Price Fluctuations Research Articles

Unveiling an asymmetric relationship between global crude oil and local food prices in an oil-importing economy

AbstractRecent swift comovements of local food and global crude oil prices have attracted the attention of policymakers and researchers. To evaluate this relationship, many studies have used time series models to explore global crude oil and local food prices. However, robust research based on advanced nonlinear time series models that incorporate control variables for their formation is lacking. In this paper, nonlinear techniques are applied to assess the asymmetric nexus between Brent oil prices and local retail food prices in Slovakia. To estimate this value, we extend the single-threshold NARDL approach to the MTNARDL model. The nominal exchange rate and industrial production index are used as the control variables. Compared with conventional NARDL models, the MTNARDL model provides a more detailed representation of global oil‒local food price linkages and detects the asymmetric effect of global oil prices on food prices from both long- and short-term perspectives. Interestingly, with respect to long- and short-term food price volatility, changes in response to oil price fluctuations are greatest under a regime with rather a small number of positive and moderate changes.

A Study on Stock Analysis of Automobile Industries

This study investigates the stock movement of automobile companies listed on the NIFTY50 index, focusing on five major firms: TVS Motor, MRF, Ashok Leyland, Maruti Suzuki, and Tata Motors. Using quarterly and annual data from January 2021 to December 2021, the analysis identifies key trends and volatility factors impacting stock prices in the automotive sector. Key findings suggest that fluctuations in stock prices are influenced by quarterly performance, industry trends, and macroeconomic conditions. Additionally, the report highlights the impact of the COVID-19 pandemic on the sector, with companies facing challenges such as reduced demand, increased costs, and supply chain disruptions. The study concludes that stock movements in this industry are volatile, urging investors to monitor these fluctuations closely before making investment decisions.

Integrating fast iterative filtering and ensemble neural network structure with attention mechanism for carbon price forecasting

Accurate carbon price forecasts are crucial for policymakers and enterprises to understand the dynamics of carbon price fluctuations, enabling them to formulate informed policies and investment strategies. However, due to the non-linear and non-stationary nature of carbon price, traditional models often struggle to achieve high prediction accuracy. To address this challenge, this study proposes a novel integrated prediction framework designed to enhance forecast accuracy. First, the carbon price series is decomposed into a series of smoother subsequences using fast iterative filtering (FIF). Subsequently, an integrated prediction model, AM-TCN-LSTM, is constructed, incorporating the attention mechanism (AM), temporal convolutional networks (TCN), and long short-term memory (LSTM) neural networks. The attention mechanism adaptively captures complex features from multiple factors, while the TCN-LSTM efficiently extracts temporal features from the sequences. Finally, the results from each subsequence are aggregated to generate the final prediction. Five carbon markets in china: Guangdong, Hubei, Shenzhen, Beijing, and Shanghai were selected to verify the validity of the proposed model. Various comparative models and evaluation metrics were employed to assess performance. The results demonstrate that: (1) the TCN-LSTM model achieves higher prediction accuracy compared to single models. (2) FIF is a more effective decomposition method with superior performance compared to EMD-based methods. (3) The proposed model exhibits the highest predictive capability, with MAE values of 0.0964, 0.1403, 1.9476, 2.0848, and 0.5029 for the five carbon markets, significantly outperforming comparison models. (4) The attention mechanism effectively captures the influence of multiple factors on carbon price, particularly within the short-term components.

The impact of dollar price fluctuations on the GDP of developing countries: Iraq as a model

The exchange rate is a tool of monetary policy, which is a matter of monetary policy, determined by the Central Bank of Iraq, as well as the subject of the exchange rate of complex topics, and the importance of this research lies in understanding the impact of dollar price fluctuations on the Iraqi economy, which contributes to enhancing knowledge about how external factors interact with local economic conditions, providing valuable recommendations for decision-makers to design effective strategies to deal with these fluctuations and achieve greater economic stability. The descriptive approach was used to collect and analyze economic data related to dollar price fluctuations and its impact on GDP, which helps to understand the relationships between these variables in Iraq during the period (2003-2024), the most important conclusions reached by the research that the general trend indicates sustainable growth in GDP, but economic challenges, such as exchange rate fluctuations and inflation, need to be effectively addressed. The government and central bank should promote economic stability through effective monetary policies that support growth and maintain exchange rate stability.

