مطالب

The research on the Markowitz model and optimization of its portfolio using a variety of evaluation indicators and meta-beta-algorithms has always been the focus of attention of accounting and finance researchers. The results of studies carried out by various types of optimization methods are different in the Markowitz modified models. The purpose of this study is to measure the optimal portfolio and its corresponding return, with respect to the portfolio in the traditional Markowitz model, as well as to compare the position of the refining and petrochemical companies versus stock market outperformers, through integrating the operational criteria and the new indicators of liquidity using the genetic algorithm in the Markowitz model. Therefore, financial data related to the research variables for 35 cases of TSE-listed refinery and petrochemical companies from 2012 to 2016 fiscal years were extracted from Rahavard Novin database software and simulated by the genetic algorithm. The results show that returns on the stock portfolio optimized using the genetic algorithm and without considering the liquidity limitations and filters have a significant and positive difference with the return on the stock portfolios optimized with regard to the liquidity limitations and filters. Furthermore, the application of liquidity limitations and filters in the formation of optimal stock portfolios leads to a conservative increase in the choice of stocks (portfolio formation), which leads to a reduction in the risk and return of investment in such portfolios.

Today, random and intelligent risks have made supply management disruptive much more than before. Over the past decade, many supply network (SN) disruptions in oil and gas industry have been due to the deliberate risks posed by international sanctions. Undoubtedly, resilience in general and resilience of SN in particular has been a systematic approach for firms and organizations to deal with disruptions. This study aimed to measure, assess and compare the resilience of SNs in oil and gas companies based on mixed approach: Systematic Literature Review (SLR) and Complex Adaptive Systems (CAS). The statistical population of the study consisted of 11 subsidiaries of the National Iranian Oil Company. A robust systematic review of the literature was conducted to collect all the crucial components of supply network resilience (SNR) from 608 articles that ultimately resulted in 40 key factors based on the context-intervention-mechanism-outcome logic (CIMO-logic). Quantitative analysis was carried out in the upstream sector of 3 subsidiaries of Iranian Central Oil Fields Company (ICOFC) including South Zagros, East and West Oil and Gas Production Companies. The results demonstrated a relationship between components and their measurement in upstream companies. A further finding is that South Zagros Oil and Gas Production Company was more resilient than the other two companies.

Unlike many arbitrations, the arbitration procedure for price reviews in gas industry contracts is not based on allegations that one party has breached a contract or otherwise committed a legal wrong. Instead, arbitrators are asked to determine whether the economics of a contract has been changed in the market, and thus should be adjusted and, if so, to establish a new price formula. Due to the complexity of revision of gas prices, the gas experts have significant role in these arbitrations. Regarding the role of gas experts, gas price arbitrations have specific nature. In this article, the nature of these arbitrations is examined to establish whether they are arbitration or expert determination as one of Alternative Dispute Resolutions (ADR). As Iran has the second proven natural gas resources worldwide and is the third natural gas producer in the world, so, Iran- Turkey case will come under scrutiny in this article.

Technical and environmental challenges resulted from an off-design running condition of processes on a platform is an important issue. The weakness of strategies to stop or decrease the amount of the greenhouse gas emission production rate in the Persian Gulf is another important matter of concern which is intensively increasing. Recently, modern methods of energy generation from available renewable potentials near offshore platforms are suggested in the literature. Integration of renewable energy converters with offshore oil and gas platforms can solve both problems with machinery and environment to an acceptable extent. In this study, the economics of an offshore complex installed in the Persian Gulf is subjected to two different power generation systems. The first case defines the present condition in which the total power demand of the complex is supplied by burning the associated extracted natural gas on board the platform in its thermal power plant. The second case considers a wind farm located near Bardekhun in Bushehr province to be connected to the complex power network and shares its renewable source generated power with the platform. The economics and relative emission production of both cases are compared. Wind speed average and wind turbine power generation are considered having uncertainties. Monte Carlo Simulation (MCS) method is used to consider those uncertainties in outcomes. The second case is found obviously more beneficial however there are some conservative assumptions included due to a shortage of data and limitations which makes it more attractive.