Economic Indicators Research Articles

Regulators for ensuring the sustainability of reproductive processes in industrial fruit growing

The necessity of developing a system of regulators to ensure the sustainability of reproductive processes in industrial fruit growing is substantiated. An assessment of the efficiency of fruit production in the Russian Federation is given. The factors influencing the decrease in the stability of reproductive processes in industrial fruit growing are identified: an increase in the cost of purchased resources; high cost of finished products; a reduction in the share of subsidies in the created cost of planting; the insufficiency of agricultural producers’ own financial resources for carrying out planned plantings renovations, updating production infrastructure funds and carrying out current production activities. Functional imbalances in the organization of reproductive processes in industrial fruit growing have been identified: internal structural imbalances, high resource intensity of production and technological processes, non-compliance with optimal comparability of production and economic indicators. Generalizing criteria for the sustainability of reproductive processes are systematized: the ability of the system to withstand negative impacts of an economic and natural nature; increasing the possibilities of expanded reproduction of all used resources; ensuring qualitative changes in the production, socio-economic, environmental parameters of the system; increasing the conditions for subsequent improvements, preventing production declines. The article characterizes and evaluates the effectiveness of existing regulators to ensure the sustainability of reproductive processes in industrial fruit growing (macroeconomic, technical, technological and economic). A system of regulators has been developed to ensure the stability of reproductive processes in industrial fruit growing in functional areas of influence. An algorithm is proposed to substantiate the necessary dimensionality of regulators to ensure the stability of reproductive processes in industrial fruit growing.

The state of the Russian agricultural machinery market under sanction pressure conditions

The article is devoted to assessing the development of the Russian market of agricultural machinery (AHT) over the past 10 years. An analysis of the production of the main types of agricultural products, market dynamics, changes in market structure, volumes of purchases by agricultural producers, and the presence of agricultural products in Russian agriculture are presented. For a comparative analysis of the agricultural tractors being sold, their main technical and economic indicators are presented. Calculations were made of the main operational properties (performance, fuel consumption) of tractors of similar traction classes of the Belarus family and Chinese-made tractors presented on the Russian market. Based on correlation analysis, the relationship and direction of indicators were verified: renewal rates, retirement rates and the availability of a fleet of agricultural machinery; acquisition of agricultural equipment and renewal and disposal rates; acquisition of agricultural equipment and availability of agricultural machinery in agricultural organizations. Quite a strong relationship between the indicators: “purchase of agricultural products” and “availability in agricultural organizations” (correlation coefficient r = 0.676 — 0.99), a significant relationship between the indicators: “retirement rate” and “availability of combine harvesters” (correlation coefficient r = from — 0.588 to -0.664), “purchase of tractors” and “disposal coefficient” — r = –0.445, there is practically no relationship between the indicators: “purchase of tractors” and “availability of tractors” — r = –0.06, “renewal coefficient” and “availability grain harvesters” — r = -0.183, “purchase of forage harvesters” and “disposal rate” — r = –0.187. When analyzing the performance properties determined in this study, it was revealed that Chinese tractors presented on the agricultural machinery market will provide significant competition to tractors of the Belarus family.

