نشریه مهندسی مالی و مدیریت اوراق بهادار
پیاپی 39 (تابستان 1398)

More confidence is a personality trait, it may affect the decisions of corporate executives, and Management with irrational behavior can affect the company's performance in the long run. The main purpose of this applied research is “Ability comparison Adaboost Learning Machine Algorithms and Probable Classification Bayesian in predicting Managers over Confidence Iranian Capital Market Companies during the years 2009 to 2017 ". In this regard, Adaboost artificial intelligence algorithms and Probable Classification Bayesian were proposed to validate this year and the following year in order to provide a model for predicting Management over Confidence in Tehran Stock Exchange companies. In total, 34 different industries were selected as statistical samples (financial data of 3145 companies-year in total). The method of data collection in the theoretical part of the library method and for calculating and statistical classification of financial data, from software's Excel and to test the research hypotheses Used from the software matlab 2017. The research findings show that, obtained nonlinear models prediction of the Adaboost algorithm and the probable Bayesian algorithm, both have ability to predict the over confidence of management for this year and one year later, But Adaboost 's prediction model, in contrast to the Bayesian's prediction model, has better results in predicting Management over Confidence. Which indicates greater power in learning and better performance of this model in order to predict the uncertainty of management.

The purpose of this study was to investigate the relationship between volume of transactions and value of transactions with stock returns in the stock exchange and various stock markets during the years 1385 to 1395. To investigate these communications, we used MGJR-GARCH, DCC-GJR-GARCH, diagonal BEKK and COPULA models. Between trading volume changes and stock returns of companies there is a two-way and direct relationship, but the relationship between transaction value and stock returns is one-way, and only the value of transactions that affects stock returns. Also, in the review of variables Researches with volume of transactions revealed that changes in the variables of liquidity volume, annual returns and oil prices with the volume of transactions have a reverse and meaningful relationship, and the returns of companies' shares and the value of transactions with the volume of transactions has a direct and meaningful relationship. Also, other than the volume of transactions, other research variables have a significant relationship with annual stock returns. The volatility of the volatile variables, the volume of liquidity and the price of gold, direct effect, and the changes in the value of transactions and oil prices have a negative effect on the returns of companies. The only variable whose volatility affects the price of oil is the return on shares of the companies.

This research aims in effect identification of Iran accounting standard No.15 in revelation of instruments, financial derivatives and its effect on excess return and companies` values in Tehran Stock Exchange. So, the research sample includes 82 investigated companies in Tehran Stock Exchange for a 4 year duration, (2014-2017). In this research combination and adjustment of Yekini suggested checklists and other internal standard 15, 36, 37 of Iran have been used to evaluate revelation level of financial derivatives in comparison by the above standard requirements. Regression test has been used for generalized squares` minimum of paneling data and the below conclusions have been gained. The research findings indicate that companies intend more revelation based on the standard requirements on Iran No.15. The findings of the research first hypothesis shows that the companies which have disclosed their financial instruments based on this standard, their risk adjusted discount rate will decrease, so this means increase of future market and market price in the other words it means increase of current market value. The findings of the second hypothesis also show that in companies that manage earnings, the risk of discount rates is also increased by reducing the level of disclosure of financial instruments and derivatives. The research third hypothesis represents that there is a direct meaningful relationship between revelation level of instruments and financial derivatives with company value. These conclusions cover the findings out of country, too. So, existence of high modulations of excess return for companies with lower revelation level indicate higher risk. Finally, company beneficiaries should expect risk in regards to level and quality of revelation instruments and financial derivatives.

The purpose of this research is to investigate the relationship between stock liquidity and dividend income during recession and prosperity in companies accepted in Tehran Stock Exchange. Statistical sample of 109 companies accepted in the capital market, whose information was available for the period 2012 to 2017, were selected by systematic exclusion method. The research carried out in terms of the target type is a part of applied research and the research method is correlated in terms of content and content. For analyzing the hypotheses, panel analysis has been used. Research findings show that there is a positive and significant relationship between stock liquidity and dividend income. There is also a positive and significant relationship between stock liquidity and dividend profits during the boom period. While there was no significant relationship between stock liquidity and dividend during the recession period.

The purpose of this study is to examine the relative importance of risk premium factors and the investor's sentiments to explain the deviations of the market price of the fundamental value of the stock of the companies. To achieve this goal, using the data of 95 companies during the financial periods from 2011 to 2016, the effect of the investor's sentiments and risk premium factors in explaining market price deviations from fundamental value of stocks has been investigated using multiple regression model. The results of the study showed that the deviation of the stock market value from the fundamental value of the stock can be explained by both the investor's sentiments and the risk premium. Negative effects of investor's sentiment lead to an assessment of below the stock market value relative to its fundamental values. The variable of the financial crisis also has no significant effect on the relationship between the investor's sentiments and the deviation of the stock market price from the fundamental value of the stock.

