Soybean Prices Research Articles

Study of Policy Innovation Strategy to Accelerate Achievement of Indonesian Soybean Self-sufficiency in 2035

The high consumption and demand for soybeans without an increase in production has forced the Indonesian government always to import soybeans. Import policy must be given special attention to suppress price increases and make the rate of MSMEs continue to grow well. It's important to formulate policy designs to accelerate the fulfilment of domestic soybean supply in Indonesia. Method research uses a qualitative method with a literature review from many literature and data sources, which is then used to make a policy-making model based on incremental theory. The results indicate that self-sufficiency in soybeans may be realized if long-term arrangements are made for several things, namely expanding the area, subsidising soybean prices, import regulations and setting fair soybean import tariffs, developing the soybean jabalsim subsystem with innovation, controlling the rate of population, and the improvisation with technology innovation. Steps to recommend policies by setting import tariffs using an open and closed system following domestic production conditions, forming small analysis teams that observe, assist and work directly on the sub-section of the soybean issue, synergy and harmony of legal products within the central government-related to excise tariffs imports according to WTO standards and rigid subsidised pricing below import prices. BULOG must regulate the trade system with digital public service innovations based on the E-Agriculture Government. In addition, the government needs to partner with the private sector to increase domestic production, provide social health insurance protection and crop insurance to soybean farmers and assist with implementing smart farming agriculture.

Effects of dietary local hemp seed meal as soybean meal alternative on productive performance, egg quality and yolk fatty acid composition of laying hens

ABSTRACT Supply problems and rising soybean meal prices have an impact on increasing feed costs. Hemp seed meal (HSM) with high protein content has the potential to be used as an alternative to soybean meal. This study evaluated the impact of dietary HSM of Narlı Sarayı variety as a substitute for soybean meal on productive performances, egg quality and yolk fatty acid composition. A total of 120 Lohmann Brown laying hens aged 50 weeks were allocated into 4 groups and 10 repetitions. Birds received treatment without HSM (control group), or soybean meal substituted with 4%, 8% and 12% HSM. Dietary 4% significantly increased (p < 0.05) egg production and decreased FCR compared with 8% and 12% HSM group but did not differ from the control group in an overall period of 6 weeks. The inclusion of the 12% HSM group significantly decreased (p < 0.05) egg production. Meanwhile, there was no influence of hemp seed meal (p > 0.05) on feed intake, egg weight, body weight change, egg shape index, albumen index, albumen weight, Haugh unit, yolk weight, yolk index and eggshell thickness. Dietary 8% and 12% HSM significantly increased (p < 0.05) eggshell weight and yolk colour compared with control and 4% HSM groups. There was a significant increase (p < 0.05) in omega-3 fatty acid concentration and a decrease in yolk omega-6 to omega-3 fatty acids ratio with an increase in dietary HSM. It was concluded that dietary up to 12% HSM of the Narlı Sarayı variety decreased egg production and increased FCR. Increasing dietary levels of HSM increased eggshell weight, yolk colour and omega-3 fatty acids content and decreased the omega-6 to omega-3 fatty acids ratio.

Analyzing the Performance of Diversified Commodity Derivatives Portfolios in Brazil

This paper seeks to investigate how we invest in commodity derivatives by comparing the performance of portfolios constructed using the mean-variance model, hierarchical risk parity, and the naive strategy with the stock market and the risk-free rate. For this purpose, daily closing future prices of ethanol, corn, cattle, gold, coffee, and soybeans traded in Brazil from 2015 to 2023 are considered, in addition to the rate of interbank deposit certificates (CDI or DI) and the performance of the theoretical portfolio. of shares in the Ibovespa index. The constructed portfolios are analyzed using the Sharpe Ratio, CVaR, Beta, and Maximum Drawdown metrics and the comparison of their returns. The results indicate that the portfolio constructed using the mean-variance model presented the lowest risk ratios and generated the highest return, followed by the hierarchical risk parity, the naive strategy, and the Ibovespa index. These findings are useful for scientific literature that investigates finance by bringing empirical evidence of Brazilian commodities to portfolio managers, investors, and other agents in the supply chain.

Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis

Accurately forecasting crude oil prices is crucial due to its vital role in the industrial economy. In this study, we explored the multifaceted impact of various financial, economic, and political factors on the forecasting of crude oil forward prices and volatility. We used various machine learning models to forecast oil forward prices and volatility based on their superior predictive power. Furthermore, we employed the SHAP framework to analyze individual features to identify their contributions in terms of the prediction. According to our findings, factors contributing to oil forward prices and volatility can be summarized into four key focal outcomes. First, it was confirmed that soybean forward pricing overwhelmingly contributes to oil forward pricing predictions. Second, the SSEC is the second-largest contributor to oil forward pricing predictions, surpassing the contributions of the S&amp;P 500 or oil volatility. Third, the contribution of oil forward prices is the highest in predicting oil volatility. Lastly, the contribution of the DXY significantly influences both oil forward price and volatility predictions, with a particularly notable impact on oil volatility predictions. In summary, through the SHAP framework, we identified that soybean forward prices, the SSEC, oil volatility, and the DXY are the primary contributors to oil forward price predictions, while oil forward prices, the S&amp;P 500, and the DXY are the main contributors to oil volatility predictions. These research findings provide valuable insights into the most-influential factors for predicting oil forward prices and oil volatility, laying the foundation for informed investment decisions and robust risk-management strategies.

PRODUCTION ARRANGEMENTS FOR TEMPORARY AND PERMANENT CROPS IN THE MUNICIPALITIES OF SANTARÉM AND MOJUÍ DOS CAMPOS - PARÁ

In the northern region of Brazil, the municipalities of Santarém and Mojuí dos Campos have been experimenting with the transformation of a productive system formerly based on traditional family agriculture to large scale mechanized agriculture. A new agricultural frontier has established itself in the region, driven by favorable conditions of climate, topography, and low land cost, and since then has attracted an increasing number of grain farmers from various regions of the country. Thus, the objective of this article is to analyze the dynamics of the permanent and temporary crop production chains in the municipalities of Santarém and Mojuí dos Campos, in the western region of the state of Pará, as well as identify the main factors that interfere in this productive chain. For this purpose, quantitative data were collected from the IBGE System of Automatic Recovery (Sidra) and the information was collected in the database of Municipal Agricultural Production (PAM). We concluded with the present research that grain productivity in Santarém and Mojuí dos Campos shows itself to be growing in recent years due to the high prices of soybeans and corn in the international market.

Volatility and dependence in crude oil and agricultural commodity markets

ABSTRACT This paper studies the evolution, volatility dynamics, and nonlinear dynamics between crude oil prices and major agricultural commodity prices. Semiparametric GARCH-in-Mean copula models are applied to monthly crude oil, corn, soybean, palm oil, rice, sugar, and wheat prices from January 1990 to May 2023. We find that the Clayton copula is the best copula to describe the (bivariate) dependence structures between the crude oil and soybean, crude oil and palm oil, crude oil and sugar, and crude oil and wheat markets, suggesting the statistically significant lower tail dependence between crude oil and major agricultural commodity returns. Moreover, the tail dependence is strongest between crude oil and palm oil.

Strategies for improving food security under the impact of external grain price fluctuations: evidence from China

ABSTRACT The purpose of this study is to explore strategies for improving food security under the impact of external food price fluctuations. Using impulse response function, complex network analysis, and other methods, we studied the linkage between CBOT prices of soybeans, rice, wheat, corn, and Chinese futures prices from 2009 to 2022. This article analyzes the prominent price linkage relationships, network evolution characteristics, and development trends. The results show that CBOT soybean and China soybean futures prices, CBOT wheat and China soybean futures prices, and CBOT corn and China wheat futures prices are three prominent price linkage relationships. The three pairs of price linkage relationships are constantly changing over time and show a gradual weakening trend. The price of domestic soybean futures and CBOT soybean futures have a strong association. The sudden food crisis will strengthen the connection between international and Chinese grain futures prices. The above results demonstrate the importance of strengthening the independence of China’s futures markets. Based on the above analysis results, the paper put forward policy suggestions such as improving soybean yield levels, utilizing the futures market for risk management, and taking measures to respond to possible changes in Chinese wheat prices based on international corn futures prices.

