سیدجلال صادقی شریف

Cash flows have a significant impact on various factors including labor investment efficiency. In this regard, Beladi et al. (2021) show that companies facing cash flow risk are likely to increase current labor investment to reduce future financing costs. Delays in labor investment expose the firm to additional risks associated with uncertain cash flows and potentially reduce its ability to finance existing projects (Boyle & Guthrie, 2003). However, due to the lack of sufficient research on this issue in Iran, this research seeks to address this need.

The statistical population for this research includes all firms listed on the Tehran Stock Exchange from 2015 to 2022. Data necessary for this study was gathere from the information bank of the Tehran Stock Exchange and Securities Organization (Codal) and Rahvard Novin software. Excel software was utilized for data collection and organization, while SPSS and Eviews were used to test hypotheses and analyze findings. This research follows an event study design, with the t-test being the most commonly used statistical test for such studies. The study focuses on evaluating legal requirements in the capital market by examining transaction volumes, announcements for news conferences, clarification of stock price fluctuations, dispelling of rumors, and trading symbol suspensions This research examines the moderating role of education and research and development costs on the relationship between the efficiency of labor investment and the fluctuations of operating cash flow of companies that are admitted to the stock exchange. In terms of goals, this research is practical and in terms of methodology, it is a type of post-event research. The statistical population includes all the companies that have been admitted to the Tehran Stock Exchange and the systematic elimination method has been used for selection. 1396 to 1400 were investigated.To collect information, a library method was used and the research hypotheses were tested using the panel data model and multiple linear regression.

Research findings show that operating cash flow fluctuations have a significant effect on the efficiency of labor investment, and employee training costs have a significant effect on the relationship between labor investment efficiency and operating cash flow fluctuations, as well as research and development costs on the relationship between efficiency. Labor investment and operating cash flow fluctuations have a significant effect.

The greater the volatility of operating cash flow, the greater the efficiency of labor investment. In other words, companies facing cash flow risk are likely to increase current labor investment to avoid high financing costs in the future; because fluctuations in cash flow increase the company's risk and thus affect the risk of companies with inefficient labor investment. Therefore, the results of this research are in line with the research of Habib and Ranasinghe (2022). On the other hand, the second hypothesis of this research was shown that the costs of employee training as a moderator of the relationship between the efficiency of labor investment and the fluctuations of operating cash flow are affected. To give this means that the lower the costs of employee training, the greater the volatility of operating cash flow as the efficiency of labor investment increases. In other words, a company with high cash flow risk is more likely to invest more cautiously in its workforce. It then reduces the costs of employee training to force management to improve the efficiency of workforce investment to increase shareholder value and reduce future financing costs. Therefore, the results of these studies are consistent with Beladi et al. (2021) and Habib and Ranasinghe(2022), because they believe that companies facing cash flow risk are likely to increase current workforce investment to avoid high financing costs in the future. Avoid, because fluctuations in cash flow increase the company's risk and thus affect the risk of companies with inefficient labor investment. Meanwhile, the third hypothesis of the current research shows that research and development costs as a moderator affect the relationship between labor investment efficiency and operating cash flow fluctuations. This means that when faced with cash flow risk, company managers try to maximize R&D expenses by effectively investing in labor to increase the value of the firm, because the ability of investments from R&D expenses is highly dependent on cash flow. And is quite sensitive to cash flow fluctuations.

One of the most important issues in financial knowledge which is related to portfolio selection, efficiency market and asset allocation is spillover effect between markets and this effect includes return, volatility and shock effect. These days every shock or volatility in one market effect on other markets. Correct identification of spillover effect is very important. This paper aims to measure and analysis spillover effect between stock, currency, gold-coin, oil and housing markets. For these purposes we collect daily data of stock, currency, gold-coin, oil and housing for the time period of 2009 to 2020.we used VARMA-BEKK-AGARCH model for estimation. Results show return spillover from currency to stock and from stock to housing and shock spillover from currency, gold-coin and oil to stock and also volatility spillover from currency and gold-coin to stock and from stock to housing. Besides result show leverage effect of shocks from stock to housing market.so we suggest in order to minimize investment risk we had better to evaluate the spillover effects in selecting markets(assets)for our portfolio.

