Abrupt Price Research Articles

Smart Contracts as a Tool to Support the Challenges of Buying and Selling Coffee Futures Contracts in Colombia

In Colombia, coffee futures contracts represent essential financial agreements that allow producers and buyers to establish prices, quality, and conditions for future transactions in the coffee market. Despite the evident benefits of stability and predictability, this practice faces significant sustainability challenges that threaten its long-term viability. One of the reasons is the significant lack of transparency in the supply chain. Farmers, affected by abrupt price fluctuations and adverse weather conditions such as the El Niño phenomenon, experience an increase in market prices, leading to the non-delivery of the final product, and contract breaches as they find better prices in the local market. In this context, smart contracts emerge as a promising technological solution to address these problems. These contracts enable the verification of each step in the process, from harvest to final sale, within a blockchain. Therefore, this research designs a smart contract managed through a platform called SmartBeanFutures, which records the clauses of futures contracts using the IERC721 framework, allowing the generation of a unique and non-repeatable asset. It aims to sell, promote, and manage coffee sale prices during the agreement’s signing, creating a transparent environment for chain actors. This proposal undergoes evaluation in a test environment, providing farmers access to the designed platform. Following the validation of the proposal, it was identified that over 74% would use this type of contract in their agricultural processes, highlighting that implementing this technology contributes to eliminating intermediaries in the chain and gives farmers more control over their participation in the market.

Retail gasoline pricing in a subsidized energy market: An empirical analysis from AIDS model for Iran

The prevailing gasoline pricing policy in Iran has traditionally been the fixed-price policy, where both rationed and non-rationed prices are set below the free-market prices. This long-standing subsidy policy has led to excessive energy consumption, fuel smuggling, and environmental concerns. However, efforts to reform these subsidies have faced social unrest due to abrupt price increases. To address these issues, we propose a new gasoline pricing policy that incorporates socio-economic factors using the AIDS model. We have categorized gasoline consumption into four groups: less than 60 L (current ration), 60 L–80 L, 80 L–120 L, and more than 120 L per month. Results shows that the price elasticity for the 60 L–80 L group is the highest (−0.94), while it is lowest for the above 120 L group (−0.48). Therefore, we recommend avoiding price increases for groups consuming below 80 L per month to prevent social unrest. Also, we suggest implementing a tax rate of 5% for consumption above the current ration. Under the proposed policy, the non-rationed price of gasoline will vary between the ration price and the Persian Gulf FOB price, depending on consumption levels. This approach ensures that higher levels of gasoline consumption will be associated with fewer subsidies and welfare benefits, and vice versa.

EXTRAPOLATION USAGE FOR PREDICTING CRYPTOCURRENCY PRICING

In this article, we delve into the challenging problem of forecasting cryptocurrency prices using mathematical extrapolation techniques. We highlight the scarcity of research in this domain, underlining the necessity for in-depth investigation. The article outlines the unresolved issues related to extrapolation-based cryptocurrency price prediction, such as market volatility and non-linearity. It primarily aims to showcase the potential of extrapolation for predicting bitcoin prices. The analysis involves a year-long bitcoin price trend, with the application of linear and polynomial extrapolation methods. While some correlation exists, notable discrepancies, especially during abrupt price changes, are evident. The conclusion emphasizes the limitations of extrapolation and advises a diversified approach to cryptocurrency investment decisions, considering various factors beyond mathematical data. In this article, we delve into the challenging problem of forecasting cryptocurrency prices using mathematical extrapolation techniques. We highlight the scarcity of research in this domain, underlining the necessity for in-depth investigation. The article outlines the unresolved issues related to extrapolation-based cryptocurrency price prediction, such as market volatility and non-linearity. It primarily aims to showcase the potential of extrapolation for predicting bitcoin prices. The analysis involves a year-long bitcoin price trend, with the application of linear and polynomial extrapolation methods. While some correlation exists, notable discrepancies, especially during abrupt price changes, are evident. The conclusion emphasizes the limitations of extrapolation and advises a diversified approach to cryptocurrency investment decisions, considering various factors beyond mathematical data.

A New Explanation for the Frog-in-the-Pan Phenomenon Based on the Cognitive-Evolutionary Model of Surprise.

The frog-in-the-pan (FIP) phenomenon suggests that investors are more sensitive to abrupt price changes than gradual price changes in the stock market. Based on the cognitive-evolutionary model of surprise and the reinforcement learning model, this paper provides a new explanation for the FIP phenomenon in that this phenomenon could be explained by the elicitation of surprise emotion. We predict that when a change substantially and abruptly occurs, the significant prediction error triggers participants' surprise, which makes participants more sensitive to the change. To ascertain these hypotheses, we recruited 109 participants and compared participants' learning rates and surprise responses under different contexts. We observed that participants' learning rate soared when the prediction error was large enough to trigger surprise emotion under abruptly changed conditions and confirmed that the FIP phenomenon could be explained by the elicitation of surprise emotion. In a word, this research demonstrates the significant role of surprise emotion in the decision-making process.