Analysis of Soybean Production Trends in Indonesia

Climate change since 2012 has had a real influence on the uncertainty of soybean production which has resulted in fluctuating soybean production in Indonesia. The study purposed to: (i) analyze the fluctuation of soybean production before and during climate change, (ii) analyzing the factors that affect soybean production fluctuations covering land area (X1), soybean prices (X2), consumption (X3). The type of data used is secondary data, a time series data of soybean production in 1994 to 2019. The data was obtained from the Central Statistics Agency. The analytical method used is trend analysis to analyze production fluctuations. Multiple linear regression analysis to analyze the factors that influence production fluctuations. The results showed that before climate change production trends decrease, during climate change production trends increase slightly. Factors that influence soybean production are land area (positive influence on fluctuations in soybean production by α 5 % means an increase in land area results in an increase in production), price has positive effect on soybean production fluctuations with α 5 % means an increase in price motivates farmers to produce, and consumption has positive effect on soybean production fluctuations with α 5 % means an increase in consumption motivates farmers to produce.

Ham Petrol ve Seçilmiş Gıda Ürünleri Arasındaki İlişkinin Tahmini

Purpose: Increasing food prices as a result of food crisis in 2007-2008 increased interest in this relationship in the literature. The objective of this research is to establish a causal link between crude oil and food prices by examining the prices of various food commodities, including wheat, sunflower, soybean, cotton, and corn. Design/Methodology/Approach: To explore the relationship between crude oil and food prices, a range of methodologies were employed, including the Augmented Dickey-Fuller test, Granger causality test, Johansen Cointegration analysis, vector autoregression model, vector error correction model, action and reaction analysis, and variance decomposition. Findings: The findings highlight both short- and long-term connections between the variables, as well as the influence of food prices on crude oil during the second sub-period. Originality/Value: Studies investigating the relationship between food prices and crude oil were mostly conducted through “energy”. The difference of this study is the fact that it draws attention to the impact of crude oil on food prices next to the effect of food product prices accepted as internal variable in the literature on crude oil.

Determinants of Asymmetric Costs In Soya Production

Purpose: The study aimed to analyze the determinants of the asymmetric behavior of fixed costs in soybean production. Theoretical background: Although previous research indicates the presence of asymmetric costs (sticky costs theory) in the agricultural sector and, specifically, in soybean production, there is still a gap in testing which determinants explain this asymmetric condition. Methodology: The study used a quantitative methodology, with the estimation of a multiple linear regression model and parametric correlation tests, using data on costs, production capacity, production quantity and soybean prices for the period from 2009 to 2022. Results and conclusion: The results showed that the capacity and price factors were statistically significant in explaining the asymmetry of fixed costs. Price was also significant in explaining total and variable costs, which were also shown to be asymmetrical by the models used. Research implications: The study advances in verifying the determining factors of asymmetry and not just in pointing out the behavior of costs in this sector, as previous literature has done. Originality/value: The approach of the work and its results contribute to expanding empirical research related to the assumptions of the sticky costs theory in a relevant economic activity.

Agricultural price forecasting based on the spatial and temporal influences factors under spillover effects

PurposeIntegrating artificial intelligence and quantitative investment has given birth to various agricultural futures price prediction models suitable for nonlinear and non-stationary data. However, traditional models have limitations in testing the spatial transmission relationship in time series, and the actual prediction effect is restricted by the inability to obtain the prices of other variable factors in the future.Design/methodology/approachTo explore the impact of spatiotemporal factors on agricultural prices and achieve the best prediction effect, the authors innovatively propose a price prediction method for China's soybean and palm oil futures prices. First, an improved Granger Causality Test was adopted to explore the spatial transmission relationship in the data; second, the Seasonal and Trend decomposition using Loess model (STL) was employed to decompose the price; then, the Apriori algorithm was applied to test the time spillover effect between data, and CRITIC was used to extract essential features; finally, the N-Beats model was selected as the prediction model for futures prices.FindingsUsing the Apriori and STL algorithms, the authors found a spillover effect in agricultural prices, and past trends and seasonal data will impact future prices. Using the improved Granger causality test method to analyze the unidirectional causality relationship between the prices, the authors obtained a spatial effect among the agricultural product prices. By comparison, the N-Beats model based on the spatiotemporal factors shows excellent prediction effects on different prices.Originality/valueThis paper addressed the problem that traditional models can only predict the current prices of different agricultural products on the same date, and traditional spatial models cannot test the characteristics of time series. This result is beneficial to the sustainable development of agriculture and provides necessary numerical and technical support to ensure national agricultural security.