In recent years, the increasing speed of information transfer and market connectedness has caused markets to converge and affect each other. The spillover effect occurs when the return or volatility of one market cause fluctuation in another market or other markets. Nowadays every shock or volatility from one market affects others. Properly identifying the effects of spillover on financial markets is crucial for managing and controlling fluctuations. This paper aims to measure and analyze the nexus and spillover effects among the stock market, currency market, gold market, and commodity market.
In this study, the researchers selected some variables like the stock market, currency market, gold market, and commodity market and for better analyses of these variables, they used daily returns of the stock index, currency (dollar), gold, and commodity for 12 years, starting from January 1, 2009, to December 31, 2020. Next, they applied the VARMA-BEKK-AGARCH Model to measure and estimate the spillover effects. The model is very strong and robust for measuring and examining the return and volatility spillovers between markets.
Results achieved from the estimation model showed unidirectional return spillovers from the gold, dollar, and commodity to the stock index, unidirectional shock spillover from commodity to the stock index, and unidirectional volatility spillover from the stock index to currency. Also, the leverage effect of shock was proved as bidirectional between currency and gold and unidirectionally from stock to currency.
According to the obtained results and considering the inverse relationship between stocks and gold, creating a portfolio consisting of stocks and gold seems useful to reduce the effects of risk spillover and helps investors to reduce their investment risk. Regarding the confirmation of shocks from stocks to the foreign exchange market, to control the foreign exchange market, it is recommended to manage the stock market and prevent severe fluctuations. Depending on the established flexibility and interaction among markets, shock and volatility spillover may have three outcomes. First, when markets are flexible and with a good and coherent relationship, the hitting negative shocks transmit among them making no damage to the markets. Second, when markets are inflexible but the relationship among them is weak, the negative shocks would damage one but would have not any effects on other markets. Third, when markets are inflexible but the relationship among them is good and coherent, negative shocks hitting one market not only damages that market but also harm those connected to it. Therefore, to diminish and modify the effects of shock and volatility spillover on the markets, markets need to be improved and enhanced from the two established aspects of flexibility and relationship among them.

In recent years increase in the speed of information transfer and market connectedness caused markets to convergence and affect each other. Today every shock or volatility from one market affect the other markets. This paper investigates nexus and spillover effect between commodity and Tehran stock index. Time periods of this paper is 12 years starting from the first of 1388 to the last of 1399. We used VAR-BEKK-GARCH Model to measure correlation and spillover effect from two groups of commodities: the first group includes precious metals (gold, silver, platinum and palladium) and second group includes base metals (copper, aluminum, zinc, tin and nickel) toward Tehran overall stock index. Results for the first group (precious metals) show spillover from gold to Tehran overall stock index and volatility spillover from palladium to Tehran overall index. for the second group (base metals) return spillover from copper, tin and zinc to overall index and volatility spillover from aluminum to overall index was revealed. shock spillover was not seen for any groups of precious metals and base metals to overall index.

In this study, we have used the total capital market index (TEDPIX) as an index of the real sector of the economy and the index of banks and credit financial institutions as an index that explains the developments of the banking system. Also, oil revenues, exchange rate uncertainty, tax revenues, liquidity, nominal interest rates, inflation uncertainty and GDP have been used as macroeconomic variables in the research period (1370-1396). To estimate the systemic risk of the banking system, the quarterly data of the banks' index is used and the value at risk of the return of the seasonal data of the index is estimated using an exponential GARCH model. In order to model the interaction of macroeconomic variables and systemic risk of the banking system, an unrestricted vector autoregression (VAR) model was estimated and then using instantaneous impact functions and based on Chulsky analysis, systemic risk response to other variables was investigated and analyzed. In order to identify the channels of impact of economic shocks on the systemic risk of the banking system, based on the structures of the Iranian economy, a structural vector autoregression (SVAR) model was specified and then the instantaneous impact functions were extracted and the effect of macro variable shocks on the systemic risk of the banking system was investigated. Also, the effect of systemic risk of the banking system on macroeconomic variables was investigated and analyzed using instantaneous impact functions. Finally, the interaction model of macroeconomic variables and systemic risk of the banking system was approved using the vector autoregressive model.