Case study of event risk management with options strangles and straddles

AbstractEvent risk environments may involve an elevated probability of both volatility regime shifts and sharp, abrupt price changes, either up or down. Purely direction‐oriented risk management approaches are not necessarily well‐suited for these market conditions. In this exploratory case study, we look at the possibility that non‐directional options strategies, such as straddles and strangles, may offer interesting benefits in the management of potential event risk environments. Our research involves only the case of the S&P500® Index from 2018 through 2020. We utilize the Market Sentiment Meter from CME Group to identify periods in which event risk may be present and particularly when the probability of sharp, abrupt price changes may be elevated. Our findings in this specific case suggest that selling option straddles and strangles during typical market conditions and then buying option straddles and strangles when the market sentiment switches to a more extreme state offers potential as an effective risk management approach for event risk. More research is needed over longer periods and for different securities, including international equity indices, to explore the usefulness of options strategies for event risk management.

Characterizing financial crises using high-frequency data

Recent advances in high-frequency financial econometrics enable us to characterize which components of the data generating processes change in crisis, and which do not. This paper introduces a new statistic which captures large discontinuities in the composition of a given price series. Monte Carlo simulations suggest that this statistic is useful in characterizing the tail behavior across different sample periods. An application to US Treasury market provides evidence consistent with identifying periods of stress via flight-to-cash behavior which results in increased abrupt price falls at the short end of the term structure and decreased negative price jumps at the long end.

Loss aversion and market crashes

This study proposes a rational expectation equilibrium model of stock market crashes with information asymmetry and loss averse speculators. We obtain a state-dependent linear optimal trading strategy, which makes the equilibrium price tractable. The model predicts nonlinear market depth and the result that small shocks to fundamentals (e.g., supply or informational shocks) can cause abrupt price movements. We demonstrate that short-sale constraints intensify asset price collapses relative to upward movements. The model also generates contagion between uncorrelated assets. These results are consistent with the main puzzling features observed during market crashes, namely abrupt and asymmetric price movements that are not driven by major news events but coupled with a spillover effect between unrelated markets.

The microscopic relationships between triangular arbitrage and cross-currency correlations in a simple agent based model of foreign exchange markets.

Foreign exchange rates movements exhibit significant cross-correlations even on very short time-scales. The effect of these statistical relationships become evident during extreme market events, such as flash crashes. Although a deep understanding of cross-currency correlations would be clearly beneficial for conceiving more stable and safer foreign exchange markets, the microscopic origins of these interdependencies have not been extensively investigated. This paper introduces an agent-based model which describes the emergence of cross-currency correlations from the interactions between market makers and an arbitrager. The model qualitatively replicates the time-scale vs. cross-correlation diagrams observed in real trading data, suggesting that triangular arbitrage plays a primary role in the entanglement of the dynamics of different foreign exchange rates. Furthermore, the model shows how the features of the cross-correlation function between two foreign exchange rates, such as its sign and value, emerge from the interplay between triangular arbitrage and trend-following strategies. In particular, the interaction of these trading strategies favors certain combinations of price trend signs across markets, thus altering the probability of observing two foreign exchange rates drifting in the same or opposite direction. Ultimately, this entangles the dynamics of foreign exchange rate pairs, leading to cross-correlation functions that resemble those observed in real trading data.

Mineral resources in the age of climate adaptation and resilience

AbstractThis article discusses issues on resources availability to achieve climate adaptation and resilience for cities and infrastructures. In the age of climate change, there could be cascading failures through a range of infrastructure breakdowns. Direct and indirect damage costs could exceed what had been estimated in traditional risk assessments. This could be exacerbated through abrupt price peaks in international supply chains of minerals, and through events happening in remote parts of the world that affect extraction and vulnerable industries. The core argument made here is one of feedbacks: climate adaptation has significant resource implications, and how resources are being used will have implications on climate strategies. Industrial Ecology has a role to play assessing those interactions and providing a better grasp of the spatial dimension of material flows, partly to track those flows and align them to specific actors, and partly to address interlinkages across different flows and their stocks (‘the resource nexus’). Methodological novelties are needed to better understand the resource base and the socio‐economic dimension, especially on innovations and transitions that can help to cope with the challenges ahead. Altogether this would enable research to establish an evidence base on sustainable materials to deliver parts of the UN Sustainable Development Goals (SDGs) and to reassess infrastructure assets and the mineral resources in the age of climate adaptation and resilience.