Dynamic Linkages Between U.S and Indian Equity Markets: An Empirical Study

In this study, we investigate the dynamic linkages between US and Indian equity markets by examining the daily Total Return Index values of NIFTY 50 and NASDAQ Composite over a decade ending October 2024. While the indices are not found to be cointegrated, suggesting potential long-term diversification benefits, they exhibit significant short-term correlations. Through various statistical analyses including regression, correlation, and variance tests, we find strong positive associations between the markets, with NASDAQ Composite movements explaining approximately 89% of variations in NIFTY 50 Total Return Index (TRI). The study reveals distinct volatility patterns, with the Indian market showing higher price fluctuations but stronger absolute growth compared to its US counterpart. Despite the strong correlation, both markets maintain unique characteristics influenced by their respective economic fundamentals. The findings demonstrate the evolving nature of market integration between developed and emerging economies, offering valuable insights for international portfolio diversification strategies and risk management in an increasingly interconnected global financial system. Keywords: Market Integration, Volatility Spillover, Portfolio Diversification, Stock Market Returns, Emerging Markets, Cross-market Correlation

Aggregate Output Stability: Divergent Perspectives

The main objective of this article was to describe two asymmetric perspectives of the aggregate imbalance approach. Starting from the contrast of the Rational Expectations and Keynesian approaches, we analyze the characterization that the general reserve makes of the causes of inflation and the implications that it has on economic policy decisions. From the rational expectations approach, companies and workers form a kind of coherent group that jointly experiences fluctuations in the prices of their products and faces in unison the problem of signal extraction. On the other hand, the Keynesian approach to effective demand explains price fluctuations in principle as an expression of insufficient demand that generates involuntary unemployment. It was identified that the increase in margins during 2021 sought to pass on to consumers and end users of the goods and services of oligopolistic structures the increase in marginal costs induced by the fall in effective demand; resulting in an effect of price increases on the supply side or cost inflation.

Research on Changes in International Energy Trade Pattern under the Russia-Ukraine Conflict

The impact of the conflict between Russia and Ukraine on world energy markets has received great attention. Some researchers have found that the Russia-Ukraine conflict has caused an energy crisis to a certain extent. However, there is a lack of overview of the changes in the trade pattern and the scope of its impact. Therefore, through a comprehensive analysis of changes in policies and economic data, this study analyzes the different response measures taken by countries in different regions such as Europe and Asia to deal with the reduction in Russia's exports of major energy products and the fluctuations in international energy prices. This study also analyzes how the mutual sanctions between Russia and Western countries have contributed to the shift of Russia's energy export focus to the Asia-Pacific region and the diversification of Western countries' energy supply. Research results show that energy trade is at risk of being affected by geopolitical factors such as regional conflicts and mutual sanctions. The Russia-Ukraine conflict has strengthened the attention of countries on energy security issues. The research also highlights the implications for future policies and actions, providing an understanding of emerging trends in the future. Economically, this study, based on past data, emphasizes the inevitability of the Russia-Ukraine conflict affecting energy fluctuations and affirms that the Russia-Ukraine conflict is conducive to global new energy transformation and sustainable development in the long term.

Research on the Dynamic Relationship Between Asset Price Fluctuation and Foreign Exchange Market

Research on the Dynamic Relationship Between Asset Price Fluctuation and Foreign Exchange Market

Modeling the Predictors of Poverty in Agricultural Households in Uganda: Application of Multilevel and Interaction Methods

