جستجوی مقالات مرتبط با کلیدواژه « financial markets » در نشریات گروه « مدیریت »

This study investigates whether green supply chain management (GSCM)4 practices help companies to be resilient against the buffer effect in the context of COVID-195. Building on the instrumental version of stakeholder6 theory, companies implementing GSCM practices should build environmental skills and competitive advantage to cope with a crisis caused by supply chain disruptions. Our survival analysis, conducted on 5,696 firms headquartered in 35 countries, shows clear evidence that GSCM companies’ market prices recover quickly from the shock. Considering mounting pressure on environmental issues, this study documents the new benefits of GSCM for companies confronted with a global financial shock. By applying a large sample, the study has originality and implications for stakeholders, including investors, governments, and policymakers, to push firms to become more eco-friendly and resilient.

The insurance industry in every country is one of the most important financial institutions active in the financial markets, especially the capital market. In addition to providing security for economic activities, the industry can play a very important key and decisive role in the mobility and dynamics of financial markets and the provision of investment funds by providing insurance services. Although this industry leads to an increase in productivity in other economic sectors by smoothing the ways of investment, reducing investment and participating in the investment of technical reserves, but the growth and development of other economic sectors also strengthens and develops the insurance industry. Assessment of the research background shows that most of the research conducted in this field has examined the role of the insurance industry in the country's macroeconomic economics or evaluating the insurance penetration rate in the economy, but comprehensive research on the impact of the insurance industry on economic investment not caried out so far. Therefore, the present study seeks to fill the role and effect of this industry by filling this vacuum. Therefore, the purpose of this study is to investigate the impact of the insurance industry on investment in the Iranian economy during the period of 1357-99.

The present research is descriptive, analytical and correlational in terms of methodology and applied research in terms of nature. In order to investigate the impact of the insurance industry on investment in the Iranian economy by documentary method and by referring to the subject literature and research conducted in this field, an experimental model has been specified and by using statistical information collected for research variables for the period 1357-99 from databases (Statistics Center, Central Bank and Central Insurance of the Islamic Republic of Iran) At a constant price in 1390, The specified model has been estimated and tested using the method of Autoregressive Distributed Lags (ARDL) models and using econometric software Eviews 12. The error correction model (ECM) was used to investigate the short-term dynamics of the estimated model.

Due to the positive effect of the insurance industry on the country's investment capacity, which takes place through two ways of direct entry into financing and investment activities and indirect operation through the creation of certainty and facilitation of investment activities, the supervisory body and other insurance industry activists are required to improve the role of this industry as an investor and financier, Through increasing the share of life insurance in portfolio of the industry, in order to have more long-term resources at the disposal of the industry. Also, in order to promote the role of the insurance industry in order to create certainty environment and facilitate investment activities, the supervisory body and all the industry activists to launch and promote insurance fields such as commercial credit insurance, bond credit insurance, cash loan credit insurance, debtor's life credit insurance, sickness and accident credit insurance, accounts receivable credit insurance, involuntary unemployment credit insurance, property credit insurance, stock insurance, and bank deposit insurance.

Pensions are one of the pillars of social protection and therefore maintaining the financial stability of them is a challenge for the future. Although the investment of funds can significantly contribute to the financial sustainability of these systems, the problem is how they are invested and The importance of this issue has led countries and international organizations to establish study groups to study the issue of investing in social security funds. Therefore, this study provides a favorable model for investing of the Armed Forces Pension Fund in the Islamic Republic of Iran's financial markets, and due to the sensitivity of access to information in the military field, the factors affecting the investment of pension funds in the country's financial market were extracted by content analysis method and a focus group consisting of 10 experts who had at least five years of financial experience and investment in the country's financial market were examined. Finally, by prioritizing the Analytic Hierarchy Process (AHP) and forming a pairwise comparison matrix, we prioritized the identified factors. The results showed that favorable investment in the country's financial market will begin with the structural reforms of the fund, and in the meantime, maintaining the financial stability of the fund will be the most important factor affecting the model. Priority of the main factors affecting the fund's investment have been factors related to the structure of the fund, factors related to fund management, macro factors, laws and regulations, and finally factors related to the country's financial market, respectively.

Islamic finance includes all operations, services, as well as transactions that take place in the financial markets and are in accordance with the principles, rules and laws of Islam and the Holy Sharia. In the past, Islamic financing instruments may not have received much attention, but in recent years, special attention has been paid to the Islamic financial system, and not only Muslim countries, but also non-Muslim countries have used this efficient system, so that as predicted, The expansion of the Islamic financial market by 2024 will reach more than 3.5 trillion US dollars. The purpose of this study is a meticulous and accurate analysis of the concepts and principles of the Islamic financial system; hence, this research is an applied research of descriptive-analytical type. Therefore, in this study, the Islamic financial system is described as an efficient financial system based on Islam and holy Sharia and a dynamic solution for the economy in today's turbulent world.

The complexity of financial instruments and markets makes it difficult for investors to decide on the type of asset, so that investors are always faced with the problem of optimizing the set of assets in their decisions. Therefore, choosing the right investment portfolio in order to maximize profits is one of the main concerns of investors. With this statement, the purpose of this article is to compare the explanation and performance of the optimization problem and the predictive power of ARMA-historical simulation models and ARFIMA-Monte Carlo (one of the most established models in the world) in fund portfolio optimization ‌ is a joint venture. The statistical and sample population included data from selected funds traded on the stock exchange of selected member countries of the Federation of Asian and European Stock Exchanges (FEAS) between 2013 and 2019. The results showed that the ARIMA-value at risk (historical simulation) model has a higher efficiency boundary compared to the ARIMA-value at risk (Monte Carlo simulation). It also incorporates the Pareto frontier drawn by the PESA-II algorithm for the other model. To determine the significance of this difference, the performance of the Mann-Whitney test has been investigated. The results indicate that the ARIMA-value-at-risk-optimal portfolio Sharp criterion is better than the ARIMA-value-at-risk (historical simulation) criterion.

Since surviving on obligations to insurers and maximizing the benefits of the company is one of the most important goals of insurance companies, and on the one hand, the regulatory agencies of each country are trying to enact specific laws and regulations and managers by adopting precautionary measures and modern technical and financial strategies. The purpose of this study was to present an intelligent model for predicting financial empowerment in insurance companies as a decision support system.

In order to present a model of predicting the financial health of insurance companies by examining the background of 17 variables as predictor variables for predicting the class of financial wealth, extracted from reliable sources of central insurance site of the Islamic Republic of Iran during 2013-2017. In this study, first, the results of applying different prediction models based on artificial intelligence including: decision tree, neural network, nibbles were compared. Then, the ranking of predictive algorithms was evaluated.

The results of this study showed that the decision tree with 99% accuracy has the best performance in predicting financial ability, considering that the decision tree is a nonlinear cognition and mapping models and patterns of turbulence between goal and decision variables.

The accuracy of the decision tree model in predicting financial robustness is high and the model extracted using decision tree has high accuracy and capability in estimation.