IMPACTO AMBIENTAL POR USO DE PLAGUICIDAS Y SUSTENTABILIDAD DEL SISTEMA PRODUCTIVO DEL MAÍZ AMARILLO DURO EN HUAURA, PERÚ

<p><strong>Background:</strong> Hard yellow maize (MAD) is one of the main crops in economic, social and environmental terms worldwide, however, it is managed through conventional agriculture which entails a high dependence on agrochemical inputs, which cause a negative impact on the agroecosystem and through this study it will be possible to identify the critical points and establish solutions for them. <strong>Objective: </strong>To determine the coefficient of environmental impact of pesticides in the field and find the general sustainability index of the MAD production units. <strong>Objective:</strong> Determine the coefficient of environmental impact of pesticides in the field and find the general sustainability index of the MAD production units. <strong>Methodology:</strong> The environmental impact (EI ha<sup>-1</sup>) of pesticides in the field was evaluated by calculating the environmental impact coefficient (EIQ), concentration of the active ingredient, dose and number of applications. In addition, sustainability was determined through multicriteria analysis by applying 85 questionnaires with structured questions to farmers whose main activity is MAD, with economic, social and environmental indicators standardized on a scale of 1 to 5. <strong>Results:</strong> The study showed that the EI ha<sup>-1</sup> of MAD was 105.11 rated as high, which generates a negative impact on the environment and a high risk for farmers who apply these pesticides. It was also found that the sustainability index of the social and economic dimensions was 3.56 and 3.18 respectively, while the environmental index (2.64) obtained a value below the minimum sustainable threshold, therefore the MAD production system in Huaura is not sustainable. The analysis found the critical points: levels and types of fertilization (2.74), incorporation of organic matter (2.33), crop residue management (1.51), living barriers (1.36), pest control method (2.49), frequency of pesticide applications (2.53), irrigation system (2.54), level of education (2.96), quality of technical assistance and training (2.8), income from other activities (2.9) and marketing channel (1.82). <strong>Implications:</strong> Timely intervention on critical points allows establishing solution options and improving pesticide management.<strong> Conclusion: </strong>The study showed that the IE ha<sup>-1</sup> of MAD was high, indicating that the pesticides used for chemical pest and disease control generate a negative impact on the environment and a high risk for farmers who apply these pesticides. Likewise, it was found that the MAD production system is not sustainable. Therefore, the identification of the critical points allows the establishment of strategies to strengthen the MAD agroecosystem in Huaura, Peru.</p>

Influence of a new saponite-containing feed additive on the productive qualities of broiler chickens

The article presents the results of the study on the introduction of a saponite-containing mineral feed additive of natural origin into the diet of ROSS-308 broiler chickens in the amount of 1, 3 and 5 kg per ton of feed. An increase in the average daily gain by 3.7; 4.3 and 4.4 g, respectively, and in the absolute gain by 154.7; 174.9 and 181.3 g in the period from 1 to 42 days of age was found. At the time of slaughter, the live weight of chickens in the 1st and 2nd experimental groups significantly exceeded the control: by 174.6 (6.3%; P ≤ 0.001) and 154.6 g (5.6%; P ≤ 0.001). The survival rate of the experimental group chickens was 6.7% higher. In the blood of chickens from experimental groups 1–3, compared with the control analogs, an increase in total protein by 1.5; 2.2 and 2.1 g/l, calcium by 0.28; 0.21 and 0.29 mmol/l, phosphorus by 0.3; 0.43 and 0.42 mmol/l was recorded. A conclusion was made about an increase in the economic and biological indicators of broiler chickens when adding a saponite-containing mineral supplement to the diet, due to the enrichment of the compound feed with minerals and the high sorption capacity of the above-mentioned supplement, while the best effect was achieved when including it in the feed in the amount of 3 kg per ton.

Statutory Bodies and Other Attached Offices under the Ministry of Micro, Small and Medium Enterprise

The MSME sector has merged as a highly vibrant and dynamic sector in the Indian economy. It is fostering entrepreneurship and generating large employment opportunities. Further, it is widening its domain sectors by producing diverse range of products and services. M/o MSME is promoting growth and development of the Sector, including Khadi, Village and Coir Industries, in cooperation with the other concerned Ministries / Departments, State Governments and other Stakeholders by supporting the existing enterprises, using cutting edge technologies and encouraging creation of new enterprises. A number of statutory and non-statutory bodies work under the M/o of MSME include the Khadi and Village Industries Commission (KVIC), Coir Board, National Small Industries Cooperation (NSIC), National Institute for Micro, Small and Medium Enterprises (NIMSME), and Mahatma Gandhi Institute for Rural Industrialization (MGIRI). Details about the authorization and execution of these bodies are presented in this article.

