فصلنامه دانش مالی تحلیل اوراق بهادار
سال شانزدهم شماره 57 (بهار 1402)

This study empirically had examined the effect of business cycles and investment strategies on return asymmetry. The statistical population of research consists all of companies listed in Tehran stock exchange market during 2014 to 2019 that a number of 118 companies were considered as statistical sample of research. The research method is causality type, the method of gathering information in literature is based on library research, and in the part of hypothesis, testing is based on documentation. Generally the statistical method had been used in this research is based on combinational data regression method and analysis of variance tests. Results showed that boom business periods cause positive skewness in stock returns and recesion periods cause negative skewness in stock returns. The results also showed that return skewness-based investment strategies did not have a significant effect on portfolio return skewness, but portfolio performance in terms of return and Sharpe ratio for return skewness based strategies was significantly better than other strategies. Succeeding in the stock market of companies, like any other market, requires choosing the right approach and maintaining order. Without these, investing will be just unplanned sales that make the investor's profit or loss more dependent on luck than on skills such as research perseverance, analytical power, decision-making ability, and patience to achieve goals. And things like that. Among the various approaches to investing in the stock market, diversified portfolio formation is recognized as a passive but relatively reliable method. Using this method reduces the amount of risk and keeps the return on investment at a level close to the total market return.

Incorrect valuation refers to a situation in which the stock price of companies in the capital market differs from its intrinsic value. Incorrect valuation of companies in the capital market considered as a phenomenon that originates from the shortcomings of the capital market. The purpose of this paper is to examine the role of stock issuance; Firm growth and stock turnover on the relationship between stock price misevaluation and firm innovation. The spatial domain of this research was the companies accepted in the Tehran Stock Exchange and the temporal domain was the years between 2013 and 2019. In this paper, the wrong valuation of the independent variable stock price and the innovation of the dependent variable company considered. In the data section, the research done by collecting the data of the sample companies by referring to the financial statements, explanatory notes and the stock exchange monthly. Based on the systematic elimination method, 147 companies selected as a statistical sample. In order to analyze the data, non-linear panel data method has been used. The results showed that the wrong valuation of the stock price has an effect on the innovation of the company, in addition to the issuance of shares; Company growth and stock turnover have a moderating role on the relationship between stock price misevaluation and company innovation.

This research point is to check the approach of analyzing social networks to form the investment optimal portfolio in Iran’s equities market. This research based on surveying-exploratory of the gathered sectional data. This research has been done in three phases, which includes studying theoretical basics and the literature review, exploratory research, Delphi method and using a questionnaire through a process that was completed in 20 levels. In qualitative part and in respect to Delphi 15 experts in the first phase and 25 experts in the second phase interviewed. For quantitative approach, 384 persons considered as the total sample of persons to be taken into account for Cochran formula and sampling method. The results showed that, assuming all the other conditions are constant; the investors were not affected by the political news in social networks, but were affected by the economical and corporate news.

Financial development and stability and their relationship with economic growth are important and influential issues on economic growth. Therefore, economic experts have investigated this issue in many researches by applying various conditions. The purpose of this research is to investigate the effects of financial development, economic stability and efficiency of government cooperative contracts during recession and prosperity, which done by applying the Markov switching regime change approach based on the annual data of Iran's economy during the period of 2016-2018. The results of the model estimation show that the variables of financial and oil crises, economic and financial risk, inflation in both periods of prosperity and recession have a negative effect on the efficiency of cooperative contracts. The results show the probability of transition from one regime to another regime and the duration of the regime, if Iran's economy is in a recession at time t, it will remain in the same state despite economic and financial risks and financial and oil crises. Also, there is a 0.80 probability that Iran's economy will return to the state of recession due to other factors. The amount of exposure of Iran's economy to the period of stagnation in the current research is 21 periods against 9 periods of prosperity.

The purpose of this study is to provide a model for the development of technological startups for the dynamics of external organizational governance mechanisms. The research was in terms of developmental purpose, in terms of combined method (qualitative-quantitative). The statistical population in qualitative research included theoretical and experimental experts who were purposefully selected, including 20 senior managers of industrial companies of the stock exchange It was Tehran and sampling continued until theoretical saturation was achieved. In a small part, the statistical population included top, middle managers and supervisors of industrial companies of Tehran Stock Exchange, sampling done purposefully and 80 questionnaires obtained from this sample. The collection tools were semi-structured in the qualitative part of the interview and in the quantitative part of the researcher-made questionnaire (1400) which was based on the Likert scale (5 options). Research data analysis performed in the qualitative phase with Max Kyoda software and in the quantitative phase with LISREL software. The results in the qualitative section indicate the variables of strategic thinking, marketing mix, market opportunity identification and competitive functions as causal factors. Underlying factors include values, macro-environmental factors, and the emergence of new technologies, global approaches, and technological infrastructure. The consequences of this phenomenon expressed in the form of development of technological startups, value creation for businesses, technological advancement, value creation for society and revival of small businesses. In the quantitative part, the conceptual model of the presented research was tested and the research hypotheses confirmed. The development of technological start-ups for the dynamics of external governance mechanisms leads to synchronization and coordination with global changes and the external environment with the internal environment of the company and leads start-ups to gain a competitive advantage that is the basis of any company and can it created value for society and businesses.