Trends and Seasonality in arrivals and prices of Soybean in APMC, Parbhani

The research was based on the arrival and prices of soybean in APMC, Parbhani, which have the maximum number of arrivals in the selected APMC. The arrival and price data for soybean were collected monthly from the official records by APMC, Parbhani. Based on availability data, the latest 21 years of data from 2000 to 2020 were collected. For analyzing the trend in arrivals and prices of agricultural commodities the compound growth rates of chosen agricultural commodities arrivals and prices were calculated, we calculated seasonal indices using the simple average approach. It is believed that, with the increase in arrivals of agricultural commodity in the market, their prices come down and vice versa. In this study, annual compound growth rate of arrivals in case of soybean (-0.69) were found negative and annual compound growth rates of prices in the case of soybean (3.355) were positive growth rate. Arrivals were noticed highest during the month of November (216.15). The lowest indices of arrivals were noticed in the month of July (37.71). In case of price indices was noticed highest in the month of January (119.42), While lowest in June (88.58). The monthly arrivals and prices of soybean in Parbhani market shows great fluctuations and no any specific trend was observed. The government should look over all the APMC and fix a single price for the sale so that the arrivals will not accumulate in one APMC.

Spatiotemporal Evolution and Influencing Factors of Soybean Production in Heilongjiang Province, China

Heilongjiang Province, as the largest production and supply base for high-quality soybeans in China, plays a vital role in optimizing the layout of soybean production and promoting the revitalization of the soybean industry. Soybean yield is used as a key indicator of soybean production. This study integrated soybean yield data from agricultural reclamation systems and local authorities. A variety of statistical analysis methods, such as barycenter analysis, the Mann–Kendall test, the space–time cube, and grey relational analysis, were used to research the spatiotemporal evolution and influencing factors of soybean production in Heilongjiang Province from 2011 to 2021. This paper revealed the spatiotemporal evolution mechanism and explored the reasons for the differences in the effects of influencing factors. The results were as follows. (1) During the period between 2011 and 2021, the center of gravity of county-level soybean yield in Heilongjiang Province moved towards the northwest over a distance of 16.82 km. The soybean yield in the province experienced a mutation in approximately 2018, from a downward trend to an upward trend. (2) The spatiotemporal hot spots of county-level soybean yield in Heilongjiang Province were concentrated along the line from Hailun to Aihui. The types of hot spots included consecutive hot spots, intensifying hot spots, sporadic hot spots, and new hot spots. (3) The spatiotemporal agglomeration patterns of county-level soybean yield in Heilongjiang Province included only high-high clusters, only low-low clusters, only high-low outliers and multiple types. (4) The temporal changes in soybean yield in various counties of Heilongjiang Province had obvious regional characteristics. (5) Socioeconomic factors had aftereffects on soybean planting decisions. (6) Sunlight hours, the price ratio of local soybeans to local maize, average temperature, the number of soybean patents, the price ratio of imported soybeans to local soybeans, soybean cultivation income, local soybean prices, and the number of newly established soybean enterprises were primary influencing factors. Precipitation and soybean import volume were secondary influencing factors. The income difference between maize and soybeans, crops-hitting disaster area, and maize yield were general influencing factors. This study aims to offer new pathways for alleviating the structural contradiction between soybean supply and demand and to provide a reference for the formulation of national soybean industry policies and food security strategies.

Economic Evaluation and Risk Premium Estimation of Rainfed Soybean under Various Planting Practices in a Semi-Humid Drought-Prone Region of Northwest China

