Price Oscillations Research Articles

Evaluation of the behavior of prices and market arrivals of tomatoes – A case study of West Bengal, India

The oscillations in prices and arrivals of agricultural goods are primarily influenced by the seasonal character of the agricultural production system. Here, we investigate the trends and seasonal price dynamics concerning market arrivals of tomatoes in West Bengal, India. Monthly data on arrivals and prices of tomatoes were collected between 2013-14 and 2019-20. Both the ordinary least square and the twelve-month moving average techniques were employed to identify the long-term trends and seasonal variations in price and arrival patterns. The market arrivals exhibit negative trends in three markets, except for Barasat and Bardhaman, where the observed values are not statistically significant. However, the lone market in Diamond Harbour shows a positive and significant trend in arrivals. Regarding current prices, all markets, except for Chakdah and Siliguri, exhibit positive and significant trend. Seasonality is more prominent in market arrivals than the price for all the markets. Results suggest the variability in arrivals is proportional to the number of arrivals in the market, in turn, larger arrivals lead to higher variability. Price variations are substantial and exhibit relative stability both within and across markets, unlike arrivals which show more fluctuation. Price fluctuations are significant not only within a given year but also between different years. Additionally, an inverse relationship between current prices and market arrivals suggest as arrivals increase, prices tend to decrease and vice versa. The study provides new insights into the trends in market arrivals and seasonal price dynamics of tomatoes in West Bengal, eastern India.

Analysis of the Impact of the “Insurance & Futures” Model on the Price Fluctuation of China's Pig Market

The market price cyclical fluctuation and oscillation "pig cycle" is a typical economic phenomenon in the pig market. In this paper, we use the coefficient of variation method and ARIMA (Auto-Regressive, Integrated, Moving Average) time-series method to analyse the weekly data of local breed pigs, domestic hybrid pigs, exotic hybrid pigs and hog price indexes from 2019 to 2023, and empirically analyse the impact of the "insurance + futures" model on the price of hogs to empirically analyse the degree of influence of the "insurance+futures" model on the volatility of hog prices. It is found that the price change trends of local breed pigs, domestic hybrid pigs, and exotic hybrid pigs are similar, and the "insurance + futures" model has a significant impact on the price fluctuation of exotic hybrid pigs, a weak impact on the price fluctuation of local breed pigs, and a non-significant impact on the price fluctuation of domestic hybrid pigs. During the pilot practice of the "insurance + futures" model, the price volatility of the three types of pigs increased significantly, and the overall pig price showed a downward trend.

СОВРЕМЕННЫЙ ПОТРЕБИТЕЛЬ: В ТЕНЕТАХ ЦИФРОВОЙ ЭКОНОМИКИ

Digital economy has created both new possibilities and new risks for consumers. Researchers have noted that there arise obfuscation effects, instruments that digital ecosystems use to manipulate the optimal choice of individuals under high search transactional costs. Intertemporal price dispersions and dynamic pricing are based on the situations where clients express inattentive aspects as a result of their informational overloading in the periods of numerous price changes. Periodic up and down price oscillations hamper price understandings for consumers and serve as a beneficial focus in supporting collusive discipline within digital platforms. Newly formed price strategies on the basis of obfuscation phenomenon are out of the current competition policy and are not duly regulated.

Announcement of accounting performance variables predictory power on share prices of listed deposit money banks in Nigeria

The study assessed the announcement of accounting performance variable predictory power on share prices of listed Deposit Money Banks in Nigeria. The study adopted an ex-post facto research design to assess the relationship between return on equity, return on assets, price-earnings ratio, and earnings per share-on-share prices of deposit money banks in Nigeria. A sample of 12 Deposit Money Banks quoted on the Nigerian Exchange Group was selected between the years 2012 to 2021. Panel data methodology was adopted because it combines time series and cross-sectional data. The methods of data analysis were descriptive statistics, correlation, and regression techniques, and other econometric statistical analyses were adopted. The results obtained disclosed that the shares market price of DMBs and accounting performance indicators (ROE, ROA, EPS PER) are related in the long run. Additionally, Granger causality tests showed that share prices are even more predicted by the explanatory variables. Further analysis revealed that all the explanatory variables have a strong and positive correlation with the share prices of DMBs. The regression result of the study showed that return on equity and return on asset hurt the share prices of DMBs while price-to-earnings ratios and earnings per share had a positive impact on share prices. Based on the findings, the study concluded that the accounting performance indices of DMBs of Nigeria are important predictors of share price oscillations in the capital market.

