سید علی نبوی چشمی

The purpose of this study is to investigate and identify the periods of formation and bursting of speculative bubbles in Iran's capital market by creating a state space model and two-mode switching regime (mode 1 is bubble growth and burst stage and mode 2 is the time of bubble loss) during the period from April 2011 to March 2018. The Oxmetrics 7 software is used to investigate the existence of multiple bubbles and research objective. The results of the study of the state space switches confirm the bubble of the capital market in Iran during four periods in the research domain. The life span of the first speculative bubble is 2 months from October to November 2011, the second is 8 months from March to October 2013, the third is 3 months from December 2015 to February 2016, and the fourth period of bubble is 5 months from August to December 2017. Therefore, the result of the research stipulates that the stock index of the Iranian capital market in the realm of research time period has had 18 months of bubbles and has spent 66 months in balance.

The purpose of this paper is to examine the impact of internal and external factors on the ratio of outstanding claims in those banks which are accepted in Tehran Stock Exchange. For this purpose, we used the data obtained from 8 banks and credit institution active in the Tehran Stock Exchange and using data regression panel.  The present survey was examined over the period 2011 till 2015. The study includes three external variables (inflation, GDP and interest rates) and two internal variables (rate of return on assets and the size of the bank). The results of the hypothesis study showed that the rate of inflation, GDP and asset returns had significant negative effect on the ratio of outstanding claims. The results also showed a positive significant impact of the interest rates on outstanding claims, but there was no evidence to prove a significant impact of the banks size on outstanding claims.

In the research, pattern explanation of micro and macro variables on return on stock trading strategies has been dealt with. Based on data collected, existence of momentum and contrarian strategies in Tehran Stock Exchange market has been studied. To collect data and make statistical analysis, Excel Spread Sheet software, and statistical SPSS and R software packages have been used. Through usage made of various statistical models, the relationship between variable of return on stock and other variables added has been studied so that based on which stock trading strategy would be predicted, for the next 12 months. To do so, three statistical models of autoregressive time series (with no auxiliary variable), linear regression, and Markov-switching have been applied. Using the model’s fit criteria, these three models have been compared and best of them has been selected. Based on selected model, stock trading strategy for the next 12 months has been predicted. Markov model showed that within next 12 months, using contrarian strategy i.e. selling previous winners and purchasing previous losers can be profitable. According to the research findings, from among micro variables (base volume, trade volume, institutional investment, and free float) and from among macro variables (currency and inflation rates), only three variables of the first (base volume, institutional investment, and free float) are effective on stock trading strategy; and, they can be used as auxiliary variables to predict return on stock and to specify stock trading strategy in future as a result.

Proving helpful in an efficient management of cash in order to reach optimal cash and clearly explain relevant optimization policies, this study examined the adjustment speed of cash holding using asymmetric models. The sample consisted of 117 firms listed in Tehran Stock Exchange and their financial details over the 2009-2018 period. Once the optimal level for cash holding was identified, asymmetric models such as the dummy variable approach, the quadratic model, and the threshold regression model were employed to test the adjustment speed of cash holding. The results revealed that cash-rich firms are moving toward optimal cash at a greater speed than cash-poor firms. In addition, the results from the quadratic model showed a non-linear, skewing effect of the cash holding adjustment speed in terms of the different cash levels. Therefore, there is an optimal level of cash holding that enables firms to deviate from the cash target. Should firms fall outside the optimal cash range, cash adjustment will occur at a greater speed, and it will be both partial and asymmetric.

The research was conducted with the aim of designing a model of brand experience with the citizenship behavior of customers in the banking industry. The research method is qualitative and grounded theory, and it is considered fundamental in terms of its purpose. The statistical population of the research is Tehran banking industry managers with the highest education, experience, authorship, and ideas. In this research, unstructured and in-depth interviews were used to collect data and information. Data and information analysis were done through coding (open, axial, and selective coding) and MAXQDA software. In the end, a qualitative model is presented, which consists of causal conditions (Appropriate internet infrastructure, The emergence of new media, Creating a new form of communication, The proliferation of media, and Internet penetration rate), the main phenomenon (Branding, Brand experience, Brand personality, and Brand interest), intervening conditions (Building trust, Outsourcing, Customer behavior, Customer emotional attraction, Islamic banking, and Advertising), the contextual conditions(Customer behavior, Reproducibility of experience, Communication with customers and Notification), strategies (Accounting system, Systematic control, Low profit and help business, Electronic banking, Human Capital, Speed of service, Structure modification, Networking, Security, Creating competition and Personnel training) and consequences (Brand quality, Originality, Function, Customer satisfaction, and Customer loyalty).