Oil and Gas Budget Revenues in Russia after Crisis in 2015

The paper propose the energy market crisis impact on the Russian budget revenues in 2015. We develop the model to forecast the impact of oil prices on budget revenues in Russia. The practical significance of this work lies in the structuring of existing knowledge on oil crisis impact on the Russian budget. Brent crude oil prices were in the range of 115-79 dollars per barrel in 2014. The cyclical strengthening of US dollar and political factors have led to an increase in supply in the oil market by more than 20%.  In 2015, we saw a decline in oil prices below $ 40 per barrel. The strengthening of the United States dollar was a major factor in the decline, as it was in the middle of 2001, when the price fell by about a one third before starting a long-term sharp increase. Keywords: oil price forecasting, budget revenues, oil and gas impact. JEL Classifications: E37, F20, G15. DOI: https://doi.org/10.32479/ijeep.663

Analysis of financial development and open innovation oriented fintech potential for emerging economies using an integrated decision-making approach of MF-X-DMA and golden cut bipolar q-ROFSs

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

Optimal Carry Trade Strategy Based on Currencies of Energy and Developed Economies

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

Pricing in Oil Market and Using Probit Model for Analysis of Stock Market Effects

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. Keywords: oil price forecasting, stock market returns, probit-model. JEL Classifications: E37, F20, G15

Volatility Spillover Effect between Stock and Exchange Rate in Oil Exporting Countries

This paper proposes the volatility spillover effect between stock and foreign exchange markets in both directions in oil exporting countries – Russia and Brazil. The data sample consists of daily observations. The method is based on FIGARCH model of the long memory. For emerging markets, volatility spillover is observed mainly in one direction: from the currency market to stock market. Calculations show that long memory is present in the dynamics of volatility, when models take into account structural breaks and frictions. We develop a model to predict the impact of oil prices on stock market indices for Russia, Brazil. The volatility spillover effect is observed in one direction: from the exchange rate to stock market. Calculations show that long memory is present in the dynamics of volatility, when models take into account structural breaks and frictions. This paper focuses on new method for forecasting of volatility (taking into account the structural breaks) on the base of FIGARCH model. The financial markets became more integrated after the World Economic Crisis of 2008-2009. The paper shows that volatility can be predicted using the FIGARCH model if the structural breaks are incorporated in the model. The paper should be of interest to readers in the areas of economic forecasting on the base of long memory models. Keywords: Efficient market hypothesis, stock indexes, exchange rates, FIGARCH model, structural breaks. JEL Classifications: C51, C58, F31, G12, G1

Market capitalization shock effects on open innovation models in e-commerce: Golden cut q-rung orthopair fuzzy multicriteria decision-making analysis

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.Ministry of Education and Science of the Russian Federatio

Bitcoin mempool growth and trading volumes: Integrated approach based on QROF Multi-SWARA and aggregation operators

Investors are looking for objects in which they invest their funds successfully, evaluating the effectiveness of alternative markets and their instruments. Historically, cash flow indicators most effectively reflected the mood of the masses in relation to any financial asset, both in the short-and long-term. This article examines in detail the queue of already completed, but not confirmed transactions in the bitcoin network. The mempool is able to timely display the growth in the number of transactions awaiting confirmation, which makes it a leading indicator of future cash flows that could affect the trading volumes and market prices of bitcoin. This study evaluates bitcoin mempool priorities and two different analyses have been conducted for this purpose. Firstly, the mempool periods are examined through a statistical analysis. Secondly, the performance determinants of mempool are assessed with q-ROF Multi-SWARA. In addition to q-ROF sets, weights are computed with IFS and PFS. Demonstrated here is that the results of all fuzzy sets are identical. This outcome explains the reliability of the findings and they indicate that a transaction is the most important determinant of the bitcoin mempool. It emerged that the adjusted mempool data (+16.7%) for 7-day and 30-day moving averages was able, with a time lag of 24–48 h, to indicate significant volatility of future bitcoin trading volumes (+1.6%) on average. The obtained values confirm the empirical conclusion reached here that the mempool growth leads to cash flow growth. An increase in future cash flows results in a substantial rise in future trading volumes. The key takeaway from the analysis is that mempool is able to effectively predict future increases in trading volumes based on the prior cash flow growth projected into mempool growth. However, as a price indicator, mempool does show mixed results with mostly uncertainty in the direction of price movement