A novel FMECA method for CNC machine tools based on D-GRA and data envelopment analysis

Failure Modes, Effects, and Criticality Analysis (FMECA) is a commonly used method for analyzing system reliability. It is frequently applied in identifying weak points in the reliability of CNC machine tools. However, traditional FMECA has issues such as vague descriptions of risk factors, equal treatment of risk factors, and unclear directions for improving weak points. In response to the issue of vague descriptions of risk factors, this paper further expands severity (S) into machine hazard (M) and personal hazard (P), and subdivides detectability (D) into functional structural complexity (D1) and detection cost (D2). In addressing the issue of treating risk factors equally, this paper integrates Distance Analysis Method (DAM) and Grey Relational Analysis (GRA) to propose Distance-Grey Relational Analysis (D-GRA). Subsequently, based on the D-GRA method, the weights of each risk factor were determined by comprehensively considering expert system scores and actual economic loss indicators. In response to the issue of unclear improvement directions for weak points, this paper introduces the BCC model. It treats common failure modes of CNC machine tools as decision-making units within the BCC model, refines risk factors as input indicators, and evaluates the efficiency values of each decision-making unit based on various actual losses as output indicators. Through efficiency value analysis, it proposes improvement directions for weak points. Then, based on the weights of risk factors and the efficiency values of failure modes, a modified calculation method for the new Risk Priority Number (RPN) is proposed to amend the traditional RPN, This paper takes the electric spindle system of a certain machining center as an example, applies the proposed method to rank common failure modes with the new RPN, and compares it with other RPN calculation methods to verify the rationality of the proposed approach. Finally, it presents improvement directions for reliability enhancement.

The Recent Progress China Has Made in Mining Method Transformation, Part I: Shrinkage Method Transformed into Backfilling Method

The shrinkage method is one of the earliest and most widely used mining methods in China’s underground mines, but shrinkage mining is often accompanied by a number of problems and safety hazards. With the continuous improvement of the filling process and filling material preparation and transportation technology, the application of trackless equipment such as drill jumbo and LHD (Load-Haul-Dump), and the continuous promulgation of mine safety and environmental protection policies, a large number of mines have transformed from the shrinkage method to the filling mining method. Suichang Gold Mine has improved its technical and economic indexes after transformation from the mine shrinkage method to the filling method. Its daily production capacity has increased from 30 t/d to 110 t/d, the dilution rate has decreased from 40% to 10%, the comprehensive recovery rate has increased from 95% to 98%, and the cost saving and revenue increase in the middle section of the test area of +180 m~+240 m has totaled 18,151,000 RMB.

The “Simultaneous Development of Quantity and Quality”: Research on the Impact of the Digital Economy in Enabling Manufacturing Innovation

The digital economy is the future direction of global development, and its innovation-driven effect has become the focus of scholars. This study takes China’s Shanghai and Shenzhen A-share listed manufacturing enterprises from 2012 to 2022 as research samples and uses a text-analysis method to measure the comprehensive index of the regional digital economy. Based on the dual dimensions of quantity and quality, we empirically test the actual impact of the digital economy on manufacturing innovation. The results show the following: (1) The internal components of the digital economy include data elements, digital technology, and digital infrastructure, which have a significant role in promoting manufacturing innovation. (2) There are significant differences in the release of digital economy innovation dividends among enterprises with different growth stages, property rights, and technology endowments. (3) From the macro-regional level, the rational allocation of R&D personnel and R&D funds is an effective way for the digital economy to enable manufacturing innovation. In addition, from the micro-enterprise level, factor-combination and information-optimization effects are also effective ways for the digital economy to drive manufacturing innovation. (4) Further, the impact of the digital economy on manufacturing innovation is nonlinear, with changes in internal composition. This study helps to break through the obstacles of the digital economy to achieve innovation empowerment and provides a theoretical reference for the manufacturing industry to continue to spur innovation vitality.