Today, beyond classical financial / behavioral theories, biorhythm science as a set of emotional causes: Perceptual and even physical, can be considered the basis for financial and investment decisions. In fact, this science is based on a sinusoidal diagram of a person's state according to the person's position in one of the positive points; Negative and critical shows that can be considered effective on individual decisions. The purpose of this research is evaluating the difference between investors biorhythmic internal rotations with the formation of portfolio based on value stocks. This study was conducted in a period of 6 months separately and 2 months in the form of 4 periods of 15 days to investigate the differences in biorhythmic internal rotations of institutional investors. In this study, 60 institutional investors in the form of 4 groups of 15 people in order to be in three cycles of physical biorhythm; Emotional and subjective were selected and analyzed through multivariate MANOVA tests, ANOVA with repeated measure and repeated measures analysis of variance and post hoc tests. The research tool was to measure the formation of value stock portfolio, the ratio of book value to market value and the separation of companies' stocks into two parts: growth and value, and to measure the biorhythmic internal rotations of investors from Biorhythm software (Biorhythm-365) used in Android and IOS operating systems. The results showed that investors who are in the positive zone in the mental and emotional periodicity tend to use value stocks to form more portfolios than investors who are in the negative and critical zone.

Pair trading strategy is one of the oldest and most common statistical arbitrage strategies. Pair formation is an important step in pair trading that examined manually and this method fails in the multivariate mode and does not consider conflicting goals in the problem structure. The main problem in this study is to present a method that creates multivariate pair combinations with multiple contradictory goals and focusing on the integration approach. Therefore, a combination of stocks optimized for two opposite objectives risk (mean-reversion) and return (spread variance) to form a set of profitable multivariate pair trading opportunities. The statistical population is companies listed on the Tehran Stock Exchange. The statistical sample limited by the need for high-frequency transactions from the top 50 companies. The problem developed in the form of a mixed integer-programming model (MIP), and due to non-convex constraints and exponential space, a multi-objective genetic algorithm used to obtain pair combinations. To achieve multiple goals, an advanced type of genetic algorithm; The Chaotic Non-dominated Sorting Genetic Algorithm (CNSGA-II) was used. The Chaos theory used to create the initial population of the genetic algorithm in order to obtain appropriate and high-precision solutions. Research has shown that the use of chaos theory can increase the degree of convergence in evolutionary algorithms. The results of the experiments of this study show that multi-objective pair trading strategies focusing on the integration approach have a significant advantage over the traditional single-objective model.

This study investigates the effects of arbitrage asymmetry and limits-of-arbitrage to explain the observed idiosyncratic volatility return premium in the Tehran Stock Exchange. The sample includes 90 companies listed on the Tehran Stock Exchange from 2008 to 2022. For this purpose, a comprehensive index of limits-of-arbitrage has been constructed based on three measures of arbitrage risk: transaction costs, noise trader risk, and information uncertainty. Furthermore, a mispricing measure has been constructed based on three anomalies: asset growth, gross profitability, and momentum. These measures and anomalies capture the main features of the Tehran Stock Exchange. To test the research hypothesis, the three-way portfolio sorting and the Fama-Macbeth cross-sectional regressions conducted. The empirical findings show that the idiosyncratic volatility premium is positive for both overpriced and underpriced stocks. Within the high limits-of-arbitrage stocks, the positive idiosyncratic volatility return premium is higher for overpriced stocks than for underpriced stocks. Consequently, the limits-of-arbitrage and the arbitrage asymmetry can explain the positive idiosyncratic volatility return premium in theTehran Stock Exchange.

After the severe price fluctuations in the capital market in 2019 and the increase in the activity of the stabilization fund in the country's capital market, doubts were raised about the way of interference and conflict of interests in the activity of this fund. In this research, Iran's capital market stabilization fund has been studied in terms of its nature, function, disclosure, and type of sources, applying a comparative approach with market stabilization funds in China, Germany, and Bangladesh. Then, by referring to the opinions and comments of experts and academicians, defects, problems, and deficiencies of the capital market stabilization fund have been identified and the optimal alternative status has been drawn. The findings of this research, which was conducted by a qualitative method and integration of comparative study and in-depth interviews with experts, indicate that the optimal method for capital market stabilization fund investments is the indirect method through financial institutions. On this basis, the proposed research model is presented in the form of a conceptual model with the aim of providing a suitable alternative solution for fund intervention in the capital market.

The main goal of the current research is to provide a model for measuring the stock price bubble with a behavioral approach. The present research method is a descriptive survey. The statistical population consists of two groups, in order to determine the factors related to the model, the first group consists of 10 capital market experts, and the second group consists of active companies admitted to the stock exchange, which were used for the model test. ANP has been used to prioritize the identified behavioral factors. The calculations performed to determine the priority of the main criteria show that the heterogeneity of investors with a normal weight of 0.128 has the highest priority. Speculative behavior, mass behavior and mental accounting are in the second to fourth place, respectively. Also, the results of the second part show that considering that the statistical population of the research consists of all the companies active in the stock market between 2012 and 2019, 143 companies were selected as a sample based on systematic elimination. Eviews software and logistic regression were used to test the hypotheses. The identified behavioral factors include speculative behavior, behavioral volatility, investor heterogeneity and market expectations. The results show that behavioral instability, heterogeneity, market expectations, as well as speculative behavior have a positive effect on the occurrence of stock price bubbles; Therefore, it can be stated that behavioral factors can have a positive effect on the formation of the stock price bubble; Therefore, the identified pattern has the necessary efficiency from the behavioral point of view.