The purpose of this research is to investigate two controversial cases about the momentum in the Tehran Stock Exchange. These two cases include risk theory and under-reaction theory. This research will be followed in two parts. The first part tries to explain the momentum with respect to risk. The second part describes the excess return in momentum portfolios with the under-reaction hypothesis. The research hypotheses have been examined using the data of 58 non-financial companies from the Tehran Stock Exchange between 1389 and 1398. The results show that the risk-adjusted momentum profit is statistically significant. In addition, the results show that the five-factor risk model is not able to explain the momentum effect. However, the momentum effect can be explained by using the under-reaction hypothesis. The under-reaction is asymmetric for first six month after the earning announcement date. In general, the findings also rejects the efficient market hypothesis in favor of the under-reaction theory.

The main purpose of this study is to investigate the effects of investor sentiment on bubble formation in the stock market. This study aims to find a significant relationship between investors' sentiments and the creation and explosion of the bubble in the Tehran stock exchange. For this purpose, daily index data is used as well as investor sentiment index for the 2009 - 2019 period. By using Dicky – Fuller test, we identify bubbles in the Tehran stock market and calculate the indicator of investor sentiment. Afterwards, we study the relationship between investor sentiment and bubble formation by using Logistic regression. According to the research findings, the hypothesis of the influence of investor's feelings in the capital market on the formation of the financial bubble is rejected.Also according to the results of logistic regression and probit regression, The probability value of the variable EMSI (Equity Market Sentiment Index) at conventional statistical levels is meaningless. Further, the author observes that, Investor's sentiment have no effect on the formation of a bubble in the Stock market.

This study aims to explain the relationship between cognitive abilities and faith in intuition with behavioral biases and also to explain the relationship between behavioral biases and performance of professional investors in the Tehran Stock Exchange. We compare two different measures of impulsive or intuitive behavior, examining their effect on anchoring bias and conjunction fallacy, and finally examining the effect of behavioral biases on investors' performance.

The sample consists of 311 professional investors in the capital market whose data were collected via questionnaires. Chi-squared test, Mann WhitneyU test, ordinary least squares, and probit regression were used to analyze the data.

The results show that faith in intuition has a positive and significant effect on anchoring bias and conjunction fallacy. While cognitive ability has a negative and significant effect on the conjunction fallacy. The results also show that faith in intuition has a negative and significant effect on return. The results of regression analysis also show that gender reinforces the negative effect of cognitive ability and the positive effect of faith in intuition on the conjunction fallacy.

The results show that faith in intuition is more related to behavioral biases and performance than cognitive abilities, and is more informative overall.

Earnings management takes advantage of how accounting rules are applied and create financial statements that inflate earnings or revenue. In breaking down earnings management, companies use earnings management to smooth out fluctuations in earnings and present more consistent profits each month or year. A company's stock price often rises or falls after an earnings announcement, depending on whether the earnings meet or fall short of expectations. In this research, we study the effect of earnings management on the long-term investment productivities of selected companies in Tehran Stock Exchange. We also study these companies in two separated groups, companies with Decreasing Earnings Management and companies with Increasing Earnings Management.
The results showed that the earnings management is not common among selected companies listed on the Tehran Stock Exchange. Most cases are increasing earnings management (over 88%). Increasing earnings management does not have a negative impact on the long-term investment productivity of these companies. But, increasing earnings management and investment productivity is inversely correlated. Also, decreasing earnings management has a negative impact on the long-term investment productivity of these companies.

 Based on Markowitz theory of portfolio optimization, capital market is not predictable by any methods and the risk can only be diversified through portfolio formation and optimization. Recent works made huge developments in the basic model from modeling and risk measures perspectives. Spectral risk measures such as expected shortfall and value at risk are being used frequently as risk measures. In addition, researchers tend to consider uncertainty in risk and return evaluation via fuzzy, stochastic and robust modeling. However, a matter that has been neglected in many researches is portfolio management under uncertainty conditions. This paper propose a method for robust modeling of portfolio optimization and management using expected shortfall as risk measure and Bertsimas modeling as robust programming. The proposed model solved with artificial bee colony algorithm and results show a better performance of proposed model compared to classic methods in both the optimal portfolio formation and its management phase.