Development of New Electricity System Marginal Price Forecasting Models Using Statistical and Artificial Intelligence Methods

The System Marginal Price (SMP) is the cost of the last unit of electricity supplied to the grid, reflecting the supply–demand equilibrium and serving as a key indicator of market conditions. Accurate SMP forecasting is essential for ensuring market stability and economic efficiency. This study addresses the challenges of SMP prediction in Turkey by proposing a comprehensive forecasting framework that integrates machine learning, deep learning, and statistical models. Advanced feature selection techniques, such as Minimum Redundancy Maximum Relevance (mRMR) and Maximum Likelihood Feature Selector (MLFS), are employed to refine model inputs. The framework incorporates time series methods like Multilayer Perceptron (MLP), Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Convolutional LSTM (ConvLSTM) to capture complex temporal patterns, alongside models such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Extreme Learning Machine (ELM) for modeling non-linear relationships. Model performance was evaluated using the Mean Absolute Percentage Error (MAPE) across regular weekdays, weekends, and public holidays. XGBoost combined with MLFS consistently achieved the lowest MAPE values, demonstrating exceptional accuracy and robustness. Among all of the models, XGBoost combined with MLFS consistently achieved the lowest MAPE values, demonstrating superior accuracy and robustness. The results highlight the inadequacy of traditional models like ARIMA and SARIMA in capturing non-linear and highly volatile patterns, reinforcing the necessity of using advanced techniques for effective SMP forecasting. Overall, this study presents a novel and comprehensive approach tailored for complex electricity markets, significantly enhancing predictive reliability by incorporating economic indicators and sophisticated feature selection methods.

Performance response analysis and optimization for integrated renewable energy systems using biomass and heat pumps: a multi-objective approach

The focus of this study is to optimize the exploration of biomass-driven multi-energy systems, which include combined heat, power, and gas generation. The objective is to enhance the thermal, environmental, and economic performance indicators of the system. The optimization objectives encompass the quantities of internal combustion engines and air source heat pumps, as well as the dimensions of tanks utilized for anaerobic fermentation. A mathematical model was developed to optimize multiple objectives for combined heat, power, and gas generation systems by employing multi-objective intelligent optimization algorithms. The validation and analysis were conducted using rural residences in Lanzhou, Gansu Province, China, as a case study. The sensitivity analysis of biomass gasification combined heat and power systems was conducted from both technical and cost perspectives, examining the dynamic impact characteristics on the outcomes of multi-objective optimization. The findings indicate that the annual energy-saving rate of the optimized combined generation system decreased from 3.62% to -6.78%, while the growth in carbon emissions reduction rate increased from 76.05 to 81.38%, and the annual cost-saving rate grew from 0.97 to 14.96%. The power generation efficiency of the cogeneration station and hydraulic retention time were found to have a significant impact on the multi-objective optimization results of the combined generation system among the technical parameters. The unit cost of anaerobic fermentation tanks had a more significant impact on the multi-objective optimization results in terms of cost parameters, compared to the price of biogas residue.

Forecasting urban unemployment rate in China using ARIMA model

Abstract. The urban unemployment rate is a significant economic indicator that has long drawn researchers interest. Monitoring and predicting changes in the unemployment rate can help in understanding economic trends and implementing appropriate measures. This article aims to forecast urban unemployment rates in China. By collecting previous surveyed urban unemployment rates in China, this article will generate and compare various ARIMA models in order to identify the one with the best forecasting accuracy. The forecast results of the selected model state that the unemployment rate will remain almost unchanged, around 5%, in the second half of 2024 and throughout 2025. Fluctuations are expected to be between 0.01% and 0.03%. The number is much lower than the peak during the pandemic, but it is still above the historical average. This article argues that Chinas economy is gradually stabilizing, and the post-pandemic measures have been effective but are still insufficient. The government still needs to implement additional actions.

ПОДХОДЫ К ОСУЩЕСТВЛЕНИЮ РИСК-МЕНЕДЖМЕНТА В УСЛОВИЯХ НЕОПРЕДЕЛЕННОЙ И ТУРБУЛЕНТНОЙ ВНЕШНЕЙ СРЕДЫ (НА ПРИМЕРЕ ЗЕРНОВОГО ПРОИЗВОДСТВА)