The prospects for future earnings, its stickiness, and the cash returns of a company's shares, due to their objectivity and tangibility, are of particular importance to stockholders and capital market players in corporate analysis.
Since the behavior and attitudes of executive managers are effective on the prospects of future earnings and its stickiness, in this research, the relationship between future income prospects stickiness and the two behavioral financial features include: conservatism and managerial max ability are investigated.
The statistical population of this study includes 206 companies accepted in Tehran Stock Exchange during the period of 2009-2017 which have been tested using multivariate linear regression using Eviews software. The results of the research indicate that there is a meaningful positive relationship between the two criteria and the stickiness of  the future earning perspective.

now wadays the subject of currency exchange rates plays an important role in international trade. Therefore, one of the major concerns of policymakers is to decide how exchange rates can be determined in an attempt to provide stability in the foreign exchange market of Iran for decreasing costs and risk of investment and making    security in economy. For achieving the goal, the identification of different sectors of FOREX can help policymakers in Iran's central bank to design an appropriate market and different instruments for controlling the currency market and making better security for businessmen in a real economy. Meanwhile, entering the marginal FOREX market in Iran and fraud activities cause reaction of regulator and Sharia's scholars who forbid this market without scientific research when marginal FOREX is only one part of the FOREX. Therefore, this research tried to recognize different parts of the FOREX market and to understand operational structure of this market especially the marginal market. Simultaneously, it studied this waste market in order to find and show advantages and disadvantages for policymakers and scholars. Also, this research tried to show jurisprudential assessment for finding Sharia's problems from Shia approach. Finally we understand that marginal FOREXjust developed speculative activities but researchers can focus on other market fields in order to design hedging instruments something like future and forward contracts. Also we understand that the marginal FOREX market has significant problems from sharia approach. This means that using and taking apart in this market is forbidden

This paper examines the relationship between stock returns and the systematic risk in the medium and long term time horizons and evaluates the effect amount of market fluctuations on the above relationship in nutrients and dairy companies listed in the Tehran Stock Exchange during the 2008 to 2013. In the financial market capital is one of the most important issues of the relationship between risk and returns, especially systematic risk; Because it is believed that stock returns is only a function of the systemic risk. Several studies have been conducted to investigate the relationship between risk and returns. Among these efforts, is a study that conducted by Sharp. He by introducing the model of (CAPM Capital Asset Pricing Model) assumed that there is a simple linear and positive relationship between systematic risk and exchange return. In order to testing the research hypothesis at first the research period based on the variance for the pharmaceutical and chemical industry index has been divided into two categories of high oscillation and low oscillation periods. Then information related to systematic risk and stock returns in the periods of high oscillation and low oscillation overlap by method of Discrete wavelet transform (DWT) and by Daubechies  wavelet by using MATLAB software parse to smaller period of time, then regression analysis was used  in order to testing  research hypotheses. Results of testing hypotheses indicate  there is a significant relationship between systematic risk and returns in the high oscillation time period in the medium and long term time horizons. Also in time periods of low oscillation also in the medium-term time horizons there is a significant relationship between systematic risk and returns but meaningful relationship between risk and return is approved only in long-term time horizon for 182 days.

In this study, to determine the stock price forecasting method, a LM-BP neural network was presented based on time series with respect to open price, highest price, lowest price, package price and volume of transactions. In the present study 315 days of stock prices were chosen to create 10 samples and the test set includes stock prices from day 316 to day 320 and used the LM-BP neural network. In this research, the determination of the critical point of excess, asymmetry and counting of intervals were investigated. The curve MRE2-MRE1 was plotted and the precision related to the best prediction of the BP neural network was estimated based on several independent replicas. The post-test was performed using a Kupiec Test and a Christopherson test. The results showed that stock price prediction based on the LM-BP neural network and over-point estimation by counting the intervals resulted in better results than the existing methods.

Recognizing variables which are able to explain stock price movements is a very important matter for the capital market activists. Three main groups of variables that seem to have a significant role in this explanation are: 1) Fundamental Variables 2) Historical Stock Price Returns 3) Macroeconomic Variables. This research investigates the relationship between these three groups of variables and stock price returns on the listed companies of Tehran Stock Exchange. Moreover, the complementary role of fundamental variables and historical stock price returns in explaining stock price movements is investigated. Eventually the difference between the roles of fundamental variables and historical stock price returns in large and small firms is studied. According to the results of the present research there is a significant relationship between all three mentioned groups of variables and stock price movements and also fundamental variables and historical stock price returns are complementary variables for explaining stock price movements. Moreover, the growth variable is more important in small firms compared to larger firms for interpreting stock price movements.

This essay is going to optimize the portfolio of stocks similar to the Markowitz approach. Nonetheless, the way in which the risk is measured is Foster-Hart risk. This measure was proposed by Foster and Hart in 2009. It takes into account the extreme events of losses. The theoretical definition could be as a minimum wealth that an investor should have in order not to face with bankruptcy. Our sample consists of adjusted daily data from thirty-four companies chosen from Tehran Stock Exchange’s Top 50 Index in the period between 1391/07/01 and 1396/06/31. Data has been collected from Rahavard Novin software which is widely used in finance studies in Iran. Different optimal portfolios has been achieved in this essay. Each of which uses a different method of risk like Cvar and Semi-Variance besides Foster-Hart. Results of this essay show that Foster-Hart optimal portfolio could have higher sharp ratio in comparison with the others.