Ergodic aspects of trading with threshold strategies

AbstractTo profit from price oscillations, investors frequently use threshold-type strategies where changes in the portfolio position are triggered by some indicators reaching prescribed levels. In this paper we investigate threshold-type strategies in the context of ergodic control. We make the first steps towards their optimization by proving ergodic properties of related functionals. Assuming Markovian price increments satisfying a minorization condition and (one-sided) boundedness we show, in particular, that for given thresholds, the distribution of the gains converges in the long run. We also extend recent results on the stability of overshoots of random walks from the i.i.d. increment case to Markovian increments, under suitable conditions.

Asset flow model for a homogeneous group of investors: High-frequency trading limit

Deterministic and stochastic asset flow models have been designed to study the effects of behavioral components on market dynamics. These models have been successful in explaining the mechanisms behind price overshoots, oscillations, reversals, liquidity- and value-induced market bubbles and oscillations, and flash crashes. While these models are originally nonlinear, we demonstrate here that, in the case of a market consisting of a homogeneous group of investors with identical trading sentiments, natural modifications of the response functions yield a version that can be represented by a linear dynamical system across the entire state space of the system. We show that this linear version exhibits all types of price behavior, just like the nonlinear version, while also having the benefit of being explicitly integrable even with time-varying parameters. We present a limiting case of the model that corresponds to fast trading, which is appropriate for modern electronic markets, and provide examples illustrating the differences in the response of the price to variability in the intrinsic value of shares or liquidity.

Impact of climate smart agriculture on food security: An agent-based analysis

The study proposes an agent-based model to investigate how adoption of climate smart agriculture (CSA) affects food security. The analysis investigates the role of social and ecological pressures (i.e. community network, climate change and environmental externalities) on the adoption of physical water and soil practices as well as crop rotation techniques in rural Ethiopia. The findings reveal that CSA can be an effective strategy to improve the rural populations' well-being for farm households with access to capital, strong social networks and access to integrated food markets. The climate scenario simulations indicate that farmers adopting CSA fare better than non-adopters, although CSA adoption does not fully counterbalance the severe climate pressures. In addition, farmers with poor connections to food markets benefit less from CSA due to stronger price oscillations. These results call for an active role for policy makers in encouraging adaptation through CSA adoption by increasing access to capital, improving food market integration and building information sharing among farmers.

Modern global oil market under stress: system dynamics and scenarios

Modelling techniques developed 40 years ago to gain insight into the issues of energy supply security remain powerful even as the focus of energy technology policy analysis has shifted to consider new problems and to use research methods more closely linked to pressing environmental challenges. Dynamic modelling continues to be of merit and indeed it has the potential to provide helpful perspectives on contemporary problems such as climate change and the transition to net-zero greenhouse gas emissions. This study seeks to help revive system dynamics (SD) modelling of the global oil market. The SD-based analysis used in this paper facilitates a rational representation of physical stocks and flows as well as causal linkages that drive decision making in the global oil system. The use of SD provides insights (intuitive and counter-intuitive) into the macro-level non-linear dynamics of global oil exchanges and permits assessment of the potential impacts of future changes in system behaviour. The model exhibits damped oscillations in oil prices, broadly consistent with real market behaviours. The results further illustrate the resilience of market dynamics in the phase of extreme supply-side shocks and reveal the ability of SD to simulate and model such effects even beyond the point of market failure.

