علی سعیدی

Stock prices are influenced by economic, technological, psychological and geopolitical factors. A review of the literature in this field shows that stochastic approaches, trend analysis and econometrics have been used to demonstrate stock market dynamics and price forecasting. However, these techniques cannot provide a comprehensive overview of market dynamics. Because they ignore the temporal relationship between these factors and are unable to understand their cumulative effects on prices. By integrating chaos theory and continuous data mining based on price acceleration, this study has eliminated these gaps by inventing a new price forecasting method called dynamic stock market recognition simulator and combining two methods: one is delay structures. Or gives time intervals to the data set, and the other is the method of selecting new variables for the market environment. The results showed that the method used can be used to predict the long-term stock price using a small data set with small dimensions.

The purpose of this study is a new understanding behaviour and net cash flow forecasting. The data of this research contains the daily trial balance for one year, which has been received from 48 bank branches. For this purpose, the optimal model out of 4 models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root at three levels of microscopic, mesoscopic and macroscopic have been investigated and the Geometric Brownie model has been approved as the optimal model in microscopic level . The results show that Geometric Brownian Motion model can simulate the net cash flow highly accurate in accordance with the criteria of mean absolute percentage error. also forecasting net cash flow for each under study time series has been done in various forecasting horizons involved 7, 14, 21, 30, 60, 90 and 180 day time period accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that according to 8 different prediction accuracy criteria, By increasing the forecast hori-zon, ability of the GBM model in simulation and forecasting the net cash flow de-creases.

Surah At-Tawbah has a variety of subjects and apparently is fragmentary and irregular; but based on the dimension of the situation, which is the same sociological issues and culture of the era of the revelation of the surah; it is understandable and has a coherent meaning with a clear language. Based on the dimension of the situation, it is possible to understand the ignorant styles such as arrogance, breaking the covenant and shifting the forbidden months by the polytheists that result in the revelation of the first part of verses 1 to 38 of this surah, which introduce this culture and its ugliness. For this reason, God and the Prophet (PBUH) acquit this culture. Consequently, it is the duty of Muslims and the Islamic community to seek the acquittal of the polytheists by following the duality (Tawḥīd, Nubuwwah) and not to approach the polytheists under the pretext of kinship. The second part of Surah (120-139) refers to the constant covenant-breaking of the hypocrites and the problems they caused to the Prophet (PBUH) and the Islamic community. Then, in contrast to the ignorant style, by introducing the religious style and its values, God asks the hypocrites and those who have sick hearts to adhere to the style brought by the monotheistic system by the Prophet in order to prepare their guiding grounds for reaching the Hereafter system. Based on the above explanations, the author has studied the role of situation in eliminating the dispersion and semantics of the surah and its relationship with the trinity (Tawḥīd, Nubuwwah and Ma’ād) with a descriptive-analytical method. Among the most important results that this research has achieved is that: The situation in Jacques Berque's order causes the audience to frame the various topics of the verses of the surah and finally to have a coherent mentality towards them and to achieve a deeper understanding.

Personality is one of the most important study structures in organizational behavior that can play an important role in predicting human behavior. To describe the differences in personality, emotional, and social behavior, researchers have proposed the theory of five personality factors, known as the Big Five. One of the decisions investors make is to allocate wealth to financial and non-financial assets. The importance of this decision is especially evident in financial assets due to their nature and the need for more knowledge and expertise in this field because the mistakes of investors in this regard can create many risks and challenges for them. The main purpose of this study is to explain the effect of personality traits and demographic features on the risk-taking behavior of investors in the Tehran Stock Exchange. The present research is applied research in terms of goals and descriptive-survey research from the method view. The statistical sample of this research includes 358 investors of the Tehran Stock Exchange during 2019 and 2020. Research data were collected based on Sivarjan's (2018) questionnaire. The results of data analysis using the structural equation modeling method indicate that personality traits including neuroticism, extraversion, openness, agreeableness, and conscientiousness have a positive and significant effect on risk-taking behavior. Still, demographic characteristics including gender, age, marital status, and education do not have a significant effect on risk-taking behavior.