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.
International oil and gas investment disputes constitute an important part of Investor-State Dispute Settlement (ISDS) system. Investment arbitration which considers as a prevalent dispute settlement mechanism in this area is under serious criticisms, since it endures huge costs, causes length of process and devastates the parties’ long-term investment relationship. In the recent years, possibility of applying Alternative Dispute Resolution (ADR) and hybrid dispute settlement mechanisms have largely discussed. Mediation-Arbitration (“ Med-arb”) ; is one of the hybrid and integrated dispute settlement mechanisms which embodies flexibility, non-judicial and negotiate-oriented benefits of mediation and finality advantage of arbitration simultaneously and in a single process ( not in separate processes). In this method, mediation is first attempted by the parties before arbitration could be started, If no settlement is reached during mediation phase, then the appointed neutral or mediator, will act as independent arbitrator(s) and proceed the case under the arbitration process and will render a binding arbitration award. In this method, if parties reach an agreement during the first phase (mediation process), they will not incur huge costs of lengthy investment arbitration. In this method, even If the first stage (mediation process) fails, since mediation process made the disputes more clarified and narrower, then the arbitration process is less lengthy and arbitration will be proceeded more efficiently. Moreover, both investors and host- states in oil and gas investment area, do have strong ambitions to maintain the investment relationships. These goals are achieved better via adopting med-arb proceedings.
Supply chains have experienced rapid growth in recent years. Focusing purely on economic performance to optimize costs or return on capital can no longer guarantee development or sustainability in the chain. Hence, the concepts of green SCM and SSCM emerged to emphasize the importance of social and environmental concerns along with economic factors in supply chain programming. Using the SD method and considering KM , this study investigates the variables related to this topic and the variables of sustainable supply chain management and it determines the relationships between these variables and their impact on the research purpose. To achieve this, first, previous studies are reviewed, and the relevant variables are extracted and finalized according to the experts. Next, SD modeling is designed and various scenarios are defined by changing the effective values of the system. Eventually, several policies are presented to achieve the optimal situation. The optimal values for the ten main influential variables are extracted according to the expert opinion and the effects shown in the model are determined by these changes.
Companies need to exactly manage their assets to balance performance, risk, and cost. The ability of an equipment to provide a certain level of performance is influenced by its design, utilization, deterioration, and its life. On the other hand, in order to obtain the desired level of performance and reduce risk, proper planning of maintenance activities during the period must be done. To manage this issue, organizations must develop a suitable method for their assets from the acquisition stage to the disposal to obtain the required processes and, ultimately, to earn the desired profit. In this study, considering Pipe line as a case study and identifying the LCC, risks and three indicators includes of reliability, availability and maintainability as KPIs. They were weighted by using the opinions of eight expert and DANP method. The final weights of LCC, risk and KPI Respectively are: 0.269, 0.301 and 0.429. Considering different strategies in each phase of the asset life cycle, different scenarios described for the equipment life cycle as follows: 1)Buy- RCM- Replacement 2)Buy- RCM- Overhaul 3)Buy- CBM- Replacement 4)Buy- CBM- Overhaul 5)Buy- TPM- Replacement 6)Buy- TPM- Overhaul. Finally, based on the gained expert’s viewpoint from questionnaire and MOORA technique to rank the scenarios the desired scenario (Buy- TPM- Replacement) was selected.
It is generally believed that macroeconomic and financial performance in oil exporting countries is interlinked to oil price movements. Regarding that assumption, the present study aims to examine the impact of oil price movements on bank nonperforming loans (NPLs) ,as a criterion for evaluation of bank credit risk, by applying the Generalized Method of Moments (GMM) on data from 18 Iranian banks data over period 2006–2017. The result of the estimated model indicates that there is a significant relation between fluctuations of oil price and bank nonperforming loans; accordingly, any decrease in the price of oil will result in an increase in bank nonperforming loans. Also, in order to have comprehensive assessment, economic and bank specific control variables were used in the model. Findings show that the NPLs ratio increases as economic growth decreases and exchange rate and real interest rates rise. Among bank specific factors, equity ratio as a criterion for efficiency and loan growth has a negative effect on NPLs, but by raising bank industry concentration, credit risk and financial stability can be threatened. Thus, the reliance of oil rich economies on oil incomes leads to the linkage of oil prices, and macroeconomic and financial performance. Therefore, the result of this study will be useful in adapting and diversifying macroeconomic policies in the face of drastic changes in oil prices and mitigating its adverse effects.
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.