Oil price is the most important and effective economic parameter during the course of oil projects evaluation process. Oil price uncertainty is affected by some factors such as political issues, supply and demand, advancement of technology etc. Therefore, evaluating an oil project is unreliable unless these uncertainties are taken into account and in some circumstances, not doing so may mislead the oil projects evaluators, managers and shareholders. To solve this problem, many researchers have tried to present intelligent models for estimating oil prices using fuzzy logic, neural networks, etc. In addition to their high accuracy, these methods gives easier and faster estimation. In the present study, taking the importance of the oil price prediction into account, OPEC crude oil data were collected weekly during 2013-2016, and some prediction models were presented using artificial neural network method, time series functions and binomial tree. Comparing the results obtained from the three models and those of the real data showed that the estimation made by neural network method is much more reliable.

Increasing the dynamics of the conditions governing economic and financial activities and increasing the risk of decision-making in the field of investment or financing of investment projects and economic projects requires the existence of an appropriate and efficient analytical method that does not have the shortcomings of conventional methods of discounting cash flows, including stagnation. Accordingly, and in response to new needs, the real option of assignment with a binomial tree approach in the DERIVAGEM software has been used for decision-making. For pricing using this method, input parameters are required. For the asset price parameter, the present value of the plan is considered, and for the exercise price parameter (agreed price), the present value of the cost is considered. Finally, the conventional method and the real option method are compared. The pricing results show that the value of the option to abandon is 1,273,845 million rials, which is the value of the project, or in other words, the value of the developed project, is estimated at 1,229,258 million rials, which is higher than the conventional method. The appropriate times for the relevant project Abandonment are at nodes (4,5) and (5,6). Based on sensitivity analyses, the strongest variable affecting the project value at the disposal of the release is the fluctuation of the asset value.

Summary: Economic parameters uncertainties perform indispensable role in mining evaluation projects, so that, evaluation of a mining project without considering the available uncertainties is incorrect and unreliable. Metal price uncertainty is the most important parameters in economic uncertainty. Many researchers have studied the role of economic uncertainties in the production planning. But majority of these studies are conducted in one-element deposits and the two-element deposits are rarely investigated. In this research uses the binomial tree technique valuation to compute the production planning evaluation in tow element deposits under price uncertainty. It is concluded that the mine evaluation suggests greater net present value when price uncertainty is considered for both element. Introduction: The main sources of uncertainty arising at the beginning of a mine project can be categorized into three groups: geology uncertainties, engineering uncertainties and economic uncertainties. Many researchers studied these types of uncertainties. In majority of the aforementioned researches, price uncertainty effect was investigated only for one-element deposits, which can result in an inaccurate valuation. Therefore, in this paper, The binomial tree method was used for determining the effect of price uncertainty in valuation of two-element deposits. Methodology and Approaches: In this research uses the binomial tree technique valuation to compute the production planning evaluation in tow element deposits under price uncertainty for four scenarios: Assuming price certainty for both elements; assuming price uncertainty for first element and price certainty for second element; assuming price certainty for first element and price uncertainty for second element; assuming price uncertainty for both elements. Results and Conclusions: It is concluded that the mine evaluation suggests least NPV the amount 245. 05 thousand dollar when price certainty is considered for both elements and greater NPV the amount 349. 6 thousand dollar when price uncertainty is considered for both elements. The sensitivity analysis shown that even by changing in input economic parameters, the NPV, which was computed in price uncertain for both elements, was the greatest.

This paper suggests a composed option pricing model based on black-scholes and binomial tree models. So at first this two models are presented and analyzed. Then we showed black-scholes model is an appropriate option pricing model for stocks with low volatility and binomial trees model is an appropriate option pricing model for stocks with high volatility. Suggested model is a composed model of black-scholes and binomial tree models and volatility is used as selecting model factor. To determine volatility limit quantity, we calculated average volatility of Iran Stock Exchange. For this calculating we selected 32 stocks in two period of time. At the end of paper, suggested model is validated by 2 methods and it’s validity is approved by both of them.

Encouraging foreign and private sectors to participate in renewable projects in developing countries, which not only experience rapid growth in energy demand but also encounter challenges in financing clean projects, presents a complex issue for their governments. To address this challenge, two contentious issues must be addressed concurrently: 1) accurate long-term valuation of Renewable Energy (RE) projects and 2) the assessment of the ideal timing for investments. This paper introduces a binomial tree real-option-based model as a valuable tool for valuing Renewable Energy (RE) projects and determining the optimal timing for investments in developing countries. Three key factors influencing project cash flow were considered in the calculation: Feed-in Tariff (FiT), Maintenance and Operation (M&O) costs, and energy production. Three scenarios were analyzed for exercising option to either improve project profitability, maintain the current profit, or prevent further losses. A real life case study involving a solar photovoltaic (PV) park in Iran has also been investigated to validate and verify the proposed model. The results revealed that, unlike traditional methods such as Net Present Value (NPV) which yielded a negative value suggesting that the project lacks financial viability, the option-based model demonstrated the project's investment potential by generating a positive value through the incorporation of option values inherent in growth projects.

