نشریه تحقیقات مالی
پیاپی 58 (تابستان 1399)

Risk management is one of the most important areas of study in finance, and its vital role in the field has attracted the attention of managers and investors in in various sectors of the industry. Especially in recent years, with the onset of financial crises, the importance and necessity of accurate studies in this area has doubled. The main purpose of this study is to provide a model for a more accurate measurement of equity portfolio risk.

To conduct this research, adjusted closing prices of a sample of thirty listed companies have been used. CVaR is the main model and four other models are formulated using different methods of variance modeling. The first method calculates conditional value at risk using constant variance and in the other three methods, variance is modeled on GARCH, E-GARCH and T-GARCH approaches.

Ultimately, the results have been evaluated using appropriate statistical tests, namely paired t test and Wilcoxon signed rank test. The results obtained from both tests suggest that the method used to model variance has a significant effect on attaining a better optimal portfolio.

Considering results of the research, which approve the tested hypothesis, one can conclude, taking into account the heteroscedasticity in Iranian capital market, would result in a better optimized portfolio. Moreover, the results illustrated that the use of CVaR model, for risk measurement, rather than previously used traditional models, can be effective in improving the performance, in optimizing stock portfolios, significantly.

This study is aimed at measuring how fast adjustments are made on capital structures, for various industries, and investigating the impact of macroeconomic conditions, in terms of recession and boom, between 2011 and 2017.

In this research, target capital structure has been calculated based on the concept of debt capacity. Variables including market excess return and real gross domestic product (real GDP) have been selected as a proxy for financial sector and real sector to measure economic status. Hodrick-Prescott filter has been used to determine the periods of boom and recession.

The speed of capital structure adjustment (depending on its sign and magnitude), could be classified into: 1) approaching, 2) moving away, 3) approaching and then moving away from the targeted capital structure. The results show that the capital structure of each year is adjusted toward the target. The boom and recession of the financial sector and real economy have no effect on the capital structure adjustment speed. Subsequent studies showed that the capital structure in the years 2011, 2012, 2013, 2016 and 2017 for various  industries, including of mining, electrical, computer, engineering, non-metallic minerals, refineries and petrochemicals, pharmaceuticals and metals, have been approaching the target.

Since the speed of adjustment of the companies is between 0 and 1, the capital structure of each year is approaching the target capital structure. Investigating the impact of boom and recession of sectors also showed that the macroeconomic environment had no effect on adjusting the capital structure of companies.

Given the importance of start-up companies valuation for investors and entrepreneurs, this study seeks to determine the value that balances their expectations through an appropriate valuation. As a result, it is expected that a more accurate valuation will be obtained by taking into account the flexibility available to start-up companies. This scan be done through the real option method, as well as by considering the effect of non-normal distribution of cash flows and agency costs.

In first step, the real option method is applied to value the startup companies. Then, Skewness and Kurtosis Adjusted Black Scholes Model is used, while considering the non-normal distribution of cash flows. In the next step, the valuation of the startup companies is done in the presence of agency cost. And finally, the equilibrium point of investor and entrepreneur is found by creating the Edgeworth box.

Using data from ten startup companies in investment banks which have been valued by the investment banks, it is indicated that using the ultimate research model with the purpose of determining the equilibrium value by the Edgeworth box, will result in statistically acceptable values.

The final model presented in this research taking into consideration the two factors of non-normal distribution of cash flows and agency costs in calculating the value of real option as the preferred method in valuing start-ups, which includes flexibility in decision making, along with the calculation of the equilibrium point of entrepreneur and investor using the Edgeworth box has led to a good equilibrium value without the need to apply different discount rates in the different startup companies.

The systemic risk is the risk of a crisis in the financial sector and its transmission to the economy. Due to the importance of social damage caused by the financial crisis, it is necessary to pay attention to the systemic risk and its factors. The purpose of the present study is to investigate the effects of strength of corporate governance mechanisms on systemic risk for financial institutions listed on Tehran Stock Exchange.

