Volume 6, Issue 23 (Summer 2018)                   IUESA 2018, 6(23): 35-54 | Back to browse issues page

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Zolfaghari M, Faghihiyan F. An extraction and Analysis of the Return Risk of Real Estate Industry, (Based on Value at Risk Based on Markov Approach). IUESA. 2018; 6 (23) :35-54
URL: http://iueam.ir/article-1-958-en.html
1- Assistant Professor, Department of Economics, Tarbiyat Modarres University, Tehran, Iran , M.zolfaghari@modares.ac.ir
2- Master of Economic Sciences, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Abstract:   (246 Views)
Today, any attempt to invest in any economic activity, requires the knowledge and access to some components of its activities. One of the important components of investment is knowledge about investment risk according to the expected return in that activity. One of the main areas of investment in the country is investment on housing, which could take place directly or indirectly (through financial markets). In this regard, the importance of awareness of the risk in indirect investment on the housing sector considering to the nature of the financial markets is more necessary. But despite the importance of knowledge about risk, quantification methods developed for the past few years have not had much development. Therefore in this research we proposed a new model for measuring the share return risk of companies in real estate industry. This model is not only able to cover much of the shortcomings of current methods, but also able to extract the risk of stock returns in different states. The present model has been designed based on the "value at risk" and using the Markov process on parametric methods. This mechanism, in addition to taking into account the risk regime transfers is designed based on a set of models that they have got a variety of normal and abnormal distribution functions based on symmetric and asymmetric behavior. The results showed that the return of the company’s stock in housing sector follows form regime transfers and has got the GED distribution based on asymmetrical models.
Type of Study: Research | Subject: Special
Received: 2017/11/18 | Accepted: 2018/05/12 | Published: 2018/07/31

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