One of the most fundamental economic issues for holding companies is capital allocation. Typically, investors in selecting investment alternatives follow conflicting preferences and goals simultaneously. Therefore, in the present study, we are looking for to study the Factors Affecting on the Management of investment in holding companies. This study is an applied research from the purpose perspective and is descriptive based on its data collection method. To assess the validity of the questionnaire, the diagnostic validity (DV) using an average variance extracted (AVE) and to determine the reliability of the questionnaire Cronbach's alpha were used. In addition to completely browsing the literature and by selecting the statistical sample members from holding managers using of random sample method, researchers have evaluated the research hypotheses by using of structural equation modeling (SEM) and regression methods. Research findings indicate that Internal factors (including Technical, process and operation parameters) and External factors (including Risk & return and market parameters) have a significant impact on Management of investment in holding companies.

The analysis of the turbulence among markets has been widely applied and in details the emphasis on theorists and researchers in different fields. The reciprocal relationship between financial markets and the macroeconomic markets is based on the idea, which has negative shocks to the economy of the housing sector. The behavior of the housing market is also important because of the impact of housing prices on bank loans and other financial institutions. In the housing sector, a monetary and monetary policy is expected to increase demand for housing by increasing the volume of money in the asset portfolio. Of course, this will depend on a variety of issues. Therefore, the need for further reflection seems necessary in this part. In this study, using the time series analysis of vector regression (VAR), the relationship between financial and financial markets has been investigated. The results of the study show that financial markets, especially foreign exchange markets and gold markets have a significant relationship with housing.

To achieve the goals, a hybrid research strategy has been used in this research. In qualitative research, 16 factors affecting the behavior of individual investors (availability, limited attention, self atribution, anchoring point, over confidence, gambler's fallacy, loss aversion, increasing risk appetite, justification, optimism, regret aversion , time horizon, control center, tolerance of ambiguity, confident- anxious, careful-impetuous) which was obtained through the method of analyzing the content of semi-structured interviews of capital market experts, which were based on the construction of a researcher-made questionnaire. In the quantitative section, the final model of decision-making behavior of the individual investors was extracted using structural equations and fitted out. In the capital market of Iran, the model of the behavior of individual investors begins with cultural factors. In other words, the underlying factor in the behavior of investors is the factor of culture. The theory that emotional biases are prior to cognitive biases is not confirmed in this research. Personality has a positive relationship with herding behavior. In other words, category of anxiety in stockholders, increases the volume of their herding behavior.

According to the first clause of article 110 of Iranian constitution, the supreme leader of Iranian revelation imparted the resilience economic policies in 2014. These policies are complementing the policies of privatization or article 44 of constitution to achieve economic goals. The main goal of this instruction is creating stability in economy. Therefore, in this research we have measured stability of banking system as a main part of economy against macroeconomic shocks. While the resilience economic policies extend the article44, we have divided banks in to two part: public banks and private banks. Then we have used survival analysis and Cox proportional hazard models to measure resilience and bankruptcy threshold of Iranian banks. Results represent that uncertainties of inflation and interest rate have more effect of resilience of banking system. Also results show that the resilience of public banks are two years less than private banks and the resilience and survival time of Iranian banking system is about 5years. Also, the positive coefficient of uncertainty of the GDP growth rate shows that there is a reciprocal relationship between the usury free banking system and the real sector of the economy. Therefore, usury free banking in Iran, due to the lack of attention of the policymaker and the supervisor of the manufacturing sector in providing the banking facility, has failed to its main advantage is to establish a close relationship with the real sector of the economy.