Nonlinear dependence in cryptocurrency markets

We are interested in describing the returns and volatility dynamics of major cryptocurrencies. Very high volatility, large abrupt price swings, and apparent long memory in volatility are documented features of such assets. We estimate a multivariate stochastic volatility model with discontinuous jumps to mean returns and volatility. This formulation allows us to extract a time-varying shared average volatility and to account for possible large outliers. Nine cryptocurrencies with roughly three years of daily price observations are considered in the sample. Our results point to two high volatility periods in 2017 and early 2018. Qualitatively, the permanent volatility component seems driven by major market developments, as well as the level of popular interest in cryptocurrencies. Transitory mean jumps become larger and more frequent starting from early 2017, further suggesting shifts in cryptocurrencies return dynamics. Calibrated simulation exercises suggest the long memory dependence features of cryptocurrencies are well reproduced by stationary models with jump components.

Loss Aversion and Market Crashes

This study proposes a rational expectation equilibrium model of crashes in an economy with information asymmetry and loss averse speculators. We obtain a state-dependent linear optimal trading strategy, which makes the equilibrium price tractable for the first time in such an economy. The model predicts nonlinear market depth and the fact that small shocks to fundamentals (e.g., supply or informational shocks) can cause abrupt price movements. We demonstrate that short-sale constraints intensify asset price collapses relative to upward movements. The model also generates contagion between uncorrelated assets. These results reflect the main puzzling features observed during market crashes, namely abrupt and asymmetric price movements, not driven by major news events, coupled with a spillover effect between unrelated markets.

Comparative production performance of vegetable crops in the country vis-à-vis Eastern India

The present study was conducted to analyze thecomparative production performance of vegetable crops in eastern India and India. In this study compound growth rates of vegetable crops and major vegetables like potato, tomato, onion, brinjal, cabbage, cauliflower, okra and pea were calculated by fitting exponential function to variables like area, production and productivity and tabular analysis was done to arrive at meaningful results. The study was based on macro framed data collected through different published secondary sources like Horticultural statistics of India and Agricultural statistics at a Glance, Ministry of Agriculture and Farmers Welfare, Government of India. The results pointed out positive growth trends in area, production and productivity of vegetable crops in the region and country during the last 16 years. Considering remarkable growth trends, vegetable crops may be taken as pathway for income enhancement of farming communities. Being good sources of healthy dietary requirements, nutritional security of the region in particular and nation in general can be addressed. Some limiting factors like pre and post harvest losses, storage facilities, lack of refrigerated vans and transportation and farmer’s friendly marketing facilities restrict arrival of the actual quantity of vegetable to theconsumers and in fetching remunerative prices of the produce. Hence, there is a need to improve pre and postharvest technologies, provide suitable transport and marketing facilities. Appropriate policy to tackle the abrupt price fluctuations during good harvest and scarce period is also needed to protect both the producers and the consumers. Shifting Indian farming from rural setup to urban setup and linking cultivators to super markets particularly for vegetables grower will be a key drivers in improving financial conditions of the farming community of country.

Bank loan loss accounting treatments, credit cycles and crash risk

Banks that follow conditional conservatism in their loan loss accounting treatments benefit from a reduction in crash risk. The key discretionary loan loss accounting channels are provisions and allowances. We show that conditional conservatism reduces crash risk of small banks during periods of credit contraction and boom. Interestingly, for large banks, crash risk is not reduced by more conservative accounting even for those with higher levels of opacity. Hence regulation prompting for more conservative bank loan loss accounting does not present a significant opportunity to limit systemic effects arising from abrupt price declines in the stocks of large banks.

How (i)rrational are we? A case of Croatian inflation

This paper examines the validity of the rational expectations hypothesis (REH) in the case of Croatian consumers and their inflation estimates. The added value of this paper in comparison to previous similar studies lies in the state space methodology, allowing the authors to test for potential time variability of the estimated relationship between actual and expected inflation. The obtained results can be summarized as follows: i) consumers heavily over-estimated actual inflation throughout the entire period 2005-2014, leading to the rejection of the REH; ii) consumer bias against inflation intensifies in times of abrupt price hikes (2007 and 2008), and diminishes in times of lower inflation volatility (2014). This empirical rejection of the REH is in line with previous research on the topic, providing additional evidence that the theoretical paradigm of homo economicus is heavily flawed.