In the modern Russian socio-economic system, there is an objective increase in uncertainty and turbulence, which requires adequate management responses. In connection with the sanctions pressure, in agriculture the strategy of reducing the risks of import dependence is becoming a stimulating factor for development. The study was conducted on the example of grain production development, which has some specifics from the standpoint of management and, in particular, risk management. The purpose of the study is to generalize approaches to risk management in an uncertain and turbulent external environment and to develop on this basis a risk distribution scheme between management entities in the risk management system adapted to the specifics of grain production. It is shown that the increase in the values of economic indicators of grain production is influenced by natural and climatic conditions, they determine the quality of grain products, costs and the complex of applied agrotechnological measures. In addition to the observed "standard" variability of natural and climatic conditions, the study also identifies extreme risk events that require forecasting and consideration when managing grain production. Also, risks in the considered sphere are caused by diversity and interdependence of such factors as natural and climatic, soil, technological, economic, social, legal, etc. In their mutual interweaving, these factors determine annual fluctuations of economic indicators (yield, gross harvest, sown area) in grain production in Russia. As a result of the study, it was established that risk management procedures in the sphere of grain production should be carried out according to the hierarchical principle with the allocation of at least two levels: the coordinating level - the executive level. Based on this idea, an industry structural and functional model of risk management at various levels of decision-making has been developed. This model has the property of dualism: some levels are simultaneously coordinating, offering strategic solutions to lower levels, and executive - for higher structures. Implementation of the developed model in the practice of risk management in grain production will increase its sustainability and predictability.

ПОДХОДЫ К ОСУЩЕСТВЛЕНИЮ РИСК-МЕНЕДЖМЕНТА В УСЛОВИЯХ НЕОПРЕДЕЛЕННОЙ И ТУРБУЛЕНТНОЙ ВНЕШНЕЙ СРЕДЫ (НА ПРИМЕРЕ ЗЕРНОВОГО ПРОИЗВОДСТВА)

In the modern Russian socio-economic system, there is an objective increase in uncertainty and turbulence, which requires adequate management responses. In connection with the sanctions pressure, in agriculture the strategy of reducing the risks of import dependence is becoming a stimulating factor for development. The study was conducted on the example of grain production development, which has some specifics from the standpoint of management and, in particular, risk management. The purpose of the study is to generalize approaches to risk management in an uncertain and turbulent external environment and to develop on this basis a risk distribution scheme between management entities in the risk management system adapted to the specifics of grain production. It is shown that the increase in the values of economic indicators of grain production is influenced by natural and climatic conditions, they determine the quality of grain products, costs and the complex of applied agrotechnological measures. In addition to the observed "standard" variability of natural and climatic conditions, the study also identifies extreme risk events that require forecasting and consideration when managing grain production. Also, risks in the considered sphere are caused by diversity and interdependence of such factors as natural and climatic, soil, technological, economic, social, legal, etc. In their mutual interweaving, these factors determine annual fluctuations of economic indicators (yield, gross harvest, sown area) in grain production in Russia. As a result of the study, it was established that risk management procedures in the sphere of grain production should be carried out according to the hierarchical principle with the allocation of at least two levels: the coordinating level - the executive level. Based on this idea, an industry structural and functional model of risk management at various levels of decision-making has been developed. This model has the property of dualism: some levels are simultaneously coordinating, offering strategic solutions to lower levels, and executive - for higher structures. Implementation of the developed model in the practice of risk management in grain production will increase its sustainability and predictability.

Decoding Users’ Continuance Intentions towards Digital Financial Platforms in the Indian Economy

Indian financial sector has seen a dramatic change in recent years, with digital finance unlocking new possibilities for financial inclusion. This paper investigates the factors influencing the continuous usage intention and advocacy intention, regarding digital finance, in the Indian economy. Utilizing the Stimulus-Organism-Response (S-O-R) model, the study examines how ease of use, credibility and ubiquity (stimulus) could influence user trust, satisfaction, and engagement (organism), ultimately affecting their intention to use and recommend the service (response) continuously. Non-probability convenience sampling technique was used to select the study sample. Based on the results, features of digital financial platforms such as ease of use, credibility and ubiquity, were found to have a significant impact on user trust, satisfaction, and engagement. These factors partially mediate the stimulus and response variables. The research findings provide Digital Financial Service Providers (DFSPs) with practical guidance on creating and implementing user-centric platforms that create engagement and trust. User experience should be prioritized and making sure that platform should be accessible, easy to use and compatible with a variety of devices.

