Portfolio Optimization of Listed Industries in Tehran Stock Exchange using Orthogonal GARCH
Subject Areas : Financial Economics
sahar abedini
1
(
Department of Economics,, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran.
)
esmaiel abounoori
2
(
Department of Economics, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran
)
Gh. Reza Keshavarz Haddad
3
(
Department of Economics, Faculty of Management and Economics, Sharif University of Technology, Tehran, Iran.
)
Keywords: G11, G32, Orthogonal GARCH, Mean-CVaR, Keywords: Portfolio Optimization, Mean-Variance JEL Classification: C61,
Abstract :
Abstract The development of financial markets and the stock market play an essential role in economic development. Considering that financial markets are always associated with risk and uncertainty, and shocks and turbulence in one market affect other markets, therefore, one of the main objectives of this research is to identify the type of distribution of financial series (stock returns of different industries) and estimate their uncertainty and risk (turbulence), determining the weight of stocks in the investment portfolio, as well as accurately identifying how the volatility changes and the intensity of correlation and interactions between the stocks of different industries over time in order to maximize the interests of investors and provide the necessary solutions to planners and policy makers Investors are for managing and developing the stock market.In order to optimize, statistics related to the weekly price index data of selected industries (mass housing, banks and credit institutions, chemical, automotive, pharmaceutical and basic metals) have been used. For this purpose, using orthogonal GARCH model and weekly data of stock price index of different industries in the period March 27, 2010 and January 18, 2021, the elements of the variance-conditional covariance matrix were estimated, Then, the stock portfolio was optimized using the obtained information and the distribution of general hyperbolic (GH) skewed t, in the framework of the static and dynamic classical Mean-Variance model as well as the static Mean-CVAR model. The results of fitting (estimation) of the data distribution show that the return distribution of the price index of the studied industries follows the distribution of the general hyperbolic skewed t; Based on the dynamic classical mean-variance model, the highest weight in the stock portfolio in the study period was related to the pharmaceutical (0/6336) and chemical industries (0/3539), respectively.
فهرست منابع
هاشمی نژاد ، محمد و عبداللهی، محمد رضا (1395). پیشبینی ریسک مالی. شرکت اطلاعرسانی و خدمات بورس: انتشارات بورس
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