real estate

This study aimed to identify, extract, and classify the factors and requisites influencing the development of Real Estate Investment Trusts (REITs) using a qualitative research method. A systematic review was conducted, examining 1,869 relevant studies published over 23 years (2000-2023). After applying various filters, 91 studies most closely aligned with the objectives were selected for final analysis. The factors and requisites for REIT development were then classified into 4 overarching and 12 organizing themes. The findings indicated that the factors and requisites for REIT development could be analyzed across 4 broad categories: functional, supervisory and supportive, infrastructural, and structural and governance. The functional aspects included attention to financial and economic indicators, operational processes, investment principles, and risk management. The supervisory and supportive aspects covered legislation, policymaking, and regulatory frameworks. The infrastructural aspects encompassed cultural, educational, innovative, and technological dimensions. The structural and governance aspects involved monitoring of managers, investors, and corporate governance. The use of the meta-synthesis approach in this research ensured a comprehensive and holistic review of both domestic and international studies in this field, facilitating the identification and categorization of the multifaceted dimensions influencing REIT development.

Economic globalization has resulted in an increased competition between the countries to improve their economic indexes. Analyses performed by prominent economists indicated that foreign investment is one of the most sustainable and reliable resources for the economic infrastructure development and production potential enhancement, which can alleviate the economic problems caused by shortcoming of domestic investment resources. The significant role of Iran’s real estate market in investment stability and preservation of property value that emerged from the socio - economic and legal texture of the country, as well as the considerable population growth that resulted in a profitable real estate investment, have drawn the attention of the foreign investors to Iran’s real estate market. Recent manuscripts have investigated the legal obstacles for foreign investment by individuals and legal entities in Iran’s real estate based upon Islamic Jurisprudence, national security, and legal references, subsequently, verified practical and realistic solutions to the aforementioned predicament. Research Approach:This manuscript is compiled using library and electronic resources, scientific and research manuscripts, and technical papers; the research approach is analytical-descriptive.

Financing is one of the factors of future success for small and medium-sized technology businesses. Because of the immaturity of these businesses, the majority of their assets are intangible, rely on technical knowledge, and lack significant financial and credit records. To control the probable risks, financing systems traditionally rely on patterns based on maximum authentication of physical assets, which do not fulfill the needs of these firms and must be altered. The fundamental purpose of this research is to create a model for assessing and determining the collaterals of technical projects and knowledge-based firms so that finances could be more easily obtained and the risk of non-refunding could be managed. In this research, in the first step, the criteria for evaluating and assessing the intended project and company were defined. By using a fuzzy expert system, the appropriate method of dealing with companies was determined. In the second step, in order to create a learning system, the results of the first step were used as input data in the form of three neural network algorithms implemented in MATLAB software and ANFIS algorithm, with 93% accuracy compared to the input data.

The final neuro-fuzzy model was tested according to the repayment data available in Iran National Innovation Fund. The statistical population included knowledge-based firms receiving facilities. By using The Cochran formula, 103 companies were selected as a sample. The results obtained by testing and evaluating the model, in 85% of cases, could correctly identify the companies' performance in repaying resources and suggest appropriate collateral (Real estate collateral or Bank Guarantees).

The model presented in this study can be used to evaluate, validate, and determine the collaterals of technological projects and knowledge-based firms. It can facilitate their access to financial resources and also help them with managing the attendant risks. It also employs new optimization methods and has the ability to learn.

Real estate investment are characterized by low liquidity and irreversible cost. Real Estate industry is one of the most important industry in occupation. Moreover, its production has the biggest weight in family portfolio.These are important characteristics of real estate markets. Real estate industry has cyclical trend. In recession, investor delay their investment. Traditional capital Budgeting models such as Net Present Value are base on fix assumption and condition. They ignore management flexibility. In this paper residential Projects are evaluated with real options (option to delay) by Black-Scholes and Binomial Lattice Model.These model values managerial flexibility. Experimental results show that project Evaluation with real options outperforms the traditional models such as NPV. This paper studies the optimal timing of investment in an irreversible project where the benefits from the project and the investment cost follow continuous- time stochastic processes. According to optimal investment timing proposed by MC Donlad and Siegel, time to start this Project is 9/5 years from now.

The present study has designed and explained the stock price forecasting model using stochastic processes. The statistical population of the study is all companies of the mass real estate industry in the Tehran Stock Exchange from 1390 to 1398. Data were analyzed in Eviews10 and MATLAB software. Predicting stock price behavior and the whole industry index by autoregressive methods and moving average in terms of random processes showed that the explained pattern can not be used to predict stock price behavior but in some random steps, the forecasting error was negligible. Regarding the forecast of stock price behavior, the last three steps of the process, winter have a significant effect on stock price forecast; But the first step has a significant effect on predicting the behavior of the industry index. In the first steps, the error of predicting the behavior of the industry index is very small and the explained model can be used to predict the behavior of the index in the first months of the year.

Recently, real option analysis has gained attention as an effective valuation method for complex real estate projects in developed countries. However, considering its potential, this method has not become as popular as it could have among developers in the country. One major reason may be its complexity and perhaps lack of finance knowledge and real estate data among Iranian developers .Thus, case studies can demonstrate the effectiveness of any theory and introduce real option analysis to Iranian devolopers as a standard valuation method. In this paper, case study analysis is used to examine the application of real options in real estate development projects. Comparison of valuations using traditional discounted cash flow with real option analysis brings out the relevance of real option methods in project decisions.Binomial method that values the project as a compound call option has increased the payoff of the project by 14% in comparison with net present value.