ایمان محمدی

There has been a significant growth in people's use of social media in recent years. It has been determined that the digital footprints are a reflection of the personality. It is possible to use this data to predict characteristics and use it in various fields, such as job Assessment Centers. The purpose of this research was to develop and examine the psychometric properties of the online profile-based personality questionnaire (OPBPQ). This study was conducted based on a quantitative positivist paradigm, utilizing a cross-sectional design. A total of 300 participants from different organizations completed the self-reported questionnaires. The data analysis procedure included item screening, confirmatory factor analysis (CFA), test for common method bias (CMB), determination of convergent validity, and invariance analysis (configural, metric, and scalar). The results showed that the OPBPQ can appropriately predict personality features and is a reliable and valid instrument. The results showed that the personality prediction questionnaire based on an online profile can appropriately predict personality features and is a reliable and valid instrument. The questionnaire can predict personality features using the data that people share on social media. Also, it can assist psychologists in using a new and reliable instrument for evaluating one’s characteristics. The development of a valid and reliable questionnaire can be useful for psychotherapists, employees, and researchers for the purposes of helping clients and organizations.

The existence of bubbles in the market, especially the capital market, can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country. On the other hand, due to the goal of investors in achieving a portfolio of high returns with the least amount of risk, the need to pay attention to these markets increases. In this research, with the aim of maximizing return and minimizing investment risk, an attempt has been made to form an optimal portfolio in conditions where the capital market has a price bubble. According to the purpose, the research is of applied type, and in terms of data, quantitative and post-event, and in terms of type of analysis, it is of descriptive-correlation type. In order to identify the months with bubbles in the period from 2015 to 2021 in the Tehran Stock Exchange market, sequence tests and skewness and kurtosis tests were used. After identifying periods with bubbles, the meta-heuristic algorithms were used to optimize the portfolio. The results indicate the identification of 14 periods with price bubbles in the period under study. Also, in portfolio optimization, selected stock portfolios with maximum returns and minimum risk are formed. This research will be a guide for investors in identifying bubble courses and how to form an optimal portfolio in these conditions.