مجله مدیریت دارایی و تامین مالی
سال یازدهم شماره 1 (پیاپی 40، بهار 1402)

In this study, systemic risk index (β) was measured and decomposed by using the extreme value theory in the banks listed in Tehran Stock Exchange (TSE) during 2013-2021. This index was divided into two dimensions: total bank risk (tail risk) and link of the bank to the system during the financial crisis (system linkage). Using autoregressive distributed lag (ARDL) regression, the relationships between systemic risk and its dimensions with the characteristics of the banks and the relationships between their economic value-added (EVA) and various financial risks, including systemic risk, were calculated. According to the results, Post-Bank, Tejarat, and Saderat banks imposed the highest systemic risks and Karafarin and Eghtesad-e Novin banks imposed the lowest systemic risks, respectively. The results showed that with increasing the bank size, the systemic and tail risks that are specific to each bank decreased and the systemic linkage increased. There was a positive and significant relationship between the EVAs of the banks and their ratios of regulatory capital to credit risk-weighted assets. Also, there was a negative and significant relationship between the EVAs of the banks and their ratios of core capital to operational risk-weighted assets, net sustainable financial resources, and interest rate risk variables.

Environmental uncertainty and intense competition in global markets have made petrochemical companies and complexes face many challenges and strategic risks. Strategic risks are risks that can unbalance the strategic system and have a significant negative impact on the industry. The purpose of this research was to design a model for identifying and prioritizing financial strategic risks, which prevented realization of strategic goals and affected all components and dimensions of the petrochemical industry. For this purpose, the primary data were first collected through semi-structured interviews with 14 experts and synthesis of previous studies. Then, using thematic analysis, the data were classified into the 3 layers of basic, organizing, and inclusive themes. Using the themes of the organizer, which were risk of financial sanctions, risk of effective financial decisions of the government, credit risk, liquidity risk, financial risk of the production area, macroeconomic risk, insurance risk and risk coverage, and product market risk and competition, a structural-interpretive modeling questionnaire was designed for high (strategic) management risks and the relationships between the risks were evaluated and investigated by asking the opinions of 15 experts from the petrochemical industry. In the end, the risk of financial sanctions as the most influential variable at the most basic level was introduced in the final model that showed the levels of financial strategic risks in the petrochemical industry.

The possibility of repurchasing the investment units issued by the fund is a distinctive feature of open-end mutual funds, which exposes these funds to liquidity risk. The main challenge of liquidity management of these funds is providing cash during a crisis and also facing more than expected redemption demands. In such a situation, the fund may not be able to sell assets quickly enough without the experience of offering high discounts. Being pressured to finance and sell assets will have an adverse effect on the price of the fund's assets and similar assets in the market, which can lead to a downward spiral at the price of these assets, leading to the invasion of other funds with similar assets and having an adverse effect on the whole market. Therefore, integrated liquidity risk management is vital for these funds and the entire financial system. The current research aimed to achieve a coherent framework in the field of monitoring and managing the liquidity risk of open-end mutual funds. For this purpose, grounded theory was used through various coding stages. In addition, the Delphi strategy was used for the elites’ opinions, and finally, a framework for monitoring liquidity risk management, including policies, infrastructures, and methods, was presented.

In this paper, analysis of the sensitivity of the bankruptcy index to financial variables during the firm life cycle was investigated using Monte Carlo simulation. To measure bankruptcy risk, Altman's modified bankruptcy model was used. To simulate score ​​of Altman's modified model, the probability distribution of each index of Altman's modified model was determined based on the historical data of the listed firms listed in the Tehran Stock Exchange (TSE) during the years 2011-2021. With the help of these distributions, 10,000 items for the bankruptcy index were simulated in each life cycle. The results of simulations showed that the bankruptcy index had high and low sensitivities to the indicators of working capital to total assets (X1) and accumulated earnings to total assets (X2) compared to the indices of earnings before interest and taxes to total assets (X3), the book value of equity to book value of total liabilities (X4), and sales to total assets (X5) in all stages of the firm life cycle, except for the decline stage.

Companies, depending on their specific characteristics, face different capital structure adjustment costs and, as a result, move to their target leverage at different speeds. The purpose of this study is a comparative investigation of factors affecting the speed of capital structure adjustment among service companies and manufacturing industries listed on the Tehran Stock Exchange. To test the hypotheses, the information of 137 companies listed on the Tehran Stock Exchange in the period 2013-2019 has been used. After calculating the research variables, a panel data regression model was used to test the hypotheses. To choose between the methods of regression data models the Limer F test was used. The panel data model was selected and the results of the Hausman test also confirmed the use of the fixed effects model. The results of the study hypotheses showed that capital structure adjustment speed of manufacturing industries is larger than service companies. The estimated speed is 73% for service companies and 85% for manufacturing industries, which indicates the high speed of adjustment which can reduce the probability of financial crises in the economy.

Investor sentiments are related to investors' subjective beliefs about cash flows and investment risks. The present study was conducted to investigate the impact of the company's financial risk on the risk sentiment of annual reports in companies listed on the Tehran Stock Exchange. To test the hypothese, 130 companies were selected as the sample between 2008 and 2021 and analyzed using the regression method of static and dynamic panel data. To evaluate the company's financial risk, the criteria of financial leverage, company size, and current ratio were used, and the frequency of vocabulary method was used to measure the risk sentiment of annual reports. The results showed that the variables of financial leverage and current ratio have a positive and significant effect on the risk sentiment of annual reports. However, the size of the company has a negative and significant effect on the risk sentiment in annual reports. The results also showed that in addition to the risky tone of the words and sentences in the description of the financial statements, the numbers and figures of the financial statements also affect the investors' risk sentiment.