A nuclear‑hydrogen hybrid energy system with large-scale storage: A study in optimal dispatch and economic performance in a real-world market

A study in optimal dispatch and economic analysis of a novel nuclear hybrid energy system (NHES) with large-scale hydrogen storage and a novel control scheme is conducted. The control scheme makes charge and discharge decisions by using the real-time electricity price relative to the historical price distribution. The pricing data is taken from the ERCOT Houston and West load zones with different price oscillations. Six case control studies with different levels of aggressiveness were chosen for each load zone for a total of 12 case studies. It is found that in a high price volatility load zone, a more aggressive control strategy maximizes revenue, while in a less oscillatory load zone, a moderate control strategy performs better. The NHES can store energy when the price is low and sell additional electricity when the price is high, as well as participate in the ancillary services market. Due to these advantages, the NHES can generate 10–40 million USD more revenue annually than a stand-alone nuclear plant. Due to higher costs, the NHES has a higher LCOE (81.36 USD/MWh) than a stand-alone plant (68.66 USD/MWh); however, the LCOE of the NHES is still comparable to other new forms of electricity generation. It is found that both the NHES and the stand-alone plant are not economical in the existing electricity market. Due to the extra revenue generated, the hybrid system has a positive annual cashflow whereas the stand-alone plant does not. It is found that the hybrid plant needs less cost subsidy than a stand-alone plant to become economical.

Apportioning limited supplies to competing retailers under panic buying and associated consumer traveling costs

Motivated by rising product insecurity during the initial waves of the COVID-19 pandemic, and the resultant need for consumers to travel further to buy scarce products, we address the possibility of shortages as a result of panic buying. In particular, we study the effect of competition on inventory and pricing by considering the case in which a manufacturer apportions a scarce product to two competing retailers. We find that competition does not always effectively respond to panic buying and can cause frequent price oscillations when the market is shared equally between the two retail firms. On the other hand, in contrast to the case of monopolistic retailing, competition enables the manufacturer to regulate the cost that consumers incur even if the wholesale price is fixed. Specifically, when the market location is biased towards one of the two firms, the manufacturer can apportion supplies to the firms in such a way as to increase the average cost (which includes the retail price and the consumers’ traveling costs), thereby mitigating panic buying and reducing the risk of shortage. Alternatively, when the panic is not severe, the manufacturer can apportion in a way that decreases the average cost, thereby meeting a social welfare-oriented goal in the framework of distributing a scarce product.

Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics.

Bao et al. (2017) show that in laboratory subjects have problems with both trading an experimental asset and forecasting its price. In this paper I explore these experimental results, by investigating a model in which financial traders individually learn how to use forecasting and/or trading anchor and adjustment heuristics, by updating them with Genetic Algorithms. The model replicates main outcomes of the Bao et al. (2017) experiment, and shows that both forecasters and traders coordinate on asset price oscillations, albeit the trading markets generate larger cycles. Both forecasters and traders learn to chase market trends, and this behavior is reinforced when agents have to perform both tasks. As a result, the famous positive feedback between financial expectations and price trends becomes enhanced and markets generate prices that oscillate between 10% and 350% of the fundamental value.

CRUDE OIL PRICE, STOCK PRICE AND SOME SELECTED MACROECONOMIC INDICATORS: AN IMPLICATION ON THE GROWTH OF NIGERIAN ECONOMY

Since the first oil price oscillation in 1973s, macroeconomists have viewed sharp measures in the price of oil are generally as an important source of economic vacillations. The go-slow of economic activities has important implications for economic agents and markets. Therefore, this paper models and forecasts the crude oil price, stock price and selected macroeconomic variables in Nigeria. A model predicated on the Keynesian model using yearly data between 1986 and 2016 and analysed using VECM and GARCH approaches. The findings showed that there is long run relationship through Vector Error Correction Model which was achieved well in forecasting the selected macroeconomic variables while the volatility in crude oil price and stock price causes by external and internal forces also captured by General Autoregressive Conditional Heteroskadasticity. The long run negative effect of macroeconomic variable on economy growth can be controlled by making strong fiscal and monetary policies. The 2016 recession was reinforced by all share index and exchange rate as the path of growth declined over the forecast horizon. Further checks carried out using normality test validated the choice of this work. The paper concludes that monetary and exchange rate policy consistency are decisive for smoothening business rotation vacillations and promoting market stability.
 