Технико-экономические показатели энергокомплекса при использовании ветроэнергетических установок для покрытия собственных нужд ТЭЦ

In accordance with the Russia Energy Strategy until 2035, within the framework of the implementation of energy-saving technologies in the power-generating sector, it is planned to use hybrid energy, which is one of the ways of transition from conventional generation to generation with a high share of renewable energy sources. However, to implement such complexes, it is necessary to conduct research that considers the natural and climatic characteristics of the region, its resource capabilities, as well as the mutual influence of conventional and renewable energy sources in the structure of generating equipment capacities. The wind potential at the construction site has been analyzed to assess the feasibility of incorporating wind turbines. Based on the technical characteristics of wind turbines and meteorological conditions, the model of wind turbines to be installed has been selected. Technical and economic indicators of the energy complex operation, providing for the use of wind power plants to partially cover the house load of CHPs have been obtained. The indicators are determined on an annual, monthly basis using the physical method of attributing the total fuel costs for heat and electricity output in case of their combined production. Operation of wind power plants as a part of the energy complex with CHP in winter has a positive effect on the process of thermal efficiency of combined heat and power generation, and in summer, on the contrary, leads to deterioration of the efficiency indicators. Relatively small fuel savings per year when using wind power plants as a part of the energy complex with CHP does not allow to consider the project cost-effective. The obtained results should be considered when making system-wide decisions on the development of renewable energy sources in parallel operation with fossil fuel power plants.

PREREQUISITES FOR THE APPLICATION OF MONETARY POLICY TOOLS OF THE "NEW REALITY" IN THE CONDITIONS OF THE GEOPOLITICAL IMPACT OF MILITARY AGGRESSION IN UKRAINE

The prospects of using a new type of monetary policy instruments, which determine modern significant changes in the development of global financial, economic and social relations, caused by the geopolitical influence of military aggression in Ukraine, are studied. Not only the negative financial and economic impact on the country victim of hostilities, i.e. Ukraine, was established. Problems with inflation and debt were also identified in the G7 countries, as well as in China due to the consequences of the war in Ukraine. It was determined that the financial system of countries that have close trade and monetary transactions with developed market countries will also have a significant impact of the global crisis. The financial and economic indicators of Ukraine, the G7 countries and China for the medium term are predicted. The influence of the main financial threats on the macroeconomic stability of the country's economy in the conditions of military aggression is determined, and the main instruments of monetary policy that would allow maintaining such stability are indicated. It is noted that the use of a new type of monetary policy in modern realities, based on non-traditional instruments, will contribute to overcoming the negative impact of military aggression in all countries that experience it.

ROLE OF FINANCIAL INSTRUMENTS IN ENSURING LIQUIDITY AND STABILITY OF THE CURRENCY MARKET OF UKRAINE IN THE CONDITIONS OF MILITARY CONFLICT

In the conditions of military actions, liquidity of the currency market is of critical importance for the financial stability and security of the state, which stipulates significant relevance of the issue of instruments of liquidity provision. The research aims to identify the influence of the instruments of the National Bank of Ukraine (NBU) on the liquidity of the currency market of Ukraine within the context of long-term military conflict.The methods of regression analysis, correlation analysis, and analysis of variance were used in the study to determine the leading factors that influence the liquidity of the currency market in Ukraine in the conditions of military conflict.The study of the liquidity of the currency market through the prism of linear regression reveals the relation between the core economic indicators and the level of liquidity of the currency market during the military conflict. The model with a coefficient of determination 0,774 was found to effectively describe 77,4% of liquidity variability, underlining the significant influence of such factors as central bank policies and macroeconomic conditions. Significant coefficients for central bank interventions (1,7867), regulatory measures (59,8199), volume of international aid (-1,5684) and inflation (-99,9780) indicate their influence on the liquidity of the currency market in the conditions of military conflict. The influence of regulatory measures with a correlation of 0,59 is especially important.The article emphasises the necessity for minimising dependence on external financing and inflation control through monetary measures to ensure price stability. Further study perspectives involve consideration of the influence of digital currency of central banks on the liquidity of the currency market.