Financial distress prediction is always a concern for shareholders, creditors and business unit managers. Hence, various models proposed to predict financial distress. In this research, decision tree model and linear multiple discriminant analysis model have been used to predict financial distress of companies. In addition, the results of these two models are compared with each other. In this regard, it has been tried to use intellectual capital and value-based performance in addition to conventional financial ratios in predicting financial distress. To achieve the objectives, three hypotheses formulated. The purpose of the research hypotheses is to investigate the information content of intellectual capital and performance indicators and financial ratios in predicting financial distress in Tehran Stock Exchange companies using decision tree models, linear multiple discriminant analysis and the combined model derived from factor analysis - linear multiple discriminant analysis and the factor analysis is the decision tree. To test these hypotheses, a sample selected from Tehran Stock Exchange companies during the years 2010-2010. The results indicate that the prediction of financial distress is possible using a decision tree, but in the decision tree model, intellectual and functional capital indicators do not have information content to predict financial distress. The linear multiple discriminant analysis model has been successful in combining financial ratios and performance indicators in the prediction of financial distress. Comparison of the capabilities of the two models indicated that although the accuracy of predictive analysis of the linear multiple discriminant analysis based on the assessment criteria (competing table) and the level below the rock curve (0.920) was higher than the decision tree (0.901), but based on the t-test, This difference is not significant (p = 0.207). In other words, the results of the two methods are very close.

This research predicts financial distress of companies listed on Tehran Stock Exchange using Factor Analysis, Decision Tree, and Logistic Regression models. For this purpose, 33 financial ratios have been investigated in the 5-year time horizon. In order to reduce the dimensions of the data and to find the internal relationship the variables, factor analysis model has been used. Then, the variables according to their relationships with financial distress are classified in eight factors. In the following, the results of the decision tree and the logistic regression models are compared with each other. The results show that both models have the ability to predict financial distress, but the decision tress model has a higher predictive power than the logistic regression model.

​In this paper, a multi-layered network model of the banking system is designed to explain the systemic risk of the banking system of Iran. This model shows how the dependence of the balance sheet structure of banks results in the crisis from one bank to another, and ultimately causes a crisis in the economy as a whole. It is assumed that the banking system is composed of banks with their balance sheet structure dependent on each other. To estimate the systemic risk of the banking system, the daily index data of banks indexes are used between December 2008 and April 2018 and the value at risk of returning daily index data is estimated using an exponential GARCH model. The daily returns of the stock market index are taken as representative of the real economy, Quantile regression is estimated at two levels of 50% and 1%. In the following, based on the estimated parameters in quantum regression and also on the basis of the CoVar Adrian and Brunnermeier (2016), the risk of the banking system is estimated. The results show that the average ΔCoVaR is estimated at -0.8587, which is consistent with negative expectations and represents a high systemic risk of the banking system.

In manager myopia, long-term profitability of the firm through reducing the research and development activities, marketing and activities which are costly in the early years are determined, have been sacrificed in order to achieve the short-term profit and enhanced current-term stock price. The purpose of this study is to examine the reaction of Capital Market to managerial myopia and theimpacts of the existence of institutional investorson listed companies in Tehran Stock Exchange (TSE).
Using systematic elimination method, 170 companies were selected from among the companies listed in TSE during 2007 to 2016. In this study, reaction of the capital market is measured based on abnormal return criteria.
The results of the first hypothesis showed that the F-value is 2.942, its level of significance is set at 0.000 and the determination coefficient was measured 0.146; besides, T-value and level of significance for managerial myopia were reported 0.165 and 0.869 respectively. Based on the results of the second hypothesis, F-value, level of significance and the determination coefficient for the companies with organizational investors are reported 2.652, 0.000 and 0.085 respectively; and the F-value, level of significance and the determination coefficient for the companies with non-organizational investors are reported 3.181, 0.000 and 0.098. Finally, T-value and level of significance for managerial myopia were reported 1.331 and 0.183 for the first group and 0.776 and 0.436 for the second group, respectively.
The results indicated that the presence or absence of institutional investors among the stakeholders does not have any significant effect on the relationship between abnormal returns and manager’s myopia. In addition, there is no significant effect of capital market reaction on myopia managers. At last, as expected there is a negatively significant relationship between managers’ myopia and abnormal returns.

