Pricing European options on agriculture commodity prices using mean-reversion model with jump diffusion

Dharmawan, Komang

doi:10.1063/1.4979418

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…On the other hand, the application of Monte Carlo simulation employs a stochastic approach in which the involved variables are modeled as probability distributions. Instead of providing fixed estimates, Monte Carlo simulation considers the uncertainties associated with each variable and generates multiple simulations to obtain a probabilistic distribution of possible outcomes, considering market variability and uncertainties [5,34,[73][74][75][76].…”

Section: Discussionmentioning

confidence: 99%

Forecasting costs and risk of corn and soybean crops through Monte Carlo simulation

Amorim,

Guimarães,

Marcomin

et al. 2023

Preprint

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In Brazil, the production of corn and soybeans has been growing significantly in recent years. Considering that the strategies for investing in the production of these crops are conditioned by production costs and risk, the objective of this article is to propose a simulation model that indicates the trend of production costs for these commodities, considering the dispersion and correlation of selected key variable prices and corn and soybean production costs practiced between the years of 2018 and 2022. Fifty specialized companies in the state of Sao Paulo, Brazil, provided data for this study, and Monte Carlo simulations showed that the total cost of corn production/ha is between USD 600.00 and USD 1150.00, with a level of certainty of 84.7%, and soybeans are in the range of USD 260.00 to USD 420.00, with a level of certainty of 86.4%. The model evidenced a trend of decreasing production costs for the crops for the 2023/24 and 2024/25 harvests, as the input with the greatest impact (fertilizer) is showing a downward trend. On the other hand, costs related to labor, soybean seed, and fungicides are showing an upward trend, while dolomitic limestone corrective remains stable.

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Section: Discussionmentioning

confidence: 99%

Forecasting costs and risk of corn and soybean crops through Monte Carlo simulation

Amorim,

Guimarães,

Marcomin

et al. 2023

Preprint

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“…These shocks might be correlated, and may harm also non-agricultural markets. (Gilbert & Morgan) Prices of agricultural commodities are adjusted seasonally, which is not a characteristic of other financial instruments (Dharmawan, 2017). The importance of derivatives in agricultural commodities has enlarged in the last two decades, since the volume and variety of agricultural commodities traded on the market has increased (Dharmawan, 2017), (Hull J. C., Options, Futures, and Other Derivatives, 2008).…”

Section: Futuresmentioning

confidence: 99%

Risk Exposition of Prices in Agricultural Commodities Using Options and Futures

Karabegovic

2018

scjournal

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“…Popularitas komoditas pertanian di kalangan investor di pasar saham telah berkembang sejak tahun 2000. Hal ini disebabkan oleh tuntutan diversifikasi portofolio dan meningkatnya permintaan untuk kebutuhan komoditas pertanian, seperti minyak kelapa sawit, kakao, kopi, dan lain-lain (Dharmawan, 2016). Harga komoditas pertanian ataupun perkebunan (kedelai, gandum, kopi, kakao) digerakkan oleh pasokan musiman, umumnya harga akan lebih tinggi sebelum musim panen (Barakova & Geman, 2006), karena komoditas perkebunan diproduksi secara musiman, tetapi dikonsumsi sepanjang tahun.…”

Section: Pendahuluanunclassified

Aplikasi Model Mean Reversion Dengan Musiman Dalam Menentukan Nilai Kontrak Opsi Tipe Eropa Pada Harga Komoditas Kakao

Dewi

Dharmawan

Asih

2017

MTK

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Many literatures explain that commodity prices tend to follow the pattern of Mean Reversion models, commodity prices are controlled by seasonal supplies resulting in price fluctuations. To overcome the risk of fluctuations in the price, an investor can hedge with option contracts. The purpose of this research was to know the application of Mean Reversion model with seasonal in determining the value of European option contract from commodity ,by estimating the parameters and simulating the model in order to get the value of European option contract. Thus, the values of the options obtained with the model was compared with the value of the options calculated by the Black-Scholes model. The results of this study indicated that the value of contract option of Mean Reversion model with seasonal value was lower than the Black-Scholes model.

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Pricing European options on agriculture commodity prices using mean-reversion model with jump diffusion

Cited by 4 publications

References 8 publications

Forecasting costs and risk of corn and soybean crops through Monte Carlo simulation

Forecasting costs and risk of corn and soybean crops through Monte Carlo simulation

Risk Exposition of Prices in Agricultural Commodities Using Options and Futures

Aplikasi Model Mean Reversion Dengan Musiman Dalam Menentukan Nilai Kontrak Opsi Tipe Eropa Pada Harga Komoditas Kakao

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