Analyzing food production risk with Monte Carlo simulation

Mahmudiono, Trias; Jasim, Saade Abdalkareem; Alghazali, Tawfeeq; Kadhim, Mustafa M.; Iswanto, A. Heri; MAJEED, Mohammed Sabeeh; Sharma, Sandhir; AL-MAWLAWI, Zaid Shaker; Panduro-Tenazoa, Nadia Masaya

doi:10.1590/fst.03522

Cited by 2 publications

(3 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Monte Carlo simulation has become essential in analyzing financial products as these financial products become more complex. This method is utilized for pricing financial instruments and plays a crucial part in risk analysis [16]. Monte Carlo simulations assume that market prices are influenced to some extent by a random factor, which can be represented by a random walk [6].…”

Section: Monte Carlo Simulationmentioning

confidence: 99%

Stock Hedging Using Strangle Strategy on Vanilla Options and Capped Options

Lesmana,

Martal,

Nabila

et al. 2024

jak

View full text Add to dashboard Cite

The financial market often experiences unexpected fluctuations that can impact stock values. Therefore, investors require hedging strategies to protect their investment values from unwanted price fluctuations. This study compares the hedging results using the strangle strategy on Vanilla options and Capped options on Micron Technology, Inc. (MU) stock. The methods used are Monte Carlo simulation and Black Scholes Merton to calculate the option prices. The research results indicate that the strangle strategy on Vanilla options has unlimited maximum profit potential, whereas on Capped options, the profit is capped above. However, the potential maximum loss on Capped options is lower than that on Vanilla options. Therefore, Capped options are preferred for hedging the MU stock. The research yields significant practical and theoretical benefits. Practically, it offers investors insights into more effective hedging choices for risk management and profit potential in the stock market. Opting for capped options allows investors to control risk better while preserving profit potential. Theoretically, the study enhances our understanding of cost efficiency and risk profiles across various options strategies, making a vital contribution to financial literature.

show abstract

Section: Monte Carlo Simulationmentioning

confidence: 99%

Stock Hedging Using Strangle Strategy on Vanilla Options and Capped Options

Lesmana,

Martal,

Nabila

et al. 2024

jak

View full text Add to dashboard Cite

show abstract

“…Among these, Monte Carlo methods, suitable for complex numerical models, are predominantly used, with the number of simulations generally set at 10,000 (Wang et al, 2023). The Monte Carlo method, born in the 1940s and based on probability statistics theory for nuclear weapon research, has expanded to various fields with the development of computer theory and applications, becoming a widely used simulation approach (Mahmudiono et al, 2022). Therefore, based on the consideration of multidimensional food security concepts and the inherent logic of uncertainty, this study attempts to enrich the research methods of food security in China by conducting Monte Carlo simulations for different food security indicator systems, expanding the paths for selecting and determining indicators, and exploring more precise measures for ensuring food security.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Only some studies on food security are based on a complete combination of qualitative and quantitative. This paper fills this gap by drawing on Woods et al (2016) in the qualitative research to determine the food security indicators by using Nvivo software coding to code and saturation test 199 literature samples sequentially and by referring to 10.3389/fsufs.2024.1363340 Frontiers in Sustainable Food Systems 03 frontiersin.org Mahmudiono et al (2022) in the quantitative study to determine the food security indicators using entropy method, principal component analysis. The food security indicators' weights will be determined, and the robustness of the indicator system will be verified based on Monte Carlo simulation methods, which can be combined with future studies that use the indicator system as a topic of discussion.…”

Section: Introductionmentioning

confidence: 99%

Construction and system evolution analysis of China’s food security indicator system

Yuting,

Meng

2024

Front. Sustain. Food Syst.

View full text Add to dashboard Cite

In recent years, the number of countries experiencing a deterioration in food security has been increasing to the detriment of the healthy development of their people. China has made significant achievements in safeguarding food security, but only some studies have comprehensively summarized China’s important initiatives and successful experiences in protecting food security since the 1960s. In this paper, we use qualitative and quantitative methods to determine the food security indicator system and observe the development of China’s food security from 1961 to 2019 to provide a reference for countries threatened by hunger and malnutrition to get out of the predicament. First, 199 pieces of literature were subjected to three-level coding and saturation test using Nvivo software to preliminarily establish an indicator system for measuring China’s food security, which consists of two categories: food chain and external environment, five subsystems: food supply, food circulation, food consumption, international factors, and domestic factors, as well as 12 specific indicators. Subsequently, the entropy weight coefficient and hierarchical analysis methods are used to calculate two different indicator weights. Monte Carlo simulation compares the uncertainty of the indicator weights calculated by the two methods. We found that the uncertainty of the indicator weights determined by the hierarchical analysis method is much higher than that of the entropy coefficient method, so the indicator weights determined by the entropy coefficient method are chosen. Based on the formation of the food security indicator system, the obstacle degree test was carried out for each indicator. We found that the average wage of urban employees before 2015 was the main obstacle to China’s food security. However, the population kept growing after 2015, which became the main obstacle to China’s food security. Secondly, the evolution characteristics of the overall level of China’s food security and the subsystems from 1961 to 2019 were analyzed individually. We found that the overall level of China’s food security has been continuously improving. However, the subsystems still have hidden dangers, and the most prominent one is the food consumption subsystem, whose composite index has been continuously decreasing and has become the main factor undermining China’s food security. The scientific construction of China’s food security indicator system will help to identify and warn of hidden food security problems promptly and, at the same time, will help to summarize and promote China’s successful experience in safeguarding food security. Food security is the foundation of agricultural development, and ensuring food security significantly impacts national security, social stability, people’s livelihoods, and health. A scientifically constructed indicator system for China’s food security can help identify and alert potential food security risks. Based on accurate indicator data and analysis results, more effective food security policies and measures can be formulated, ultimately promoting the sustainable development of the gain industry.

show abstract

Analyzing food production risk with Monte Carlo simulation

Cited by 2 publications

References 32 publications

Stock Hedging Using Strangle Strategy on Vanilla Options and Capped Options

Stock Hedging Using Strangle Strategy on Vanilla Options and Capped Options

Construction and system evolution analysis of China’s food security indicator system

Contact Info

Product

Resources

About