مجله مدیریت دارایی و تامین مالی
سال هشتم شماره 4 (پیاپی 31، زمستان 1399)

Most of the problems of banks can be attributed to mismatching in the balance sheet, revenue-expense gap, and unbalanced cash flow. The main aim of this research is to investigate executive solutions allowing for solving these problems through financial restructuring in Iranian banks. For this purpose, a general picture of the problems of the banking system is firstly drawn via seeking previous studies and the information provided by the Central Bank of Iran (CBI). Secondly, by an in-depth study on internal and international resources, the initial solutions are identified. Thirdly, by a two-stage Delphi approach, the agreements about those solutions are obtained. In this study, half of the experts hold a Ph.D. degree and the rest have an MS degree, with an average of around 18 years of experience.   Ultimately, a final list of 21 solutions is extracted and classified in 5 sections: 1) clarifying the circumstances of unsafe banks which have considerable overdraft from the central bank of Iran; 2) improving the regulatory and supervisory system of the Central Bank; 3) selling the excess assets of banks and improving their branch networks; 4) lowering the long-term liabilities of banks; and 5) enacting efficient rules and regulations.

Financial statements are of substantial significance to investors and other players in financial markets. Yet, these statements are sometimes misinforming and misleading. Thus, a potentially intricate issue for financial decision-makers is the prediction and detection of fraudulent financial statements.

This research investigates the relationship between earnings management and fraudulent financial statements in Firms, listed in Tehran Stock Exchange in order to help identify fraudulent financial statements in the time interval from 2009 to 2016. In other words, the objective of this study is to evaluate the ability of the popular discretionary accrual models to detect fraudulent financial statements. For this mission, 189 companies (21 fraudulent companies and 168 non-fraudulent) are selected as the research sample. The data mining methods employed in this research are Decision Trees (REPTree), Artificial Neural Networks (ANNs), and Bayesian Networks. We evaluate the ability of 7 measures derived from the extant discretionary accruals models to detect the existence of fraudulence.

The obtained results indicate that among all data mining methods, the Decision Trees method and among all accruals models, the Modified Jones model with book-to-market ratio have the greatest relationship with fraudulent financial statements.

This study is the first to examine the issue of time-varying long-term memory in the Tehran Stock Exchange, using a new efficiency index through a rolling window technique. To test the robustness of the results, this estimation technique is repeated with time windows with 5-day shifts. Furthermore, the wild bootstrap versions of the Automatic Portmanteau test (AQ) and the Automatic Variance Ratio test (AVR) have been performed with 14- and 5-day shifts.

The sample employed in this paper consists of daily observations on the Tehran Stock Exchange Index (TEPIX), covering the period from December 2008 to October 2019, making up a total of 2621 observations. The TEPIX series are collected from the Rahavard Novin software. The hypotheses are analyzed by Excel, EViews, R, and MATLAB software.

The findings show that in the Tehran Stock Exchange the estimated values of the generalized Hurst exponents (GHE) for all windows with 14-day shifts are over the efficiency indicator 0/5. Therefore, a kind of long-term memory exists on the Tehran Stock Exchange. Moreover, a high degree of inefficiency ratio is observed in the market. Furthermore, the Tehran Stock Exchange does not become more efficient over time. Finally, the results from the time windows with 5-day shifts as well as wild bootstrap versions of the AQ and AVR tests with 14- and 5-day shifts indicate that the previously-mentioned empirical results are robust. The findings from the study provide important implications for investors, portfolio managers, and policy-makers.

Open limit order book can be used as a tool to enhance transparency and price discovery in financial markets by showing the offered volumes and prices of buy and sell orders. In this study, we aim to answer two questions by examining the limit order book on  Tehran Stock Exchange: 1) Does the information in the limit order book have the predictive power for stock price movements in the short-term?; 2) Can increasing the public disclosure of the limit order book from three to five levels enhance price discovery?

For this purpose, three different regressions areused, each of which measures the volume and price information of the two sides of supply and demand in a different way and examines the ability to predict short-term behavior of stock price by this information.

The results show that the limit order book contains information about future short-term returns. Our results also indicate that increasing the public disclosure of the limit order book from three to five levels can enhance transparency and price discovery but it causes the marginal predictive power of additional levels to decrease.

One of the most important financial and managerial decisions of companies is determining the optimal amount of inventory needed for each period. The inventory of goods and commercial credit can be considered as one of the important items in supply chain management and as a source of short-term finance, respectively, which can be of great benefit to organizations if they are managed prudently. We investigated the effect of product inventory management and commercial credit on the stability of capital structure by using a dynamic combined data method with a generalized torque approach in 101 firms, listed in the Tehran Stock Exchange between 2006 and 2019. The results indicate that with increasing efficiency of inventory management, the stability of capital structure decreases based on the book and market leverage. In addition, based on the book leverage, when business credit goes up, the stability of the capital structure decreases, and based on the market leverage, with the increase of commercial credit, the stability of the capital structure reduces.

 By public-private partnerships, the overflow of resources and innovation goes from the private sector to the public sector, and, consequently, the public sector could improve the efficiency and effectiveness of its services. Despite the attractiveness of public-private partnerships, there are many barriers to their implementation. The aim of this study is to investigate the barriers of public sector financing for construction projects in Isfahan province using a multi-criteria approach.

 The statistical population includes all managers and experts who have the necessary expertise, experience, and knowledge in the field of public sector financing. Due to the uncertainty of the exact size of the statistical population, using the theoretical saturation, the sample size was determined to be 40. Thus, we distributed 40 questionnaires among 20 organizations active in construction projects in the Isfahan province. The measurement instrument of this study was a researcher-made questionnaire whose validity was confirmed by experts. The TOPSIS method was applied to answer the research questions.

 The results show 66 barriers in 5 categories. The findings also show that public-private partnership contracts with the least barriers are service contracts, lease agreements, management contracts, construction, operation, transfer, concession, and joint ventures, respectively.