The purpose of this research is the pricing of gold coin option contracts in Iran mercantile exchange. The price of gold coin option contracts has been estimated by the Black– Scholes, Boness and Binomial tree models. For this purpose, the theoretical prices have been compared whith the Black-Scholes method for each maturity from December 2016 to November 2017. The theoretical prices of the option contracts have been compared with market prices in Iran mercantile exchange. The volatility of the gold coin in the market has been estimated by the GARCH method as a variable in the pricing models. The comparison of pricing call options indicates that the theoretical prices of the call option based on Black-Scholes method were more than the theoretical prices on the Boness method. The comparison of pricing put options indicates the theoretical prices of the put option based on Black-Scholes method were lower than the theoretical prices based on Binomial tree method at the level of the strike price 12750000 Rials.

The Railway transportation industry is one of the major indicators of the development of countries. On the other hand, the railway transportation sector has many risks and uncertainties that can be considered as a negative factor from the perspective of investors. The purpose of this study is to identify and manage the risk of the railway transportation sector, which has been used as an example of the listed Stock exchange companies of railway transport. The risks of the railway transportation sector, especially the systematic risk of rail stock companies, are estimated with the beta coefficient, and then the ranking of rail stocks will be done according to the systematic risk. Related stocks are priced according to systematic risk with the capital assets pricing model. After identifying the risks of this sector, for risk management, option valuation will be used using the binomial model. Finally, the sensitivity of the option price of railway shares is checked using Greek parameters. Due to the large volume of data and their non-normality, in order to predict the future price and the exercise price of stocks, the Monte Carlo simulation method is used for option pricing. According to the outputs of the model and the examination of the movement path and price changes of rail stocks and option prices with the help of the binomial model in Python and DERIVAGEM software, as well as the estimation of the option price sensitivity by Greek parameters, relevant analyzes are expressed for different rail stocks.

Introduction: The use of new financial instruments, and specifically option contracts, as a tool for risk management and create profitability, can help to boom exchanges and reduce the problems of the agricultural sector. Given the increasing population and the growing need for animal protein, the fluctuation in prices of these products can have a significant impact on the food security of individuals. The fluctuation of the prices of production inputs, including soybean meal and corn, can lead to fluctuations in the price of meat. The Iran Mercantile Exchange can play a major role in eliminating concerns and concerns of market participants for strategic agricultural products, including soybean meal and corn, using derivatives such as futures contracts and options. The trend of development of commodity exchanges in the world suggests that the emergence and development of these markets activities in the field of economy, seeks to dispel some of the economic needs and in many cases, eliminate some of the bottlenecks and barriers in the commodity market. The trend of development of commodity exchanges in the world suggests that the emergence and development of these markets activities in the field of economy, seeks to dispel some of the economic needs and in many cases, eliminate some of the bottlenecks and barriers in the commodity market. Option contracts is one of derivatives in commodity exchange that can have effective roll in agricultural market for overcome the problems of traditional market and reduce the risk of investors in this market. According to population, growth and increasing demand for Chicken meat and eggs, soybean meal and maize prices volatility may be fluctuating prices for white meat and egg. According to this, the aim of this study is determine the price of Asian option and Sensitivity parameters. Materials and Methods: Among quantitative methods to calculate derivatives and risk sensitivity parameters of an option, binomial tree model is frequently used. Arithmetic and Geometric Asian option with fixed and floating expiration prices were calculated using the binomial tree model for soybean meal and maize. Moreover, the sensitivity of an option's price to changes (Change in the price of the underlying asset, Delta, price volatility, time until maturity and risk-free interest rate) measured by using sensitive parameters and the impact has been obtained. Required information includes historical data on the weekly prices of soybean meal and corn in the years 2007-16. Results and Discussion: The results indicate that an Asian option is cheaper than a European simple option. Increase in asset prices, increase in asset price volatility and increases risk-free interest rate, increase the price of call option. By reducing the remaining time to maturity (T), with other factors constant, the value of an option is reduced. The hedge ratio for soybean meal is equal to 0. 69 and 0. 81 for corn, which means that in order to reduce the income fluctuations due to changes in the price of soybean and corn, 69 and 81 percent of the products must be sold in future and option markets. Two methods of Monte Carlo simulation and binomial tree model were used to determine the price of Asian option whit fixed strike for soybean meal and corn were 12. 5 and 9. 2, respectively. The results indicate that the control variate in variance reduction Monte-Carlo simulation method has a very good performance and significantly reduced the variance. Increase in asset prices, increase in asset price volatility and increases risk-free interest rate, increase the price of call option. Conclusions: In general, it can be said that to adopt a proper position in an option, is necessary to consider all the variables affecting the price. In addition, according to the sensitivity of an option to each of these variables, it should consider a good strategy to hedge these contracts. The option is a good tool for risk management, but it is also associated with risks. In volatile markets where volatility is high, the value of options is changing rapidly. Therefore, risk managers should regularly review the value of an option and thoughtful strategies to update these changes, because perhaps once-profitable option other time is extremely unprofitable.