This study aimed to model the predictors of poverty in agricultural households in Uganda. The study's specific objectives were to examine the effect of individual predictors of poverty and analyze the contribution of community predictors of poverty in agricultural households. The study utilized data from the Uganda National Household Survey (UNHS, 2019/20) obtained from the Uganda Bureau of Statistics. A sample of 13,732 households was randomly selected from the total weighted sample representation of 11.3 million households involved in agricultural activities. A logit model was used in the analysis and estimates were provided using multilevel and interaction methods. Key findings suggest that poverty in agricultural households was positively and significantly influenced by the gender of the household head, marital status of the household head, income stability of the household, age of the household head and livestock ownership. Additionally, regional differences accounted for 17.9 % of the variations in poverty levels in Uganda and understanding such regional differences and their influence on poverty levels can assist policymakers and organizations in designing targeted interventions and policies to reduce poverty levels among households. Such measures can address the specific challenges faced by different regions and promote more equitable development across the country. However, poverty in agricultural households was negatively and significantly influenced by residence status, savings account ownership and household size. Based on the study's findings, the key policy recommendations were that; the government should continue implementing gender-focused interventions to address gender disparities among women empowerment programs that involve access to resources including land, equal access to employment opportunities and equal access to education to reduce poverty among women. Regarding income instabilities in agricultural households due to price fluctuations, the government should empower farmers to form farmer groups where they can collectively increase their bargaining power to avoid price fluctuations.

The Effect of Food Price Stabilization on Inflation in West Nusa Tenggara 2019-2023

One of the primary contributors to the inflation rate in West Nusa Tenggara Province is the fluctuation of prices for food commodities. The objective of this study is to examine the extent to which fluctuations in food commodity prices, including those of rice, red chili, and shallots, contribute to inflationary trends in West Nusa Tenggara. The data used is monthly data on inflation and food commodity prices from 2019-2023 obtained from BPS (Central Bureau of Statistics), DKP (Food Security Agency), and the Agriculture Office of West Nusa Tenggara Province. The analysis method used is vector autoregression (VAR), which includes stationarity test, VAR stability test, optimal lag test, cointegration test, VAR estimation, impulse response function (IRF), and variance decomposition. The results of this study indicate that in the short term premium rice prices, curly red chili prices, and shallots do not affect inflation. Conversely, in the long run, the variable price of shallots does not affect inflation, while the variable price of premium rice and curly red chili prices exert an influence on inflationary pressures in West Nusa Tenggara Province. The Variance Decomposition Test indicates that the price of curly red chili contributes 37.24 percent to inflation in the fifth period, while premium rice has an effect of 8.66 percent on inflation in the second period and shallots have an effect of 7.93 percent on inflation in the fifth period.

How volatility in the oil market and uncertainty shocks affect Saudi economy: a frequency approach

In this study, spectral Granger causality analysis is employed to investigate the spectral dynamics of uncertainty transmission and its impact on economic growth and financial development in Saudi Arabia from 1993 to 2020. We examine the relationships between crude oil volatility, geopolitical risk, global economic uncertainty, financial development (measured by market capitalisation, MCGDP, Financial Institutions Access Index, FIAIX) and economic growth. The empirical results show that negative shocks in crude oil volatility have a significant impact on financial development as measured by the MCGDP, with capital flight and reduced domestic investment playing key roles, despite the effective contribution of increased government spending to mitigate these effects. In this study, spectral Granger causality analysis is employed to investigate the spectral dynamics of uncertainty transmission and its impact on economic growth and financial development in Saudi Arabia from 1993 to 2020. We examine the relationships between crude oil volatility, geopolitical risk, global economic uncertainty, financial development (measured by market capitalisation, MCGDP, Financial Institutions Access Index, FIAIX) and economic growth. The empirical results show that negative shocks in crude oil volatility have a significant impact on financial development as measured by MCGDP, with capital flight and lower domestic investment playing a key role, despite the effective contribution of increased government spending in mitigating these effects. However, looking at the FIAIX, crude oil volatility has a different impact, with positive shocks having no significant impact on financial development. In contrast, negative shocks show long-term causal effects, which emphasises the vulnerability of the banking sector to oil price fluctuations. Geopolitical risk has a significant long-term impact on the MCGDP due to uncertainty shocks caused by regional and global geopolitical measures. For geopolitical risk, the results are mixed with a significant causality of negative shocks on the FIAIX over certain frequencies, emphasising the sensitivity of the banking sector to geopolitical tensions. In contrast, the world economic uncertainty has only a limited direct impact on the FIAIX, indicating the resilience of the Saudi financial sector to fluctuations in global uncertainty. In terms of economic growth, positive shocks have a greater impact than negative shocks due to the volatility of crude oil. However, shocks resulting from geopolitical risks, whether positive or negative, have little effect on economic growth. The industrial production index, a measure of the resilience of the Saudi economy, indicates that it is susceptible to positive shocks from fluctuations in oil prices over a range of time periods. Our study’s findings can assist Saudi Arabia’s authorities in fortifying the country’s financial and economic resilience against the spread of uncertainty. For strong financial development and sustainable economic growth, these uncertainty elements must be well monitored.

