فرخنده جبل عاملی

Sanctions increase managers' motivations to manage profits and the accumulation of bad news due to their negative impact on corporate profitability and cash flow. According to Jin and Myers (2006), this issue increases companies' stock price crash risk. The higher probability of stock price crashes indicates a stock price overvaluation. As a result, the expected return on such shares will be low. The current paper used the softmax model to calculate the probability of stock price crashes and the expected return calculated by the Fama-French three-factor model. The sample used in this paper includes 80 import- and export-oriented exchange companies from 2008-2021. The results of this paper indicate a positive and significant relationship between the sanctions variables and the probability of stock crashes. So, sanctions cause an increase in the accumulation of bad news and information asymmetry between managers and investors. The second part of the paper's results indicates a negative relationship between the probability of stock crashes and the expected return on the stocks in the Iranian capital market. Therefore, investors have relatively good analytical skills in the Iranian capital market due to its shallow depth and infrastructure problems. The results of this paper can be used in portfolio management to select stocks with a lower probability of crash and higher return.

The Unconventional Gas Production Revolution in the US has ushered in new opportunities for American petrochemical companies, granting abundant access to gas resources and fostering business growth. Consequently, prominent global petrochemical firms have made substantial investments in the United States' petrochemical and chemical industries. Simultaneously, the surge in gas production from unconventional reserves in the US has led to considerable growth in the country's petrochemical output. To address this crucial topic, we conducted a comprehensive time series analysis, investigating the long and short-term relationships between oil and polyethylene prices in the US during the shale gas development phase. Employing an autoregressive distributed lag (ARDL) model for the period spanning from January 2013 to December 2017, our research findings reveal that, in the long run, there exists a positive and significant influence of the oil price variable on polyethylene prices. However, in the short term, no discernible impact on the polyethylene price variable was observed. Interestingly, the analysis also indicates a unidirectional causal relationship, with oil prices influencing polyethylene prices. This finding suggests that despite the divergence between oil and gas prices, oil remains a crucial determinant of petrochemical product pricing. The results underscore the significance of shale gas development and its impact on the petrochemical industry. As the US continues to experience increased gas production, comprehending the intricate relationships between oil, gas, and petrochemical prices becomes imperative for companies' strategic decision-making and policymakers alike.

Because colonial governments disrupt financial markets to exert political pressure on target countries. For this purpose, in this study, the effects of sanctions on the economic conditions of countries are examined. The criteria (sanctions) examined in this study were placed in international, property, commercial, knowledge, oil, finance and individual groups. These criteria are the sanctions imposed on Iran in the period 1984 to 2020. The method used for analysis is a combination of the Fuzzy Decision Making Trial and Evaluation Laboratory technique and sanctions intensity model. The results of this study indicate that in the introduced model, international sanctions are the most effective. These sanctions are most effective when the sanctioned government is in business. Thus, international sanctions have the greatest impact on the government's trade disputes (Commercial sanctions). International sanctions on a country like Iran, which trades in oil and sells its oil, affect oil sanctions as much as they affect Commercial sanctions, but less on individual sanctions. Finally, the results of the model indicate that the intensity of sanctions was at its peak between 2010 and 2015, with the greatest effect being due to international sanctions.