 JEL: L10; E30 
 
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Deep Q-Learning and Preference Based Multi-Agent System for Sustainable Agricultural Market.

Yearly population growth will lead to a significant increase in agricultural production in the coming years. Twenty-first century agricultural producers will be facing the challenge of achieving food security and efficiency. This must be achieved while ensuring sustainable agricultural systems and overcoming the problems posed by climate change, depletion of water resources, and the potential for increased erosion and loss of productivity due to extreme weather conditions. Those environmental consequences will directly affect the price setting process. In view of the price oscillations and the lack of transparent information for buyers, a multi-agent system (MAS) is presented in this article. It supports the making of decisions in the purchase of sustainable agricultural products. The proposed MAS consists of a system that supports decision-making when choosing a supplier on the basis of certain preference-based parameters aimed at measuring the sustainability of a supplier and a deep Q-learning agent for agricultural future market price forecast. Therefore, different agri-environmental indicators (AEIs) have been considered, as well as the use of edge computing technologies to reduce costs of data transfer to the cloud. The presented MAS combines price setting optimizations and user preferences in regards to accessing, filtering, and integrating information. The agents filter and fuse information relevant to a user according to supplier attributes and a dynamic environment. The results presented in this paper allow a user to choose the supplier that best suits their preferences as well as to gain insight on agricultural future markets price oscillations through a deep Q-learning agent.

Speculative asset price dynamics and wealth taxes

Based on the seminal asset-pricing model by Brock and Hommes (J Econ Dyn Control 22:1235–1274, 1998), we analytically show that higher wealth taxes increase the risky asset’s fundamental value, enlarge its local stability domain, may prevent the birth of nonfundamental steady states and, if they exist, reduce the risky asset’s mispricing. We furthermore find that higher wealth taxes may hinder the emergence of endogenous asset price oscillations and, if they exist, dampen their amplitudes. Since oscillatory price dynamics may be associated with lower mispricing than locally stable nonfundamental steady states, policymakers may not always want to suppress them by imposing (too low) wealth taxes. Overall, however, our study suggests that wealth taxes tend to stabilize the dynamics of financial markets.

Analysing price volatility in agricultural value chains using systems thinking: A case study of the Indonesian chilli value chain

CONTEXTHigh price volatility in agricultural commodities can be a major issue for value chain actors exposed to its adverse economic impacts. Price volatility results from the interaction of multiple factors linked within dynamic and complex agricultural systems. Therefore, to address price volatility, the approach needs to be capable of analysing feedback that occurs in such complex systems. OBJECTIVEWe integrate a systems thinking approach and value chain analysis to overcome the constraint of other methods to explicitly describe and understand how system structure influences system behaviour observed in price volatility and the assessment of the consequences of ex-ante and ex-post policy interventions based on this understanding. METHODSThe proposed integrated approach involves the active participation of value chain actors and stakeholders to improve their understanding of the complex systems they operate within including the policy environment. The approach takes the Indonesian chilli value chain as a case study. We implemented the first two steps of systems thinking (i.e., articulating problems and formulating dynamic hypotheses). In the group model building processes, we developed causal loop diagrams to represent a dynamic hypothesis that explains the feedback loops that cause price oscillation behaviour and systems archetypes that identify potential intervention points. RESULTS and CONCLUSIONSThe integrated approach was able to link the Indonesian chilli value chain's system structure and the system behaviour observed in price volatility. The causal loop diagram clearly displays the feedback between production, market governance, consumption, and price. The diagram also portrays how these factors impact value chain actors' performance and the influence of time delays and random shocks on the entire value chain system. Limits to growth and shifting the burden archetypes were identified as critical leverage points in formulating fundamental policy interventions to address price volatility. SIGNIFICANCEThis study demonstrates the strengths of the proposed approach in developing a comprehensive dynamic qualitative model of a whole value chain system that influences the system behaviour, such as oscillation, which other modelling studies do not consider. The use of system archetypes to identify intervention points is another research contribution in that it improves value chain analysis. The results also highlight the benefits of participatory system dynamics modelling in enhancing the learning of value chain actors in anticipating the consequences of any actions or random shocks on the entire systems.