Overcoming Challenges in Scented Geranium Cultivation, Processing, and Marketing: Study from Northern Karnataka, India

Medicinal and aromatic crops play a pivotal role in the socio-cultural, economic, spiritual and health dimensions of India's rural population and have become an integral part of our culture and rituals. Karnataka is a major repository of aromatic and medicinal treasures of the country. The demand for aromatic plants in India surpasses the available supply, prompting the widespread commercial cultivation of major aromatic crops in various regions. Among these, scented geranium emerges as a vital perennial aromatic, cultivated for its leaves imbued with a captivating rose fragrance. The aromatic oil of scented geranium is increasingly replacing traditional rose oil and identified as one of the top 20 essential oils traded globally. The present study aims to identify challenges in cultivation, processing and marketing aspects of scented geranium in Northern Karnataka. Considering the area and concentration of scented geranium in the state, Belagavi district is purposively selected for the study. Primary data was collected through personnel interview of randomly selected geranium growers. The major challenges faced by the farmers in the production, processing and marketing aspects of scented geranium were analysed and prioritized through Garett ranking technique. Analysis of the data revealed that in production, high cost of planting material, lack of high yielding varieties and high wage rates, high cost of inputs and sensitivity of crop to heavy rains were identified as top five constraints. Whereas, in processing, significant hurdles were high working capital requirement, high capital investment in installation distillation unit and insufficient knowledge on operation of distillation units, low oil recovery and lack of efficient processing equipment. In marketing aspects, high price fluctuation, lack of marketing information and lack of competition in the market, non-existence of local market and lack of adequate demand in nearby area were identified as major challenges in the study area. Educating farmers in nursery management and implementing mechanization techniques, particularly for harvesting, are crucial for enhancing productivity and profitability. Additionally, training on proper storage and transportation practices is essential to maintain the quality of volatile essential oils. This comprehensive strategy promotes sustainable and economically viable cultivation of scented geraniums in the region.

Demographic changes, technology growth, and retirement policy reform: Implications for U.S. housing dynamics

As the population aging process continues, concerns about how this situation impacts the housing market and social security rise. To address this question, this paper presents a developed and calibrated general equilibrium life-cycle model incorporating two production sectors to analyze the impacts of demographic structure changes and retirement policy reforms on housing price fluctuations and household choices. The model calibrated to the U.S. macroeconomic data between 1968 and 2018 suggests that in an economy with unlimited land supply, the housing supply curve exhibits perfect elasticity, rendering demographic changes insignificant in housing price fluctuations, while technological advancements lead to decreased prices. A 1% growth in productivity in both sectors results in a 2.6% decrease in house prices. Furthermore, a 1% decrease in population and a 5-year early retirement led to significant reductions of 25% and 30% in individual social security payments and 9% and 18% in interest rates, respectively. This suggests that during a recession caused by demographic structural changes, households become more conservative and prioritize precautionary saving strategies, increasing savings and investing more in housing assets. Consistent with empirical findings, during an economic boom, a decline in the capital-output ratio and the real housing price suggests a decrease in savings and housing asset investment. The rise in consumption drives the capital demand of the non-housing sector to increase, stimulating business expansion and labor inflow.

