درخت حوزه‌های تخصصی

Evaluation of stock portfolio performance is considered one of the important issues in the capital market and investment management in stocks. Proper evaluation of portfolio performance requires recognizing the factors affecting it. The macroeconomic variables are important and effective factors due to affecting the systematic risk of companies. In this research, ordinary least squares method (OLS) was used to evaluate the effect of macroeconomic variables including inflation, interest rate, liquidity growth rate, oil price and currency rate (Rial versus Dollar) on the stock portfolio performance based on traditional and modern network theory. Performance of portfolios including growth portfolio, growth-value portfolio, and value portfolio, and offensive portfolio, indifferent and defensive portfolio was measured based on seasonal data from 2006 to 2016 using the Teriner Index. The research results show that at the error level of 5%, macroeconomic variables have an impact on the performance of both traditional and modern networks. However, the Akaike information criterion for the modern network model is equal to 5.822, which is less than the traditional network value with the value of 6.724. This suggests that the interpretation of macroeconomic variables in a modern network portfolio is better than that of traditional one. In addition, the effect of macro variables on the performance of the six portfolios will be different

The purpose of this paper is investigating the effect of JCPOA on the network behavior analysis of Tehran Stock Exchange indexes using the minimum spanning tree (MST) and hierarchical clustering. By simplifying a complex system, network analysis allows for the extraction of important and essential information from that system. In this paper, using network analysis the simultaneous behavior of 38 industry indexes in Tehran Stock Exchange in manufacturing, service and invest-ment sectors during 2012-2017 was investigated. These analysis included identi-fying the main indexes in the direction of moving other indexes using the MST, providing a classification using hierarchical clustering for the behavioral similarity of the indexes as well as examining the degree of integration (behavioral similarity) of market indexes over time. The results showed that investment, automobile, industry and medicine indexes in the research period had a major role in guiding other indexes and indexes can be classified into six groups in terms of behavioral similarity. The market has also been moving toward integration of indexes since early 2015 and beginning the executive steps of Joint Comprehensive Plan of Action (JCPOA). This reflects the investors' hope for the promotion of all indexes.

With increasing trade among different countries The exchange rate fluctuations, consumption, inflation, and market portfolios are considered as major risk factors in financial markets. Hence this study aimed to examine the relationship between the exchange rate fluctuations and asset returns within a theoretical and empirical model, i.e. Consumption-based Capital Asset Pricing Model (CCAPM). To this end, a basic CCAPM was extended and imported consumables were included in Epstein and Zin’s recursive utility function. The research sample encompassed eight portfolios and monthly data from 2003 to 2014. The pricing model parameters were estimated using Euler's equations and Hansen and Singleton’s generalized method of moments (GMM). An estimation of the parameters of Euler's equations indicates the risk aversion and tolerance of economic factors, low elasticity of substitution for domestic consumables and imported consumables, and high elasticity of intertemporal substitution. In the next step, using Euler’s linearized equations as asset pricing model and Fama and Macbeth's two-step regression method, the effects of exchange rate risk premium, inflation, market efficiency, and consumption growth on return premium on assets were investigated. The results indicated the positive impact of the exchange rate risk premium, inflation, and market returns on the return premium on assets.

Evaluating the performance of companies using their financial ratios is a challenging task that is expected to become more straightforward by reducing the dimensionality of the data. The purpose of this study is to evaluate the performance of companies using a hybrid model for investment-related decision making through which the mean value of various financial ratios are calculated based on the investor's risk-taking behavior so that the number of all criteria is reduced to one single value for each alternative. To do so, a sample of 172 companies listed in Tehran Stock Ex-change was selected from 2008 to -2018. Firstly, the financial ratios were prioritized using decision trees regression analysis (type CART) and TOPSIS Technique. The results showed that Gross Profit Margin and Debt to Equity Ratio are the most and the least important factors, respectively. Then, using OWA (Ordered Weighted Averaging Aggregation) operator, the role of investor’s risk-taking behavior was investigated, and the results showed that investor’s risk-taking behavior changes the outcome of the decision-making process significantly.

Resource-based view (RBV) theory analyzes and interprets company's resources in order to find out how organizations gain a competitive advantage. This theory fo-cuses on the implications of the complicated features of a company as the resources for excellent performance and comparative advantage. According to this view, capa-bilities and resources of the company are the main factors in explaining the func-tional results or competitive advantage. Resources can be considered as inputs which enable companies to do their activities. The purpose of this research is to introduce a resource-based theory for calculating the efficiency score of accepted companies in Tehran Securities Exchange by using Data Envelopment Analysis (DEA). In this regard, the financial statements of 190 companies accepted in the exchange for the 2009 – 2018 period have been analysed. Efficiency indicators, which include 4 categories of resources (10 inputs) and 5 outputs, have formed the axis of the mentioned technique. The results of implementing this model for compa-nies with the efficiency score of one, indicates first a minimal input consumption compared to competing companies in the same industry while producing more out-put, and second, using the resource-based view theory (integration of tangible and intangible resources) enables the company to push the boundaries of efficiency. Finally, it can be said that utilizing minimum and maximum resources simultaneous-ly leads to a focus strategy-type competitive advantage.

This study, attempts to estimate and compare four different models of jump-diffusion class combined with stochastic volatility that are based on stochastic differential equations, and their parameters latent variables are estimated by Markov chain Monte Carlo (MCMC) methods. In the Stochastic Volatility with Correlated Jumps (SVCJ) model, volatilities are scholastic, and the term jump is added to both scholastic prices and volatilities. The results of this study showed that this model is more efficient than the others are, as it provides a significantly better fit to the data, and therefore, corrects the shortcomings of the previous models and that it is closer to the actual market prices. Therefore, our estimating model under the Monte Carlo simulation allows an analysis on oil prices during certain times in the periods of tension and shock in the oil market