Dynamics of the price behavior in stock markets: A statistical physics approach

We study the time evolution of stock markets using a statistical physics approach. We consider an ensemble of agents who sell or buy a good according to several factors acting on them: the majority of the neighbors, the market atmosphere, the variation of the price and some specific measure applied at a given time. Each agent is represented by a spin having a number of discrete states q or continuous states, describing the tendency of the agent for buying or selling. The market atmosphere is represented by a parameter T which plays the role of the temperature in physics: low T corresponds to a calm market, high T to a turbulent one. We show that there is a critical value of T, say Tc, where strong fluctuations between individual states lead to a disordered situation in which there is no majority: the numbers of sellers and buyers are equal, namely the market clearing. The specific measure, by the government or by an economic organization, is parameterized by H applied on the market at the time t1 and removed at the time t2. We have used Monte Carlo simulations to study the time evolution of the price as functions of those parameters. In particular we show that the price strongly fluctuates near Tc and there exists a critical value Hc above which the boosting effect remains after H is removed. Our model replicates the stylized facts in finance (time-independent price variation), volatility clustering (time-dependent dynamics) and persistent effect of a temporary shock. The second part of the paper deals with the price variation using a time-dependent mean-field theory. By supposing that the sellers and the buyers belong to two distinct communities with their characteristics different in both intra-group and inter-group interactions, we find the price oscillation with time. Results are shown and discussed.

The invisible hand of Laplace: The role of market structure in price convergence and oscillation

The “invisible hand” of the free market is remarkably effective at producing near-equilibrium prices. This is difficult to quantify, however, in the absence of an agreed model for out-of-equilibrium trade. Short of a fully reductionist model, a useful substitute would be a scaling law relating equilibration time and other market parameters. Even this, however, is missing in the literature.We make progress in this direction. We examine a class of Arrow–Debreu markets with price signaling driven by continuous-time proportional-tâtonnement. We show that the connectivity among the participants in the market determines quite accurately a scaling law for convergence time of the market to equilibrium, and thus determines the effectiveness of the price signaling. To our knowledge this is the first characterization of price stability in terms of market connectivity. At a technical level, we show how convergence in our class of markets is determined by a market-dependent Laplacian matrix.If a market is not isolated but, rather, subject to external noise, equilibrium theory has predictive value only to the extent to which that noise is counterbalanced by the price equilibration process. Our model quantifies this predictive value by providing a scaling law that relates the connectivity of the market with the variance of its prices.

Impact of climate smart agriculture on food security: an agent-based analysis

The study proposes an agent-based model to investigate how adoption of climate smart agriculture (CSA) affects food security. The analysis investigates the role of social and ecological pressures (i.e. community network, climate change and environmental externalities) on the adoption of physical water and soil practices as well as crop rotation technique. The findings reveal that CSA may be an effective strategy to improve the rural populations' well-being for farm households with access to capital, strong social networks and access to integrated food markets. The climate scenario simulations indicate that farmers adopting CSA fare better than non-adopters, although CSA adoption does not fully counterbalance the severe climate pressures. In addition, farmers with poor connections to food markets benefit less from CSA due to stronger price oscillations. These results call for an active role for policy makers in encouraging adaptation through CSA adoption by increasing access to capital, improving food market integration and building social networks.