A Study on Issues and Challenges Faced by the Street Vendors in Mysore City

Street trading is the oldest mode of trading form of retail business in the country, though it was considered illegal in independent India for six decades. In the year 2014, the parliament agreed to the Street Vendors Act (to protect livelihood to regulate street vending), this act legally enables providing a prosperous atmosphere. In the present day, many street vendors primarily work to raise income to provide basic needs like food for their family members and to pay the school fees of their children. This would become the source of income for unemployed persons, especially middle-aged women who have limited education. In this context, through objective model methodology studies, this study selected 110 street vendors of Mysuru city to know their socioeconomic status along with the challenges and problems faced by them. 38.18 % of vendors were illiterate, 58.18% belonged to backward classes, and 28% of vendors had 251 to 350 rupees of daily income. 48.18% of traders face low-income problems and 40.9% of traders face a low range of competition in the market. Likely 40% of people facing medium-level challenges related to the environment, and 36.36% were confronting intermediate-level social security challenges. Around 46.37% were encountering a medium level of issues from the local committees. The study shows that 42.73% of traders were confronted with low levels of market fluctuations in prices. Hence, it is significant that this study helps to solve the problems of street vendors.

CroCoDai : A Stablecoin for Cross-Chain Commerce

Decentralized Finance (DeFi), in which digital assets are exchanged without trusted intermediaries, has grown rapidly in value in recent years. Stablecoins , which are pegged to a non-volatile asset such as the US dollar, are a prominent feature of DeFi as they mitigate the risk associated with price fluctuations. However, existing stablecoin systems are tied to individual blockchain platforms, and trusted parties or complex protocols are needed to exchange stablecoin tokens between blockchains. Our goal is to design a practical stablecoin system for cross-chain commerce, and to do so we must overcome two main challenges. The first is to support a large and growing number of blockchains efficiently. The second is for the stablecoin to be resilient to blockchain platform failures and to price fluctuations that affect its collateral. We present CroCoDai to address these challenges. We demonstrate CroCoDai 's efficiency by comparing the performance of a prototype implementation to related baselines, and its resilience through an empirical analysis of historical token price data.

Cost and Return Analysis of Tomato Cultivation in Three Different Districts of Bangladesh

This paper attempts to analyze the costs, return and production problems of tomato in three districts namely Gazipur, Rangpur and Cumilla in Bangladesh. It is necessary to enunciate that through purposive sampling technique, the data were collected from 225 tomato cultivators of Cumilla and Rangpur districts. Human labour, fertiliser, bamboo sticks, thread, seeds and seedlings, ploughing, irrigation, insecticides and pesticides, hormone, etc. are all necessary for the production of tomatoes. Transport expenses must be taken into account as well. Together, the aforementioned elements were taken into account to estimate the cost of tomato production. Every data set was subjected to statistical and economic analysis, with validated outcomes via a series of tables. Numerous issues affect farmers, and this study sheds insight on this situation. The findings showed that the total cost was highest in Gazipur (Tk.333,800/ha) than that of Rangpur ( Tk. 304,600/ha) and Cumilla ( Tk.282,670/ha). Gross returns from tomato in Cumilla and Rangpur were Tk. 234,942/acre and Tk. 212,213/acre respectively. The net returns were found higher in Gazipur (Tk. 206,200/ha) than that of Rangpur (Tk. 135,400/ha) and Cumilla (Tk. 97,330/ha). Based on overall costs, the Gazipur, Rangpur and Cumilla districts' benefit cost ratios for tomato production per hectare were determined to be 1.60,1.40 and 1.30, respectively. The most notable limitations in were the high cost of inputs, the absence of storage facilities, price fluctuations, and damage from insects and diseases.

The Spillover Effects of Public Attention and Real Estate Market: A Case Study from Shanghai, China

The real estate industry is closely linked to the national economy, and fluctuations in house prices have long been a major focus of public attention. This study explores the relationship between public attention and the real estate market, using public attention as a focal point. It systematically explains how public attention affects investment decisions in real estate. Taking Shanghai as a case, this study empirically examines the dynamic time-varying relationship between public attention and house prices, sales, investment and floor space completed by building a Time-Varying Parameter Vector Autoregression (TVP-VAR) model with data from 2011 to 2024.The research shows that the spillover index of house prices on public attention is positive and house prices acting as the sender of the shock, with rising house prices boost public attention. Conversely, the spillover index of public attention on house prices is negative, with public attention acting as the receiver of the shock. Based on the empirical results, it is recommended to incorporate public attention into the real estate market monitoring system, observe the real estate industry using multiple indicators, and enhance the regulation of online media to ensure policy transparency.

