Determining fluctuations and cycles of corn price in Iran

Behzad, Fakari; Farsi, Mohammad; Kojouri, M

doi:10.17221/141/2012-agricecon

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…This condition is allegedly due to the slow flow of information (asymmetric information) from the market in Jakarta to the Kupang city and the market in Kupang district, as well as infrastructure and commodity cycle constraints in the form of selling time and business patterns. According to Fakari, et al, (2013) in the study of fluctuations and cycles of prices of agricultural commodities (corn) in Iran, finding that each commodity often has its own price movement cycle.…”

Section: Resultsmentioning

confidence: 99%

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2018

RJOAS

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Various positive and negative impacts (social, economic, and environmental) arise from the establishment of a company in a region. It results in the government issuing laws and regulations to ensure a company's responsibility to the public, especially the community around the company's operating area through real activities. The real activities undertaken by the company are called Corporate Social Responsibility. The implementation of Corporate Social Responsibility can be viewed from the legal and economic aspects. Through the legal aspect, Corporate Social Responsibility is an obligation that must be implemented by the company in accordance with the laws and regulations applicable to the the company's operation. Based on the economic aspect, the impact of the Corporate Social Responsibility implementation is a company's reciprocity regarding the community where company operates and the sustainability of the company. This research explores Corporate Social Responsibility for TBK's agricultural sector companies in Indonesia (2012.

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Section: Resultsmentioning

confidence: 99%

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2018

RJOAS

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“…Fakari et al (2013) constructed a GARCH model and found that the corn price fluctuation cycle was 21 months. They also discovered that short-term volatility in corn prices could lead to greater fluctuations in future futures prices, and that futures contracts are an effective tool for controlling corn price volatility [ 3 ]. Zhou et al (2015) used quarterly price data from 2004 to 2014 to build an ARMA model for forecasting the prices of Chinese cabbage, cucumbers, and tomatoes.…”

Section: Background and Relevant Literaturementioning

confidence: 99%

Short-term forecasting of vegetable prices based on LSTM model—Evidence from Beijing’s vegetable data

Zhang,

Yang,

Zhao

et al. 2024

PLoS ONE

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The vegetable sector is a vital pillar of society and an indispensable part of the national economic structure. As a significant segment of the agricultural market, accurately forecasting vegetable prices holds significant importance. Vegetable market pricing is subject to a myriad of complex influences, resulting in nonlinear patterns that conventional time series methodologies often struggle to decode. In this paper, we exploit the average daily price data of six distinct types of vegetables sourced from seven key wholesale markets in Beijing, spanning from 2009 to 2023. Upon training an LSTM model, we discovered that it exhibited exceptional performance on the test dataset. Demonstrating robust predictive performance across various vegetable categories, the LSTM model shows commendable generalization abilities. Moreover, LSTM model has a higher accuracy compared to several machine learning methods, including CNN-based time series forecasting approaches. With R2 score of 0.958 and MAE of 0.143, our LSTM model registers an enhancement of over 5% in forecast accuracy relative to conventional machine learning counterparts. Therefore, by predicting vegetable prices for the upcoming week, we envision this LSTM model application in real-world settings to aid growers, consumers, and policymakers in facilitating informed decision-making. The insights derived from this forecasting research could augment market transparency and optimize supply chain management. Furthermore, it contributes to the market stability and the balance of supply and demand, offering a valuable reference for the sustainable development of the vegetable industry.

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“…The average unconditional volatility of international price in grain markets almost rose 80 percent, this price volatility usually transmitted to grain markets in developing countries (Ceballos et al, 2015). Price volatility has a drastic impact on some actors such as producers, consumers, investors, and government (Fakari et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Volatility Transmission of Barley World Price to the Domestic Market of Iran and the Role of Iran Mercantile Exchange; An Application of Bekk Model

et al. 2019

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Barley is one of the main crops after wheat and rice. The importance of this product increases because it is an essential input in the livestock and poultry industries. The prices of input, which used in the livestock and poultry industries, faced fluctuations in recent years. Thus, in this study, the price fluctuation of barley in the Iran Mercantile Exchange, Iran domestic free market and World Market compared by applying the GARCH model. This model applied to monthly prices of barley from March 2009 to February 2017. Also, the volatility and shock transmission of barley price between these three markets analyzed by the BEKK model. The results showed that the price fluctuations of the domestic market are more than the global market. In addition, the shocks and volatilities of the world and Iran free market transmitted to the Iran Mercantile Exchange. Thus, the use of new financial instruments in the domestic free market is necessary.

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Determining fluctuations and cycles of corn price in Iran

Cited by 7 publications

References 13 publications

Untitled

Untitled

Short-term forecasting of vegetable prices based on LSTM model—Evidence from Beijing’s vegetable data

Volatility Transmission of Barley World Price to the Domestic Market of Iran and the Role of Iran Mercantile Exchange; An Application of Bekk Model

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