ОСОБЛИВОСТІ ЗАСТОСУВАННЯ ФОНДОВОГО ІНДЕКСУ У ОПЕРАЦІЯХ З ЦІННИМИ ПАПЕРАМИ ТА ФІНАНСОВИМИ ІНСТРУМЕНТАМИ

Stock market in the economic relation of state is a complex of invest-financial relations, which are transformed in cash contributions of participants until branches and spheres of the objects economical activities, to which relate companies, organizations, institutions of all ownership forms, and also territorial districts, where localized sectors of public economy, municipal fields, capital construction institutions etc. But first of all stock market display system relationship between participants, what relating operations with securities and financial instruments in the form of trades on basis trends in certain areas of activity and economical processes in the state. Character sign of functioning stock market is direct participation in agreements with securities under time realization market trades – with aim involve incomes. And here to substantiate constant application indicator of stock index, that is measurement of fluctuation value securities on stock market, and has a significant impact on economy the state. In this article, the methodical basis for the evaluation of stock indexes, which are more commonly used on the stock exchange, are disclosed in domestic and foreign practice. And this algorithm for calculating stock indices is based on the criteria for selecting information about entrepreneurial activity and the economic state of the country, as well as those factors that impact – both on the country’s economy and on the stock market in particular. Of course, stock indices are subject to changes that are primarily related to corporate events experienced by companies whose securities are included in the index. Changes may also apply to the list of securities used to calculate the index. Because these stock indices that exist and are most often used within the stock exchange, form the value of securities and financial instruments, and also affect the rates of national currencies. The features of the methodology for evaluating stock indexes are the calculation of price oscillations due to the occurrence of random phenomena, which allow determine the degree of yield of securities and financial instruments for a certain period of time, taking into account changes in their values.

Основание динамики рыночного взаимодействия в пространственно-временном описании на современных турбулентных биржах с позиций теорий ценности и полезности (часть 2)

Цель: в продолжение [9, 10] в статье осуществляется дальнейшее обоснование биржевых волн и их суперпозиции в процессах рыночного взаимодействия с учетом турбулентности в долговременном периоде на основе аналогии закономерности образования природных волн в различных средах. Обсуждение: мировую биржевую торговлю будут постоянно «лихорадить» финансовые и другие потрясения и неустойчивости [3]. В предыдущих материалах [9, 10] было доказано, что основная причина развивающихся биржевых кризисов – это естественное увеличение скоростей биржевого обмена типа «купли – продажи» акций или других аналогичных производных инструментов. Скорость обменных биржевых операций и процесс турбулентности привели к тому, что брокеры-трейдеры одновременно оказались в роли биржевых покупателей и биржевых продавцов. Возникли непредсказуемые ценовые изменения в виде дополнительных ценовых «скачков», вплоть до минусовых значений, которые привели к неуправляемым нарушениям устойчиво проявляемых ранее биржевых тенденций горизонтальных трендов. В результате происходят потери существенной части прибыли, что так часто приводит к неминуемому разорению трейдеров или брокеров. Поэтому продолжение моделирования биржевых процессов в условиях турбулентности в длительный период базировалась и на доказательстве происхождения и развития природно-возникающих волновых процессов. Обоснование природных процессов возникновения таких явлений и на биржах даст возможность моделировать и прогнозировать биржевые процессы при изменениях биржевой среды. Результаты: моделируются волновые процессы в условиях турбулентности при биржевых взаимодействиях в разных временных интервалах с учетом принципов экономической динамики применением математической интерпретации классических теорий полезности и ценности товара. Доказывается природное единство происхождения и развития волновых процессов в различных средах, в т.ч. и волновые процессы, возникающие в биржевом пространстве в условиях турбулентности за счет воздействия колебательных движений во временном экономическом периоде, определяемом в результате влияния детерминант спроса или/и предложения на материализованную субстанцию, заполняемую акциями или другими производными инструментами. Это позволяет понять природу процессов, происходящих в рыночной среде при проявляемых в них ценовых турбулентностях, и получить новое научное обоснование их в пространственно-временном описании при изменении современных условий.