Cost-Optimal Charging of Plug-In Hybrid Electric Vehicles Under Time-Varying Electricity Price Signals

This paper develops a convex quadratic programming (QP) framework for the charge pattern optimization of plug-in hybrid electric vehicles (PHEVs) under time-varying electricity price signals. The work is motivated by the need for a computationally efficient PHEV charging model in the bidirectional vehicle-to-grid (V2G) integration studies, accounting for the hybrid powertrain dynamics and battery energy losses of the PHEVs. We adopt a previously developed PHEV power management system and construct a simplified model for the convex optimization problem. We use an equivalent circuit battery model to compute battery energy losses during grid charging and discharging. We then derive the total fuel and electricity cost of the PHEV as a quadratic function of battery state of charge and use a standard QP solver to minimize it for a few sample trips obtained from the National Household Travel Survey data set. Using a quad-core computer, the daily PHEV charging trajectory with 5-min time resolution can be optimized in less than tenth of a second. Through several examples, we show the application of the proposed method in various V2G-related problems, such as obtaining the aggregate load patterns of PHEVs, analyzing the potential impacts of large-scale bidirectional V2G integration, benchmarking the fuel economy of PHEVs, and determining the sensitivity of V2G load to abrupt price variations.

Demand in the Wake of an Emerging Middle Class and Low-End Entry

The emerging middle class has become a force of great economic importance in consumer markets around the globe. This paper examines the impact of a substantial rise in Brazil's living standards on the development of the country's large soft-drink market, during a period which saw unprecedented growth in the share of generic soda brands. Relying on a unique combination of richly varying market and consumer-level data, we estimate a novel structural demand model that identifies a mechanism by which a household develops either a 'premium brand habit' or a 'frugal habit'. We find strong empirical evidence of such persistence in preferences, and demonstrate that controlling for such consumption habits is instrumental for identifying the heterogeneous price sensitivities of different socioeconomic groups. Our model casts light on the nature of competition between premium brands and the expanding competitive fringe in an emerging market. In particular, our demand model provides support for Coca Cola Co's abrupt price cut in July 1999, whereas models that do not incorporate our persistence structure provide weaker support for this strategic move.

Mixed signals: market incentives, recycling, and the price spike of 1995

Abstract Environmental economics assumes that reliance on price signals, adjusted for externalities, normally leads to efficient solutions to environmental problems. We explore a limiting case, when market volatility created ‘mixed signals’: prices of waste paper and other recycled materials were suddenly extremely high in 1994–1995, then plummeted back to traditional low levels in 1996. These rapid reversals resulted in substantial economic and political costs. A review of academic and business literature suggests six possible explanations for abrupt price spikes. An econometric analysis of the prices of wood pulp and waste paper shows that factor which explained price changes in 1983–1993 contribute very little to understanding the subsequent price spike. From the econometric analysis and from other sources, we conclude that speculation must have played a major role in the price spike, perhaps in combination with modest effects from changes in government policy and in export demand. If speculatively driven price spikes can disrupt an environmentally important industry such as recycling, what is the appropriate role for public policy? When price volatility is sufficiently disruptive, then measures to control or stabilize prices, rather than interfering with the market, might help to make it more efficient.

New technology introduction in a marginal coffee area of Colombia

Income stagnation in the downward cycle of primary product prices is a problem for small farmers in developing countries. The recent abrupt price decline in coffee poses a large adjustment problem in marginal production areas. One method of farm income stabilization for marginal export crop production areas is diversification into food crops with improved technology. The potential for a cushioning of this farm income decline via the introduction of improved food crop technology was examined. A substantial moderating effect was obtained even without uprooting the improved coffee technology. Moreover, an analysis of the constraints to the earlier introduction of the Caturra coffee variety helped identify some of the components of farmer decision making relevant to adoption of new technology.

Comment on "Optimal Oil Producer Behavior Considering Macrofeedbacks"

Harry Saunders's paper on the above subject in this issue of the Journal raises a very interesting point. As is well known, oil-exporting countries now hold major assets in the Western economies. Furthermore, the sensitivity of these economies to abrupt changes in oil prices seems widely accepted. It then seems reasonable to expect oil exporters' pricing decisions to be influenced by concerns about the rate of return on their assets. In particular, Saunders argues that oil exporters would want to avoid abrupt price changes because the ensuing shock effects would tend to reduce the rate of return on capital.

Strategies for Opes's pricing dicisions

Using a model of the world energy mark at that incorporates price expectation and lagged adjustment of demand and supply, we examine the implications of various price-paths that could be selected by OPEC. After demons trating the sensitiyity of the results to change in vunetional spectifications and certain parameter values, we discuss a variety of rule-of-thurob pricing stragegics under which OPEC sets prices in response to available market singals. A strategy that is relatively caustious about further major price increases servces OPEC relatively well in comparison with other strategies, but there exists a real possibility of major, abrupt price increases within the next ten years.