Economic benefits and risk premiums significantly affect the production system decision making of farmers and government departments. This study evaluated the economic feasibility and estimated the risk premium of 12 rainfed soybean production systems with various planting densities, fertilization rates and planting patterns by considering the impact of soybean price fluctuation. There were two planting densities (D1: 160,000 plants ha−1 and D2: 320,000 plants ha−1), two fertilization rates (F1: 20 kg ha−1 N, 30 kg ha−1 P, 30 kg ha−1 K; F2: 40 kg ha−1 N, 60 kg ha−1 P, 60 kg ha−1 K) and three planting patterns (F+W0: flat cultivation with no irrigation; R+W0: plastic-mulched ridge-furrow cultivation (PMRF) with no irrigation; R+W1: PMRF with supplemental irrigation of 30 mm at the pod-filling stage). Based on the two-year (2019–2020) field data in a semi-humid drought-prone region of northwest China and soybean price fluctuation from January 2014 to June 2021, the net income (NI) was calculated by considering the impact of soybean price fluctuation and assuming constant soybean production costs. The net present value (NPV) method and the stochastic efficiency with respect to a function (SERF) method were used to evaluate the profitability of protective alternatives and the risk of these alternatives. The results showed that the 12 proposed soybean production systems were economically feasible. Reducing the fertilization rate reduced the input costs, but it did not necessarily result in a decrease in soybean yield and NI. The payback period of all production systems was within two years for farmers investing through loans. High-fertilizer and high-density production systems made personal investment obtain the highest economic benefit in this study, which was not the best investment strategy from the perspective of production-to-investment ratio and environmental protection departments. The preferences of farmers with various risk aversion and environmental protection departments in terms of risk premium were also proposed. The economic and risk assessment framework of this study can enhance the understanding of the adjustment of production systems from different perspectives, and provide strategies for promoting the protection of economic, environmental and socially sustainable agricultural systems.

FUTURES PRICES LINKAGES IN THE US SOYBEAN COMPLEX

This work investigates the linkages among the futures prices of soybeans, soybean meal, and soybean oil in the US. This has been pursued using a flexible methodology that allows modelling price relationships at different parts of their joint distribution. According to the empirical results, the markets are strongly connected in the vertical direction regardless of the sign and the size of shocks. The meal and oil prices maintain a negative relationship at the median and the upper quantiles but they are not connected under large negative shocks. The soybean market is a net transmitter of price risk to the other two markets while price shocks around the median tend to be transmitted with higher intensity relative to those at the extremes.

Meta-Analytic Modeling of the Severity-Yield Relationships in Soybean Frogeye Leaf Spot Epidemics.

Frogeye leaf spot (FLS), caused by Cercospora sojina, is an important foliar disease affecting soybean in the United States. A meta-analytic approach including 39 fungicide trials conducted from 2012 to 2021 across eight states (Alabama, Arkansas, Illinois, Iowa, Kentucky, Louisiana, Mississippi, Tennessee) was used to assess the relationship between FLS severity and soybean yield. Correlation and regression analyses were performed separately to determine Fisher's transformation of correlation coefficients (Zr), intercept (β0) and slope (β1). Disease pressure (low severity, ≤34.5; high severity, >34.5%) and yield class (low, ≤3,352; high, >3,352 kg/ha) were included as categorical moderators. Pearson's [Formula: see text], obtained from back-transforming the [Formula: see text]r estimated by an overall random-effects model, showed a significant negative linear relationship between FLS severity and yield ([Formula: see text] = -0.60). The [Formula: see text]r was affected by disease pressure (P = 0.0003) but not by yield class (P = 0.8141). A random-coefficient model estimated a slope of -19 kg/ha for each percent severity for a mean attainable yield of 3,719.9 kg/ha. Based on the overall mean (95% CI) of the intercept and slope estimated by the random-coefficients model, the estimated overall relative damage coefficient was 0.51% (0.36 to 0.69), indicating that a percent increase in FLS severity reduced yield by 0.51%. The best model included yield class as a covariate, and population-average intercepts differed significantly between low (3,455.1 kg/ha) and high (3,842.7 kg/ha) yield classes. This highlights the potential impact of FLS on soybean yield if not managed and may help in disease management decisions.

