scholarly journals ECONOMICAL AND FINANCIAL ANALYSIS OF AVIARIES FOR THE INTEGRATION OF BROILERS UNDER CONDITIONS OF RISK

2015 ◽  
Vol 39 (3) ◽  
pp. 240-247 ◽  
Author(s):  
Danilo Simões ◽  
João Paulo Ribeiro ◽  
Pedro Rodrigo Gouveia ◽  
Josiane Corrêa dos Santos
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Financial Analysis ◽  
Financial Risks ◽  
Financial Return ◽  
Financial Investment ◽  
Flow Models ◽  
Investment Projects ◽  
Broiler Production ◽  
Technological Level

Financial investment projects are characterized by uncertainties. When quantified, these will determine the probability of their occurrence and the condition of risk. This information might be analyzed via simulation of Monte Carlo Method, which will establish the level of associated risk. To understand the financial risks of broiler production in integration system, cash flow models for aviaries were formulated with different technological levels. Using deterministic techniques, the value of the main economic viability indicators were calculated, which were incorporated to the risk through a probabilistic model of pseudo-random numbers, generated with Monte Carlo Method. The uncertainties associated to financial projects show that broiler production in different integration systems is economically viable. However, the best financial return and smallest risk are obtained with an aviary which contains low technological level and the least financial investment.

scholarly journals Simulation Modeling in Assessing the Effectiveness and Risk of Investment Projects

2020 ◽  
Vol 22 (1) ◽  
pp. 119-124
Author(s):  
Volodymyr Kharchenko ◽  
◽  
Hanna Kharchenko ◽  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Agricultural Production ◽  
Random Number ◽  
Investment Project ◽  
Average Risk ◽  
Universal Method ◽  
Investment Projects ◽  
The Monte Carlo Method ◽  
The Impact

Introduction. The article deals with the modeling features in the implementation of investment projects using the Monte Carlo method. The purpose of the article is to substantiate the feasibility of using economic and mathematical models to identify the risks of investment projects in agricultural production, taking into account the randomness of factors. Results. The expediency of using this method during the analysis of projects in agriculture is determined. This type of modeling is a universal method of research and evaluation of the effectiveness of open systems, the behavior of which depends on the influence of random factors. Particular attention is paid in such cases to decisions on the implementation of investment projects. The expediency of using this method in the analysis of projects in agriculture is determined. The main characteristics of the investment project are considered: investments involve significant financial costs; investment return can be obtained in a few years; there are elements of risk and uncertainty in forecasting the results of the investment project. The algorithm of the analysis of investment projects consisting of various stages is offered. The importance of investigating the risks of investment projects in agricultural production is substantiated. It is investigated that the basis of the Monte Carlo method is a random number generator, which consists of two stages: generation of a normalized random number (uniformly distributed from 0 to 1) and conversion of a random number into an arbitrary distribution law. The task of choosing an investment project for a pig farm is proposed. The calculations revealed that the amount of the expected NPV is UAH 63,158.80 with a standard deviation of UAH 43,777.90. The coefficient of variation was 0.69, so the risk of this project is generally lower than the average risk of the investment portfolio of the farm. Conclusions. The results of the analysis obtained using the method of Monte Carlo simulation are quite simple to interpret and reflect the change of factors over a significant interval, taking into account the probabilistic nature of economic factors. Thus, this method allows the implementation of the investment project to assess the impact of uncertainty on the final result of the project.

scholarly journals Planning Tunnel Construction Using Markov Chain Monte Carlo (MCMC)

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Juan P. Vargas ◽  
Jair C. Koppe ◽  
Sebastián Pérez ◽  
Juan P. Hurtado
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distributions ◽  
Financial Risks ◽  
Underground Excavation ◽  
Construction Time ◽  
Tunnel Excavation ◽  
Unit Operations

Tunnels, drifts, drives, and other types of underground excavation are very common in mining as well as in the construction of roads, railways, dams, and other civil engineering projects. Planning is essential to the success of tunnel excavation, and construction time is one of the most important factors to be taken into account. This paper proposes a simulation algorithm based on a stochastic numerical method, the Markov chain Monte Carlo method, that can provide the best estimate of the opening excavation times for the classic method of drilling and blasting. Taking account of technical considerations that affect the tunnel excavation cycle, the simulation is developed through a computational algorithm. Using the Markov chain Monte Carlo method, the unit operations involved in the underground excavation cycle are identified and assigned probability distributions that, with random number input, make it possible to simulate the total excavation time. The results obtained with this method are compared with a real case of tunneling excavation. By incorporating variability in the planning, it is possible to determine with greater certainty the ranges over which the execution times of the unit operations fluctuate. In addition, the financial risks associated with planning errors can be reduced and the exploitation of resources maximized.

New explicit closed form formulae for the prices of catastrophe options

2015 ◽  
Vol 02 (02) ◽  
pp. 1550017 ◽  
Author(s):  
Yunguo Jin ◽  
Shouming Zhong
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Measure ◽  
Option Pricing ◽  
Closed Form ◽  
Stock Returns ◽  
Financial Risks ◽  
Counterparty Risk ◽  
Catastrophic Risks ◽  
Risk Neutral Measures

The paper presents an approach of probability measure changes to the pricing of catastrophe options with counterparty risk and new catastrophe option pricing formulae. According to our knowledge, there still does not exist a literature to present the approach of probability measure changes to option pricing when underlying stock returns are discontinuous (in particular, catastrophe options). We shall see that sometimes it is convenient to change the risk-neutral measures. Furthermore, our models and results have potential improvements. Finally, we use Monte Carlo method to the analog calculation of the formulae, and demonstrate how financial risks and catastrophic risks affect the price of the catastrophe options.

scholarly journals Improving the assessment of the environmental and economic efficiency of measures