Resilience of economy against internal and external shocks is an important concept that has been of interest to economists in the last decade. In this paper, we propose a model based on Schumpeter economic theory using system dynamics analysis approach and also discuss on resilience and vulnerability of economy. Based on the proposed model, vulnerability of Iran’s economy and 5 other countries (i.e. Sweden, USA, Japan, South Korea and Indonesia) is forecasted for next 50 years. Major contributions of this paper can be explained in two aspects: first, the concept of economic resilience, that mostly expressed qualitatively, is explained quantitatively. Second, the concept of economic resilience and system dynamics are combined and the capability of studying different scenarios is provided. Five different scenarios are proposed in this paper and it is found that if the current level of innovation is double increased and decrease 50 percent Oil dependence, the vulnerability risk in Iran’s economy will decrease by 70 percent.

One of the most important issues of financial markets is the prediction of price and stock returns. In this paper, we try to find the best model and stock price prediction approach based on the mean square error (MSE), root-mean-square error (RMSE), R-squared, standard deviation (SD), Mean absolute error and the mean absolute percent error (MAPE) for the Fama and French five-factor model. For this purpose, after the formation of a portfolio based on the Fama and French model during the period from 2009 to 2017, stock price is estimated by econometric model, neural network and Fuzzy Neural Networks, so the accuracy of each approach was compared. The results of the prediction the efficiency of the generated portfolios show that the prediction accuracy of the radial base function network (RBF) is very high compared to other ARMA models and other neural networks.

One of the most important actions on risk management is to obtain correct and rigorous information from the nature of the time series which are known as risk drivers. In this paper we introduce a model for interest free deposits using stochastic processes. To this end we use the geometric Brownian motion, jump-diffusion, Cox- Ingersol-Ross and mean-reversion models. Also to develop the approach we decompose the volatility of the time series into deterministic and stochastic parts and model the stochastic part only. The deterministic part is the sum of trend line and periodic cycles. We observe that after estimation of parameters and model calibration, the results are consistent with initial expectations which are as follows: The performance of the models increases with separation of deterministic and stochastic parts. Although at the same time the phenomenon of mean reversion and heavy tail is approved, but, Cox-Ingersol-Ross model show a better behavior than jump-diffusion model. Finally the man-reversion and Jump-diffusion models have better performance than other models.

The purpose of the study is to obtain a probability of a very high loss for a credit portfolio in a fixed time horizon and to calculate the loss of this portfolio in the worst possible case (the defaults of all customers). For this purpose, the Copula function approach is used. A Copula function is a new tool that increases the accuracy of the calculation of this probability. Gaussian Copulas cannot simulate the dependence between the members of the portfolio. For this reason, the T- Copula method has been used as an alternative model in this paper. The T-Copula pattern, in contrast to the normal Copula method, supports the extreme dependence between variables. The structure of a multivariate distribution t is the ratio of a multivariate normal distribution on the second root of a Chi-square random variable. If the denominator of the distribution chooses values ​​close to zero, then the corresponding vector coordinates of the random variables are distributed t , Can record large joint movements. The Chi-square random variable plays "common shock" roles. The present study, using the hidden variables method, has calculated the probable unpredictability of loss for a heterogeneous portfolio of given facilities consisting of 250 borrowers. For this purpose, based on the type of borrowed loans, borrowers are divided into three groups. Using the Monte Carlo simulation method, the probability of a loss in this portfolio is estimated, then the residue levels in each group of agents and the total amount of exposure are calculated. The findings showed that, considering the degree of freedom 2 for the distribution of the student's t-test related to the vector of hidden variables, the maximum probability of loss of credit portfolio Has been 11.01.

Barrier options are considered the most widely used financial derivatives, which are massively traded in the financial markets due to its cheaper price in comparison with other standard options. Also, these options are family-path-dependent options, because their value depends directly on the movement of the underlying asset value during the option contract. Because the accurate order differential equation is unable the effect of trend memory in financial market, in this paper, we consider the fractional order differential equation. In order that our problem is closer to the real market model, we assume that interest rate, dividend yield and volatility are as function. The main purpose of this paper is to determine the price of European double-knock-out barrier option under the time-fractional Black-Scholes model with a fractional order . In here, the underlying asset follows the constant elasticity of variance (CEV) model. Such problems do not have exact solution in closed form, so using a finite difference method we find a suitable numerical solution by introducing implicit difference scheme. In the continuation, we investigate unconditional stability and convergence the proposed scheme by using Fourier analysis. We finally show the efficiency of the proposed difference scheme and its numerical convergence order by mentioning some numerical examples. In addition, we study the effect of the important model parameters (,  and ) on long memory in form table and figure.