مجله راهبرد مدیریت مالی
سال نهم شماره 1 (پیاپی 32، بهار 1400)

This study investigates the effects of external financing requirement on corporate governance index and the value of companies listed on the Tehran Stock Exchange. This research in nature is a descriptive - correlation research. The sample consistes of 180 companies during 1392 to 1396. The hypotheses tested by multivariable regression panel data. The results show that the corporate governance have an insignificant effect on the companys’ value. However, the need for external financing has significant effects on both the value of the companies and corporate governance index. Based on the results, it is recommended that business managers seriously seek to enhance the quality of corporate governance in controlled entities if they seek to influence the factors that enhance capital structure. Capital structure selection is optimized. Based on the results, it is recommended that business managers seriously seek to enhance the quality of corporate governance in controlled entities if they seek to influence the factors that enhance capital structure. Capital structure selection is optimized.

Optimal asset allocation affects portfolio performance and decreases investor risk. In this regard, the most widely used models include asset allocation with equal-weighted and minimum variance. These models from the very beginning have faced much criticism. After the financial crisis in America in 2008 equal risk contribution of asset allocation model was presented where special attention is the risk factor. In equal risk contribution (ERC), the risk contribution of each portfolio is equal. In this paper, the performance of these three strategies in terms of risk, return, Sharp ratio, diversification in terms of weight and risk, maximum drawdown, turnover, cost of transactions, risk in financial crises and cumulative returns are compared with each other. Samples included weekly data of 25 main indexes in Tehran Stock Exchange from 1385 to 1395. The results of this study show that equal risk contribution of asset allocation strategy in most cases performs moderately well and in some cases performs better than the other two strategies and the investors and portfolio managers have more reliable performance by applying it.

The customer concentration can increase the cash input flow risk, the need to additional cash holdings and the risk of corporate future financial crisis, which could affect cash holdings level and cash holdings adjustment speed. The purpose of this study was to examine the effectiveness test of customer concentration on cash holdings adjustment speed in listed companies in Tehran Stock Exchange. In this regard, have been investigated 140 companies (980 firm-year observations) accepted in the Tehran Stock Exchange during the period from 2011 to 2017. In order to test the hypotheses of the research, has been used multiple linear regression model using combined data (panel method). The results of this research indicate that the customer concentration on cash holdings level and cash holdings adjustment speed hase positive and significant effect. In other words, in companies to major customer, cash holdings level and cash holdings adjustment speed have been higher. These results explainer the importance and effectiveness of the role the company major customers in increasing the cash holdings level and cash holdings adjustment speed.

This study seeks to investigate the existence or absence of independence in return series in S&P index of the New York and 11 different indexes in Tehran Stock Exchange and their adherence to the random walk model in two Low volatility and high volatility regimes using the Markov switching model. Research sample included daily price information of 9 different industry indices of the bank, cement, oil products, machinery, chemicals, automobiles, sugar, food but sugar, metal minerals, index of 50 Top Companies and price index (TEPIX) in Tehran Stock Exchange Market for the period from 03/25/2011 to 03/19/2019. The results of the Markov Switching and Arima model showed that only in the high volatility regimes of the S&P index of the New York Stock Exchanges, with a durability of 32 percent, and the index of oil products in Tehran Stock Exchange with a 6 percent survival, the Arima model was not significant and in the rest The cases of the Arima model became significant.

IPOs acknowledged as an important and continuous event in stock markets. A lot of research investigated why do company go public? How to price a new company? And the abnormal return of IPOs in the short and long term. In another aspect, we can consider IPOs as an economic event or even critical news and examine its effects on the existing companies' return. In this paper, we attempted to investigate investors' behavior around an IPO and the competitive effect of IPO's in the Tehran Security Exchange using event study methodology. For this purpose, we classified 235 IPO for 14 years based on their size, industry, P/E, and B/M. The results indicate that investors consider the big size and low P/E IPOs as a negative event on the existing portfolio. We also find that the initial filing of an IPO has a negative price impact on existing firms in the same industry.

The purpose of this article is to predict impending financial distress of the listed companies on Tehran Stock Exchange (TSE) and Iran Fara Bourse (IFB) using a wide range of features including accrual accounting variables, cash-based accounting variables, market-based variables, corporate governance mechanisms, and macroeconomic indicators. The final sample includes 421 firms leading to 3,670 firm-year observations. The prepared data, was then split into a train and test data set using a 70/30 ratio. In this research, various data pre-processing machine learning techniques i.e., Z-score standardization, one-hot encoding, stratified K-fold validation combined with feature engineering are applied to improve classifier performance. Stratified K-fold cross validation method, (with k = 5) was used for estimation of model prediction performance during training phase. During the training phase, hyper-parameter tuning of a model was carried out using a grid-search. Furthermore, a cost-sensitive meta-learning approach in conjunction with the proposed imbalance-oriented metric i.e., F1 score were used to overcome the extreme class imbalance issue. Based on the experimental results, the tuned Support Vector Machine (SVM) model achieved a f1-score, MCC, recall and precision of respectively, 55%, 56%, 78% and 43% on the training set. Finally, the proposed model was tested on the hold-out test set which resulted in a f1-score, MCC, recall and precision of 50%, 50%, 68% and 40%, respectively.

