also a significant link between the yield of the carry trade strategy and the profitability of the USA stock market.
International Journal of Energy Economics and Policy, 2018
This paper proposes the degree of interdependence between the prices of crude oil and gross domes... more This paper proposes the degree of interdependence between the prices of crude oil and gross domestic product (GDP) of leading of countries such as Saudi Arabia and as the main suppliers of crude oil to the world market. The paper examines the theoretical aspects of oil pricing and investigation between the oil prices and GDP of leading oil producing countries. The main focus was on the results of empirical studies, which showed the strong relationship between prices for crude oil and GDP. Mutual dependence between prices and GDP was observed in Russia and Saudi Arabia.The developing the alternative sources of energy the countries will make the possibility to reform their own economy and make them less vulnerable to fluctuations in oil prices.
Journal of Reviews on Global Economics, 2018
Optimal investment strategy depends on the loan in currencies of developed economies (EUR, JPY) a... more Optimal investment strategy depends on the loan in currencies of developed economies (EUR, JPY) and lending in currency of energy economies (RUB, BRL). Since 2014, there has been a shift to euro funding as the currency of financing for carry trade against the backdrop of the European Central Bank (ECB) not changing the volume of incentives to accelerate economic growth. There is some evidence to support the use of euro as a funding currency for carry trade, such as the irrational behavior of the currency during the Greek shock in the middle of 2015. Thus, the impact of yen-based trading strategies on the Japanese stock market is unconventional. It also became evident that the relationship between the dynamics of US dollar and S&P 500 index is extremely uncertain. When risk appetite waned due to the high volatility, the money was back. The ECB's zero-rate monetary policy has some impact on the global stock market.
International Journal of Energy Economics and Policy, 2019
This paper proposes the effect of oil price shocks on the Russian economic indicators using time ... more This paper proposes the effect of oil price shocks on the Russian economic indicators using time series for the period 1991-2016 year to cover all of oil price shocks. The vector autoregressive and the Dickey-Fuller test were utilized to investigate the long-run and the short-run relationships between variables. From the results shows that one of the most important external impact factor is the world price of oil. The research suggests a positive and significant long-term relationship between oil prices and Russian GDP dynamics.
International Journal of Energy Economics and Policy, 2019
The paper proposes modification of auto-regressive integrated moving average model for finding th... more The paper proposes modification of auto-regressive integrated moving average model for finding the parameters of estimation and forecasts using exponential smoothing. The study use data Brent crude oil price and gas prices in the period from January 1991 to December 2016. The result of the study showed an improvement in the accuracy of the predicted values, while the emissions occurred near the end of the time series. It has minimal or no effect on other emissions of this data series. The study suggests that investors can predict prices analyzing the possible risks in oil futures markets.