نشریه چشم انداز مدیریت مالی
پیاپی 35 (پاییز 1400)

The nature of business and investment activities is such that earning a return requires risk tolerance. Choosing a stock portfolio is a difficult and difficult task that the investor sees in the face of the many and varied choices that she must choose as one of the best methods. The present study deals with the problem of stock portfolio optimization according to the Value at Risk based intelligent fireworks algorithm and compares it with Particle Swarm Optimization algorithm with the historical simulation method using MATLAB software. The parameters of meta-heuristic algorithms were adjusted by Taguchi method using MINITAB software. Not suspended, used. For reliability of the study, generalized Dickey-Fuller test and Phillips-Prone test were used. To evaluate the accuracy of the Conditional Value at Risk model, the kupiec proportion of failure test, Christoffersen independence test and Conditional coverage test are used.  A comparison was also made between the models by Lopez test. The execution time of the Particle Swarm Optimization was less than that of the fireworks algorithm at all three levels of confidence, but the convergence speed of the fireworks algorithm was faster than that of the Particle Swarm Optimization at all levels. Findings showed that the Value at Risk model using the fireworks algorithm, despite the longer execution time due to better convergence speed and higher rank of Lopez test has a more appropriate validity for stock portfolio optimization.

The present study seeks to answer the question of whether there is a relationship between investor behavioral bias and short-term returns of initial public offering (IPO) or not and whether this relationship is affected by audit quality (audit size) and the firm growths of be moderated or not? In this research, the data of 172 companies listed on the Tehran Stock Exchange (TSE) during the years 2008-2021 have been used. To measure investors' interest in lottery through the expected skewness criterion as well as short-term cumulative return, it is calculated within 10 working days after the offer. Regression test was performed based on cross-sectional regression. The results of the study indicate that the direct relationship between the investors’ preference for skewness and short-term returns of IPO and higher audit quality (audit size), reduces the amount of the effect. Also, the intensity of this effect is less in companies that have less growth options than the average than companies that have more growth options than the average.

In order to maintain the balance of cash flow between lenders and borrowers, banks have to use a financially appropriate ecosystem. When such a flow is rebated and or disrupted by non-performing loans (NPLs), life trends of banks and implementation of national economic policies are damaged seriously. Mis management and flexibility in lending and repaying off a loans are considered a drive force of NPLs.The aim of present research is to present a model for the optimization of bank loans portfolio under conditions of uncertainty, which is based on the robust scenario-based approach developed by Mulvey et al. uncertainty criteria set in this study include such economic factors as exchange rates, inflation, and systematic risks. This model has three objective functions: (1) increasing the returns of banks by increasing current loan, (2) decreasing the credit risk, and (3) mitigating the risk of bankruptcy based on Altman Financial Ratios, which are analyzed by using GAMS software. Using this model, bank managers based on the status and strength of each type of loan under normal circumstances and uncertainty can make the right decision to pay a certain amount of each type of loan according to the optimal limit, which reduces the credit risk and bankruptcy of the bank. The results also show that respectively systematic risk, inflation rate and exchange rate have the greatest impact on loan quality reduction.

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.

The purpose of this study is to investigate the effect of informed and noise investors' perceptions of financial statements on stock returns. In this regard, the qualitative data of the reports of the board of directors of 116 companies listed on the Tehran Stock Exchange during the period 2011-2019 have been used. To qualitative analyzing the reports of the board of directors and extracting the textual elements considered by the two groups of informed and noise traders, the text mining and Lasso regression approach was used and to separate the capital market traders into two groups of informed and noise traders, Kalman filter was used. Findings of the study show that both groups of informed and noise traders can achieve abnormal returns by using the information of board reports and basing words and separating them into words with real and fact basis. In the case of mix-meanning based words, the perception of informed traders can affect abnormal stock returns, while noise traders are unable to distinguish mix-meaning words and do not seem to pay much attention to them in their decisions. The results of the research are generally in line with the theory of noise traders and show the behavioral basis (imitative effect) in the Tehran Stock Exchange.

Virtual money is one of the emerging phenomena that can be considered as one of the results of the penetration and expansion of cyberspace in human life. Facilitating financial transactions without the presence of intermediaries such as banks and financial institutions can be considered as one of the goals of creating virtual money. The purpose of this study is to investigate the effects of volatility spillover from Bitcoin as the largest digital currency on other digital currencies. In this study, the variables were converted into Rial currency to reflect Rial fluctuations simultaneously. One component of this analysis is identifying the digital currencies that have been most affected by the price bubbles and the free fall of bitcoin prices. The findings of the present study show that Bitcoin has the highest fluctuations on Dogecoin and dash among digital currencies, respectively, and it receives overflow from other digital currencies that have high transaction value. According to the results of the present study, the bubbles in the digital currency market show that the market is irrational and due to the effects of the existing overflow, it may spread to domestic financial markets and cause a lot of fluctuations.

The main purpose of this study is to investigate the effect of self-control and financial knowledge on financial satisfaction mediated by financial behavior among investors in the Tehran Stock Exchange. This research is one of the types of quantitative and applied studies. In this study, sampling was done by Convenience method with Cochran's formula from the target population. Also, the data were collected through a questionnaire with Likert scale and from the opinions of investors of Tehran Stock Exchange. The face and content validity of the questionnaires were confirmed by experts and its reliability was confirmed by Cronbach's alpha coefficient. Finally, the collected data and the analysis of the relationships between the variables were analyzed by structural equation modeling and SPSS and SmartPLS software. Software output shows that self-control and financial knowledge directly affect the financial behavior of investors. Also, financial behavior has a positive effect on financial satisfaction. The important result of this study was that the role of financial behavioral mediator between independent and dependent variables was significant. The results of this study show that the existence of a desirable level of self-control and financial knowledge among investors can strengthen their rational financial behavior and ultimately, provide financial satisfaction to investors.