Dynamic analysis and application of network structure control in risk conduction in the industrial chain

According to control theory, a dynamical system is controllable if, with a suitable choice of inputs, it can be driven from any initial state to any desired final state within a finite time. Most dynamic characteristics of real networks are nonlinear, so achieving target control is more practical and necessary. The network’s control energy is also a problem that must be considered. Whether and how to control the complex system of the industrial chain has high theoretical and practical significance. In this study, we use the GARCH model, DCC model, and network structure control theory comprehensively to study the price fluctuation risk of the mining stock market from the perspective of the industry chain and network control dynamics and obtain interesting results. (1) Risk conduction among stocks has a prominent industry-driving effect, and the risk conduction ability of upper and middle stocks is stronger. (2) The risk regulation cost, time cost, and node number cost of the whole-industry chain are all higher than those of the two-tier chain, which indicates that the correlation complexity of the network has a positive relationship with risk control. (3) Key risk nodes play an essential role in risk control, so monitoring key stocks from the industrial chain perspective is necessary to control risks in time. This work can provide valuable suggestions for market regulators and policy-makers in terms of risk management and control.

Strategy of Development of Sustainable Red Chili Agribusiness Areas in North Sumatra Province

The development of sustainable red chili agribusiness areas in North Sumatra Province is a challenge that involves various aspects, including cultivation technology, farmer institutions, supply chain efficiency, government policy support, and environmental sustainability. This study aims to identify and formulate a sustainable red chili agribusiness development strategy that can increase farmers' productivity and welfare without sacrificing the environment. Through a qualitative approach, data were collected from in-depth interviews with farmers, agribusiness stakeholders, as well as a review of government policies related to sustainable agriculture. The results show that the application of precision agriculture technology, such as drip irrigation systems and integrated pest management, can significantly increase productivity while preserving natural resources. Strengthening farmer institutions, such as cooperatives, is also very important in coordinating production, improving market access, and stabilizing farmers' income. In addition, supply chain efficiency through the construction of storage and distribution centers will reduce post-harvest losses and price fluctuations, while government policy support is needed in the provision of agricultural infrastructure and stable price regulation. In conclusion, the sustainable development model of red chili agribusiness areas must include synergies between environmentally friendly technologies, strong institutions, efficient supply chains, and proactive policy support. With this model, red chili agribusiness areas in North Sumatra can develop sustainably, contribute to food security, and improve farmers' welfare.

Optimal planning and sizing of microgrid cluster for performance enhancement

Access to electricity is a key indicator of a country’s development. In developing nations like Ethiopia, this metric is particularly crucial for assessing progress. Currently, about 45.8% of Ethiopia’s population lacks access to electricity, with rural areas experiencing even higher rates, reaching 57.2%. The Southern Nations, Nationalities, and People’s (SNNP) region faces the greatest challenge, with 62.1% of its population lacking electricity. Ethiopia aims to achieve universal electricity access by 2030, and microgrid (MG) development is expected to play a pivotal role in meeting this goal. This study employs a multi-tier framework (MTF) to categorize village households based on electricity access, considering factors like income level and willingness to pay, to support the MG development process. Three villages—Toba, Koza, and Womba—in the SNNP region were selected for optimal MG sizing. Sensitivity variables such as global horizontal irradiance (GHI) variation, photovoltaic (PV) and battery prices, battery usage limits, and capacity shortage levels were analyzed for their impact on net present cost (NPC), initial capital cost, and cost of energy (COE) using HOMER Pro software. For example, in the Toba MG, increasing the capacity shortage from 0 to 10% reduced the COE from 0.1195 $/kWh to 0.09104 $/kWh, a 23.82% decrease. Additionally, fluctuations in PV and battery prices had a direct impact on the system’s NPC. The study also explored the impact of clustering the microgrids by interconnecting the three individual systems and conducting a techno-economic analysis. The comparison between standalone MG operation and clustered microgrids revealed that, despite the added cost of interconnection, the benefits in terms of technological, economic, and reliable operation of the clustered system were comparable to standalone microgrids. Finally, a feasibility study was conducted for the potential grid extension of the Toba MG, which is located 130 km from the nearest substation in Sawla.