MAIN STAGES OF DESIGNING RESOURCE-SAVING TECHNOLOGIES FOR INGOT DEFORMATION ON HYDRAULIC PRESSES

Objective. To study the technological process of forging large ingots on hydraulic presses in order to identify and reduce resource consumption. Research methods. A finite element method that makes it possible to assess the stress-strain state of a workpiece, the possibility of levelling it, and homogenising it by controlling the factors that form the optimal forging method for a given workpiece. Results. A resource-saving technological process based on the optimal forging method has been developed, which allows to bring the quality of the designed products to a new level and leads to an increase in technical and economic indicators of production. By controlling the stress-strain state of the metal, high quality forged products can be achieved and resource-saving technologies for forging forgings of high-alloy steel grades and alloys can be created. Scientific novelty. The factors that form the rational resource-saving technological process of plastic deformation and the method of forging large forgings from alloyed, stainless steels and alloys on hydraulic presses, as well as the directions of their optimisation, have been formed. The finite element method allows us to predict the distribution fields of the workpiece’s stress-strain parameters, metal microstructure, and grain size. Practical value. Practically grounded recommendations for optimal modes of forging ingots from tool steel grades were developed. This will reduce energy consumption, save time in the production of forged products and generally intensify the process of plastic deformation. The proposed recommendations can be applied not only in the processes of forging tool steel grades but also in other types of hot plastic deformation of metals of a wide range.

Predicting Gold Prices Through Machine Learning with Economic Indicators and Feature Selection Methods

The enormous fluctuation of the gold price in international markets gives predictive analysis an indispensable place for business firms, economists, and investors. With this in mind, this research aims to construct a machine learning model for gold price prediction based on past information and identify some leading patterns affecting the prices of such a commodity. The model thus covers a range of related financial and economic factors, be it past gold prices and inflation metrics, oil price vagaries, worldwide market indexes, and interest rate movements. Using machine learning algorithm approaches like Support Vector Machine (SVM), Random Forest, as well as Linear Regression approaches, the system is set to identify complex relationships prevailing in the data and provides predictions for short-term movements and long-term movements concerning price. The model will be trained and validated using historical data that includes the history of the gold price. In this respect, the findings of the study are relevant to stakeholders in financial forecasting who could make informed investment decisions. Additionally, the paper has outlined the method for feature selection that determines which factors are dominant in explaining the fluctuation of the gold price. The goal of the model, therefore, is to enhance its performance through prediction accuracy reduction in noise, recursive elimination of features, and application of correlation analysis. As a result, a robust evaluation of several machine algorithms, including support vector machines, allows the selection of a suitable model that best solves the prediction task. This approach to forecasting will therefore aid in the creation of instruments for risk management, automated trading techniques, and financial strategies for an individual as well as for organizations. Keywords: Support Vector Machine, Random Forest, machine learning, and gold price prediction; economic indicators, feature selection, and linear regression in the field of financial forecasting; erratic behaviour; and risk management.

Sectoral Performance of ESG Enabled Stocks during COVID-19 Pandemic in the Indian Stock Market

Over past one decade, there is significant rise in Environment, Social and Governance (ESG) enabled investment practices across the globe and Indian economy is no exception to that. The ESG-enabled investment options provide better investment avenues for investment for retail and institutional investors by ensuring the long-term sustainability of the business. The present study tries to assess whether there is any impact of ESG scores on performance of stocks at the time of COVID-19 pandemic period. The study compares the performance of stocks with high ESG score vis-à-vis stocks with low ESG scores during COVID-19 period for different sectors of Indian stock market. The study considers the data of 312 sample firms listed on BSE 500 index. The event study methodology is used to assess the impact of COVID-19 on Indian stocks. The stocks were further divided into three categories high score (top 30% of firms), medium (middle 40% of firms) and low (bottom 30% of the firms). The results of the study suggest that the investors were more confident about the performance and revival of firms that carry high ESG scores than firms with low ESG scores. The investors are confident about the long-term prospects and sustainability of the firms, and they tend to hold their investment in the firms with high ESG scores.