Accruals are the non-cash component of earnings. Cash-based operating profitability is a measure that excludes accruals from the operating profitability. We used this measure to predict stock returns. With a sample of 164 stocks from the Tehran Stock Exchange (TSE) over the period of 2006 to 2015. We observed the relations between accruals, operatingprofitability and cash-based operating profitability in the cross section of stock returns and found that cash-based operating profitability is a better measure compared to accruals and operating profitability in predicting stock returns. We also performed portfolio sorts and priced accrual-size portfolios using Fama and French three-factor model augmented with accruals, operating profitability and cash-based operating profitability. It turned out that the three factor model which was augmented with cash-based operating profitability factor outperformed other augmented models for pricing portfolios sorted by accruals-size according to well-known performance measurement tests such as GRS.

The rapid technological changes, the intense competition of enterprises, and globalization have transformed the phenomenon of financial distress and corporate bankruptcy into a major issue in financial and investment literature. Bankruptcy attracted the attention of financial sector activists, including investors, lenders, suppliers, business partners, and governments. Considering the role of intellectual capital in organizations, one can expect that companies with a richer intellectual capital are more intelligent in avoiding bankruptcy. The purpose of this research is to investigate the role of intellectual capital and its components (including human capital, structural capital, and customer capital) on the firms’ probability of bankruptcy in Tehran Stock Exchange. For this purpose, the data of 147 firms from Tehran Stock Exchange that are selected by systematic elimination method were studied during the years 1387 to 1393. In order to measure the intellectual capital, the PULIC model and to assess the probability of bankruptcy, conversion of Zscore results (from Altman Model) to the probaility was used. Also, to test hypotheses, multivariate regression models with hybrid data have been used. The results of the hypothesis test show that intellectual capital and its components have reverse and significant effects on the firms’ probability of bankruptcy in Tehran Stock Exchange.

Working capital management is one of the most important issues in financial management and corporate finance that focuses on current liabilities and current assets. The aim of this research is to investigate the relationship between working capital management and profitability of listed firms in Tehran stock exchange. The research in class of the field study and with the use of techniques of panel data Includes 3120 observations (company/season) is done. Therefore the seasonal information of 156 firms of listed firms in Tehran stock exchange during the period of 1389-1393 has been investigated. In this research¡ in order to not false regression, stationary test on the Research variables used and to specify the type of a hybrid model (Panel model vs pooled model) F limer-test used¡ and to specify the type of the Panel model (fixed effects vs random effects) The hausman test has been used.ultimately in this Research the Panel data with fixed effects model and by EGLS method has been used. Eviews software to test assumptions and The estimate of research models and analysis of the results of the research models is used Research findings indicates that between all of the elements of working capital with profitability of companies significant inverse relationship exists.

Bubbles in asset markets result in diversion of savings allocations. For this reason, in macro level, the diversion of the savings disrupts investment efficiency and whole economy. Many studies in the field of behavioral finance have been undertaken to investigate this phenomenon. Recent research has shown that traditional models of unit root in the detection of explosive behaviors, especially at long ranges, are weak. In this paper, the generalized models, right-tail Dickey Fuller (RADF), and more powerful models of generalized Dickey Fuller (SUP ADF and GSADF) are used. These models, in addition to their stronger identification of explosive behaviors at long intervals, can also specify the time period of the bubbles. In this paper, the time period from 1980 to 2003 for the stock market and real state was tested. The results of this research, which is based on the advanced tests, show that the stock market and the reals state market experienced explosive bubbles behaviors in the period examined; it was 24 periods for the stock market and 12 periods for the housing market.

The stock market agents should increase their prediction accuracy to maximize their returns, and it needs some advanced tools. In this article stock price of 50 companies in the Tehran Stock Exchange have been modeled using feedforward artificial neural networks. In this way, the daily stock prices are used from December 1384 to December 1394. The predictions accuracy are evaluated with four statistical indicators. The results show that accuracy of ANN predictions is very high. In some cases, although the prediction accuracy is higher, the correctness is lower. Therefore, in the assessment of the prediction, evaluation of the correctness has a significant contribution