Flexibility can be seen as a link between domestic and foreign borrowing capacity, and through accumulated internal funds enabling the company to make growth choices at the right time and in a competitive manner, and do projects with positive net present values. But the existence of Principal-principal Conflict due to separation of ownership from management can affect this effectiveness. The purpose of this study is to investigate the effect of financial flexibility on the intensity of investment and dividend with emphasis on role of principal-principal Conflict in the companies admitted to Tehran Stock Exchange. In general, the use of a sample (102 companies) from Stock Exchange companies for the years 2011-2017, based on linear regression, suggests that the flexibility financial composite index has a significant positive effect on investment propensity and dividend policy. And the interactive effect of flexibility financial composite index and Principal-principal Conflict composite index have a moderating effect on investment propensity and dividend policy and has a significant negative effect on the investment propensity and dividend policy.

Measuring credit risk and estimating the likelihood of companies failing is one of the most important challenges in the credit sector. Structural and non-structural models are the two main frameworks for estimating default risk and credit risk. But each of these models has its strengths and weaknesses, and it seems that combining these two frameworks and providing a hybrid model can provide a more accurate prediction of companies' default risk. In the present study, a hybrid model has been used to measure the default risk of listed and over-the-counter companies in the period between 2007-2017, which has been transferred to the basic market according to the laws of the Iranian capital market. First, the Merton model (structural models) was used to measure the risk of default of these companies, and then the results of this model were compared with the Z-Altman model (from non-structural models). Then, by regression analysis of different financial ratios, significant variables were identified and Morton's and Z-Altman models were statistically and comparatively compared. The findings show that the hybrid model offers a more accurate prediction of the risk of default than structural and non-structural models. By entering the results of each of these two models into the hybrid model, the statistical power of the hybrid model increases. Therefore, using a combined model will help banks and credit institutions to provide resources to healthier companies with less risk.

Capital structure as the most important and effective parameter on the orientation and valuation of the firm in the capital markets has been considered. Given the lack of comprehensive research and case study in this field, the aim of this research is the determination of the dominant pattern of the capital structure in automotive and parts industry. The research period was 2006-2016 and in the mentioned industry, 26 companies were selected as statistical sample. The pooled/paned regression models were applied to analyze of research data in econometric software EViews 9. In the study, three criteria such as book leverage (LEV1), market leverage (LEV2), and long-term leverage (LEV3) were applied to determine of capital structure. Also, variables such as DPS to EPS (DPO), return on equity (ROE), business risk (BR), asset structure (TANG), liquidity (LIQ), market to book value (MB), company size (SIZE), non debt tax saving (NDTS), tangible assets to debt ratio (TADR), debt tax shelter (DTS), and interest coverage (IC) were exerted to measure of effective factors on capital structure based on different theories. Findings indicate that in the automotive and parts industry, pecking order, extreme management optimism, and market timing theories have been the dominant patterns in Iran's capital.

The purpose of this research is to compare the four indicators of earnings quality that use only accounting data to determine the quality of profit and determine their impact on the degree of credit risk of listed companies in Tehran Stock Exchange. For this purpose, 156 companies were gathered between 2008 and 2017. In this connection, 20 financial indicators were used to determine the risk of credit and then its ranking by data envelopment analysis method. The relationship between the indices with the credit rating of each company was also tested and confirmed. Also, four indicators of earnings quality including sustainability and predictability features, profit / cash relationship, accruals, and, finally, earnings response coefficient and adjusted earnings response coefficient are used. First, the relationship of the 20 financial ratios applied with the credit rating determined by the data envelopment analysis method was verified in the form of a regression model tested and validated by the model. Then, the relationship between the four indicators of earnings quality with the credit rating of each company was tested. The results show that companies with lower credit risk have higher earnings quality. Also, with a decrease in the quality of profit indicators, their credit risk will also increase. From this research it can be concluded that there is a significant relationship between credit risk of listed companies in Tehran Stock Exchange and their main indicators of earnings quality. In this research, credit rating is the amount of credit risk that is calculated and ranked by data envelopment analysis method.