In order to study the subject, after extracting the data of 42 financial institutions listed in the Tehran Stock Exchange during the period 1390-1394, combined data and multivariate regression model are used to test the research hypotheses. The strength of corporate governance is scored by applying TOPSIS technique based on the five criteria that as follows: percentage of institutional ownership, major shareholders and managerial investors, board size and the percentage of non-executive members of the board. The systemic risk is measured bases on the marginal expected shortfall (MES) and the expected shortfall of capital (SRISK).

The effects of strength of corporate governance mechanisms on (MES) and (SRISK) as two indicators of systemic risk is not accepted, because it has a significant level above 5%. Also, the significant level of control variables (Size) and (Capital Ratio) indicates that larger financial institutions (with higher assets) and higher capital ratio, have greater role in the systemic risk.

The research findings show that the strength of corporate governance mechanisms does not have significant effect on the financial institutions' systemic risk.

This research is aimed at investigating the impact of internal and external corporate governance on the relationship between information asymmetry and investment efficiency.

For the purpose of analyzing the research hypothesis, 106 publicly traded firms on the Tehran Stock Exchange, between 2009 and 2018, have been selected using the elimination method. The analysis of the hypotheses was carried out by using a multivariate regression model with panel data method and employing the fixed effects approach.

According to theoretical bases and research finding, information asymmetry has a negative and significant relationship with investment efficiency. Also, corporate governance variables, in both external and internal governance, and both variables of information asymmetry and both dimensions of corporate have a positive and significant relationship with investment efficiency.

The results of the research show that the existence of asymmetric information and ambiguity in financial information may lead to inefficient investments. Hence, one of the ways to reduce information asymmetry and increase investment efficiency is enhanced corporate governance quality. According to the existing principle, current expectations, and the findings of this study, the interaction of information and corporate governance have a positive and significant relationship with investment efficiency. This means that in the condition of information asymmetry, the existence of internal and external corporate governance reduces inefficient investments and urges managers to make optimal and efficient investment decisions.

After beginning of stock markets liberalization in mid-1980, integration of these markets into global markets is increasing. The countries are attempting to attract international investors to divide their portfolio risk, increase liquidity level and promote informational transparency and hence improve stock market efficiency. This study investigates the effects of financial liberalization on stock market informational efficiency in developing economies, during 2000-2016.

With regarding to informational efficiency level in economies with developing characteristics is time-varying because of benefit from their investor experiences and increase of informational access and quality. In order to, we applied a state space model with GARCH effects to determine the degree of informational efficiency during time for any selected countries. In continue, we use panel GMM model that allow measuring and assessing the impact of financial liberalization on the informational efficiency.

The results of state space model realized the weak efficiency hypothesis in selected countries. In other words, the past returns do not contribute much to anticipate future returns, but it affected by macroeconomic, external shocks and political events. Also, the results of GMM model indicate that financial liberalization significantly (of course tiny) improves the degree of informational efficiency. Likewise, we found that information variable (turnover) and macroeconomic variables (inflation rate and exchange rate volatilities) would strengthen significantly informational efficiency in developing countries.

This research contributes to improving informational efficiency in developing economies, this is necessary to implement financial liberalization process as well as improving macroeconomic circumstance and declining exchange rate volatilities.

This study is primarily aimed at designing a tax risk assessment model for companies listed on the Tehran Stock Exchange. This research is also aimed at investigating the impact of corporate tax risk on capital asset pricing models and comparing the explanatory power of multifactor capital asset pricing models in relation to corporate tax and a firm’s value.

This research is an applied and analytical-explanatory. The statistical population of this study have all been selected from companies listed on the Tehran Stock Exchange between 2011 and 2017 and the statistical sample has been selected using systematic elimination method of 103 companies.

In the study, a model for the assessment of tax risk has been presented. In this model, the quantitative and qualitative variables that had the greatest impact on tax gap were identified and the tax risk was ultimately obtained from the remainder of this model. The results of the study showed that tax risk, in all four models of capital asset pricing, has a significant and negative impact on the value of the company. Another result of the study found that the five-factor pricing model is better able to explain the relationship between tax risk and a company’s value.

Understanding the impact of tax risk on a company’s value helps shareholders to make the right decisions when national tax laws are revised. This is mainly because each of these decisions will have different effects on the company's value and its stock price and ultimately the shareholders' wealth and their satisfaction with the company.