2021 ◽  
Vol 112 ◽  
pp. 00002
Author(s):  
Inna P. Bandurinа ◽  
Mikhail A. Bandurin ◽  
Alexander P. Bandurin
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Economic Efficiency ◽  
Land Reclamation ◽  
Simulation Method ◽  
International Standards ◽  
Future Research ◽  
Investment Projects ◽  
The Monte Carlo Method

The purpose of the study is to improve methods for improving the regulatory and methodological framework for assessing the environmental and economic effectiveness of land reclamation investment projects. The research methodology is based on the Monte Carlo method, which corresponds to international standards, the theory and algorithms of innovative methods for determining risks, as well as the ability to provide the user with information about the content of risk assessment operations and ensure that their preferences are taken into account in the calculation process. Currently, many tools have been developed for automating risk analysis procedures, including those performed by the Monte Carlo method, which are described in various studies with varying degrees of completeness. The analysis of priority methods of assessing the risks of achieving the projected economic indicators of project solutions is performed and the prospects of the simulation method for practical use in the field of land reclamation are shown. The results of the risk assessment of environmental and economic efficiency of anti-filtration coatings of hydraulic structures of irrigation systems performed by the Monte Carlo method in the environment of the Crystal Ball software product are presented, and the need to improve the reliability of the predicted results of the effectiveness of the designed measures is established. Future research is risk assessment of profitability of the designed activities promote the development of existing and formation of new theories to justify the feasibility of implementation of reclamation investment projects.

scholarly journals Hierarchical method of randomized composite indicators and its application for comparison of investment attractiveness of the projects

2020 ◽  
pp. 111-131
Author(s):  
Dmitrii Vladimirovich Kolodko
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Sample ◽  
Weight Vector ◽  
Composite Indicators ◽  
Hierarchical Level ◽  
Investment Projects ◽  
Hierarchical Method ◽  
The Subject

The object of this research is the methods of multi-criteria selection. The subject of this research is the problems of application of hierarchical method of randomized composite indicators in solving the problems of multi-criteria selection. It is noted that in gradual synthesis of composite indicators of the highest hierarchical level, it is impossible to obtain the exact values or assessment of probabilities of dominance of the compared objects. Structuring the exhaustive set of values of weight vector of hierarchy allows obtaining these probabilities, but such approach is applicable only in case of small number of characteristics of the compared objects. For solving this task, the author employs Monte Carlo method, consisting in formation of random sample from exhaustive set of weigh vector of hierarchy and sequential assessment of essential characteristics. The article suggests the procedure for assessing probability characteristics of randomized composite indicators. The author develops and presents the software written on the R platform for realization of this procedure. An example of comparison of the investment projects, when selection is based on the probability of dominance, rather than the composite indicators, is demonstrated.

scholarly journals Financial and Statistical Analysis of Investment Projects High-Tech Scientific Developments Based on Carbon Nanomaterials

2017 ◽  
pp. 46-52
Author(s):  
F. V. Motsnyi ◽  
M. E. Sinytskyi
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Carbon Nanomaterials ◽  
Net Present Value ◽  
High Tech ◽  
Market Prices ◽  
Investment Projects ◽  
The Family ◽  
The Impact ◽  
Selection Of

Carbon nanomaterials (graphene, nanotubes, fullerenes, the family of derivatives from C ) belong to the miraculous materials of 21 century, which can radically change technologies in the coming years. Thus, unique supercapacitors with the capacity of 10.000 F have been proposed on their basis, which is 12.5 thousand higher than the capacity of the Earth. Immense funds have been invested globally in research of carbon nanomaterials and development of devices on their basis. Utilization of scientific advancements in the domestic industry will promote economic growth, innovation society building and market recovery in Ukraine. This article is the first to pose the question about selection of advanced developments projects on the basis of carbon nanomaterials using Monte Carlo method. Investment projects for high tech scientific developments (nanotubes, nanobatteries, supercapacitors, nanoaccumulators) are analyzed. Approaches to account for the risks of investment projects in the conditions of non-established stock market in Ukraine are shown. Use of Monte Carlo method as the most preferred approach to evaluating the impact of risks on decision-making in the conditions of uncertainty is substantiated. Current market prices on respective products are used as the input database. The Net Present Value (NPV) and the probability of its negative numbers are computed. The point of the project reliability at which the probability of negative NPV numbers approximates zero is found. It is shown that this point can be used as the benchmark, because the relative distance to it is the criterion for selection of the most acceptable version of project implementation. The projects with minimal expected risks of implementation are selected.

Outbursts of comet Schwassmann-Wachmann 1, and the cloud of interplanetary boulders

1974 ◽  
Vol 22 ◽  
pp. 307 ◽  
Author(s):  
Zdenek Sekanina
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Interplanetary Space ◽  
Porous Matrix ◽  
Maximum Diameter ◽  
Expansion Velocity ◽  
Solid Constituent ◽  
Meteoric Material ◽  
Periodic Comet

AbstractIt is suggested that the outbursts of Periodic Comet Schwassmann-Wachmann 1 are triggered by impacts of interplanetary boulders on the surface of the comet’s nucleus. The existence of a cloud of such boulders in interplanetary space was predicted by Harwit (1967). We have used the hypothesis to calculate the characteristics of the outbursts – such as their mean rate, optically important dimensions of ejected debris, expansion velocity of the ejecta, maximum diameter of the expanding cloud before it fades out, and the magnitude of the accompanying orbital impulse – and found them reasonably consistent with observations, if the solid constituent of the comet is assumed in the form of a porous matrix of lowstrength meteoric material. A Monte Carlo method was applied to simulate the distributions of impacts, their directions and impact velocities.

Sign in / Sign up

Export Citation Format

Share Document