جستجوی مقالات مرتبط با کلیدواژه « سرایت ریسک » در نشریات گروه « مالی »

The Tehran Stock Exchange and its industries have contributed to the risk of tail events occurring in recent years, such as the U.S. and European sanctions against Iran and the COVID-19 pandemic. Industries affected by these crises have become more connected. Crisis episodes have raised risk spread within the financial system. Whenever an impulse hits an industry, it is quickly transmitted to other industries through a contagion mechanism, which ultimately causes fluctuations in the whole system. Stress situations suggest that promoting financial stability should be a priority for regulators and academic researchers. For this purpose, analyzing the systemic risk contagion and tail risk interconnectedness among industries is important to enhance the stock market’s safety and design the related macroprudential policies. The stock market plays a vital role in the financial system by allocating resources and facilitating price discovery. However, Tehran Stock Exchange is a completely immature market, which greatly increases the possibility of risk contagion to the entire market. For example, the collapses of stock price bubbles in the Tehran Stock Exchange over the past two decades resulted in huge losses in the net worth of investors and was followed by a recession. The financial turmoil highlights the importance of measuring systemic risk in the stock market.Interconnections among industries in a network imply that a shock in one industry may lead to risk transmission between related industries, causing risk contagion to the entire stock market. Therefore, investigating the risk interrelationships between industries and identifying the systematically linked industries is essential to effectively predict the systemic risks and control risk spread in the stock market.This study analyzes the risk interdependence among the main industries listed on the Tehran Stock Exchange. In particular, the risk contagion effects among industries are analyzed under extreme market conditions.

The present article is to investigate the contagiousness of systemic risk in Iranian financial markets. In recent years, markets, i Due to the fact that information is not evenly distributed among the players in the market, this asymmetry causes the transmission and transmission of shock from one market to another In this dissertation, simultaneous multi Garch models and co-variance changes are used, method for identifying seriality and its effects in institutions.each other in the event of various internal and external shocks and creating financial stability, it is necessary to examine the contagiousness of risk between markets.In general, it can be said that the relationship between financial markets can be considered as a strength and can also be explained as the possibility of crisis transmission or systemic riskThe purpose of this study was to investigate the contagiousness of systemic risk in Iranian financial marketsThe variables studied in this study included internal and external shocksexchange rates, oil pricesand information about them during the years 98-97 from the stock exchanges and securities in the target markets and the financial system of the largest oil holding company, Was collected. the variables were calculated and processed using Excel software, and then Ives software was used for statistical analysis of the obtained information and achieving a reliable result.Friedman test, the country's capital market sector with an average rank of 2.9 has the highest share of systemic risk and the banking system with an average rank of 1.8 has the lowest share of systemic risk

In this research, it is attempted to present a framework for estimating and predicting systemic risk in Iran capital market using the marginal expected shortfall approach (MES), which has recently been considered in systemic risk literature. On this basis, MES as a systemic risk measure, will be analyzed in terms of assumptions for market and firm returns as a function of mean, volatility, correlation, and tail expectations and its components will be measured using an ARMA-GJR-GARCH-DCC framework and a nonparametric tail expectation estimator. In this way, a weekly panel will be created from the company's MES. On the other hand, the systemic risk is built up in a period that looks calm and low fluctuations, and is accumulated until activation. In other words, systemic risk potential increases as fluctuations decrease. In this study, it was attempted to predict systemic risk by taking advantage of the panel structure of the data and the relationship between MES and firm-specific variables that are available in certain sections.