APPLICATION OF ARCH/GARCH MODELS IN ANALYSIS OF PRICE VOLATILITIES LOCAL, IMPORTS (USA), AND WORLD

Soybeans are one of Indonesia’s strategis agricultural commodities. Soybean prices fluctuation due to high demand and low stock of soybeans. This study was conducted to determine the behavior of local soybean prices in Indonesia, imported soybeans from the USA, and world soybeans. This study uses monthly soybean price time series data from January 2017 to March 2022 for local and world soybean price data and for imported soybean price data (USA) from January 2018 to March 2022. The data is obtained from the Kementrian Perdagangan, UN Comtrade, and the World Bank. The research method used is the ARCH/GARCH analysis method. The result of this study is the estimation of the GARCH model on the volatility of local soybean prices in Indonesia, imported soybeans (USA), and world soybeans obtained the GARCH (1,1) model. Based on the GARCH (1,1) model, the price of local soybeans in Indonesia is more volatile than the price of imported soybeans (USA) and the price of world soybeans is more volatile than the price of imported soybeans (USA). The prices of local soybeans in Indonesia, imported soybeans, and world soybeans are more volatile after the Covid-19 pandemic than before the Covid-19 pandemic. Future forecasts of local soybean prices in Indonesia, imported soybeans, and world soybeans are predicted to increase with the highest price in December 2024 of IDR 15,391.21 for local soybeans, IDR 11,303.92 for imported soybeans, and IDR 12,069.11 for world soybeans. This price forecast can be used as a reference by the government in planning soybean import policies.

The dynamics of price discovery between the U.S. and Chinese soybean market: a wavelet approach to understanding the effects of Sino-US trade conflict and COVID-19 pandemic

During geopolitical crises, the price stability of agricultural commodities is critical for national security. Understanding the dynamics of pricing power between the U.S. and China and how it varies over time can help smaller nations navigate unpredictable moments. This study uses a unified framework and wavelet approach to examine soybean price discovery in the U.S. and China from the standpoints of price interdependence and information flows. We begin by illustrating the integrated link between the soybean futures markets in the U.S. and China, which includes multiple structural breaks. The pricing difference between the two nations acts as the primary information spillover route for their integrated relationship. Furthermore, we show that the direction and degree of information spillover change dramatically in proportion to the strength of the U.S.–Chinese soybean interaction. Finally, we find that China’s recent retaliatory tax on the U.S. soybeans gave the Chinese market a more powerful position in soybean futures price discovery. After the first-stage trade deal was reached, and during the epidemic phase of the coronavirus pandemic, the pricing power of the U.S. soybean market showed no signs of full recovery.

Dynamic connectedness between energy markets and the Brazilian cash market: An empirical analysis pre‐ and post‐COVID‐19

AbstractBrazil's significant commodity production is internationally recognized, yet the absence of a mature futures market exposes it to price risks and international shocks. This study explores the dynamic connectedness between commodity futures and the Brazilian cash markets, using a time‐varying parameter vector autoregressive model. We also assess COVID‐19's impact on this connectedness. We find a significant influence of oil prices on Brazilian ethanol prices, and particularly emphasize the Heating Oil spillover effect on ethanol in the post‐COVID‐19 era. We also note the ascension of Brazilian soybean spot markets' international significance since 2017, amplifying their role in global grain price discovery. Finally, by computing hedge ratios and effectiveness between commodity futures contracts and Brazilian spot prices, our study reveals soybean cash price as the most effective hedge. These insights deepen comprehension of connectedness within Brazilian commodity markets, thereby guiding investors and policymakers in strategic energy policy decisions.

Keragaan dan Analisis Rasio Keuangan Usaha Penjualan Kedelai (Studi Kasus pada PT. Sari Eco di Desa Gudang Kecamatan Tanjungsari Kabupaten Sumedang Jawa Barat)

This study aims to determine the performance of soybean sales at PT. Sari Eco and know the company's financial performance seen from the liquidity ratio, solvency ratio, profitability ratio and activity ratio. This research uses a case study method through a quantitative descriptive approach. The result of this research is PT. Sari Eco is a company engaged in the supply of food ingredients that has sold a lot of soybeans to various tofu and tempeh craftsmen in Sumedang Regency. The company was founded in 2000 with the founder Mr. Ace as owner. With the support of the potential of soybeans which are often used in making processed tofu and tempeh in Sumedang Regency, PT. Sari Eco has won a lot of trust from tofu companies and is always ready to partner with other companies. Based on the results of research for financial performance assessment using financial ratio analysis, namely the analysis of liquidity ratios, solvency ratios, profitability ratios and activity ratios at the company PT. Sari Eco. The company's financial performance of PT. Sari Eco is not healthy which is decreasing every month. The company is having difficulty selling its products due to the Covid-19 pandemic and the rising soybean prices. This must be considered so that the users of the company's assets experience improvements every month.