This paper examines the causal relationship between stock prices and macroeconomic aggregates in Iran, by applying the techniques of the long–run Granger non–causality test proposed by Toda and Yamamoto (1995). We test the causal relationships between the TEPIX Index and the three macroeconomic variables: money supply, value of trade balance, and industrial production using quarterly data for t...

Stock Exchange Investors have paid more attention to the banking group in recent years so that in many cases, the direction of the banking index has changed the general direction of the market. Therefore, exploring the banking index fluctuation is important from the point of view of investors as well as the direction of the market. The purpose is to examine the effectiveness and direction of ne...

This study examines the impacts of real exchange rate fluctuations on the companies' strategic investments in Iran. The data of 92 listed companies in Tehran Stock Exchange during the period of 2002-2015areused. First, the volatility of exchange rate is estimated by the Generalized Autoregressive Conditional Heteroskedasticity (GARCH). The model is estimated by GMM and system GMM methods. The r...

since the 1970s, services marketing has grown into a major sub discipline of marketing. it is constantly claimed – but is refuted in the article – that services are now the dominant economic activity in developed countries and keeps growing while the two traditional goods sectors, manufacturing and agriculture, are declining. in today's competitive world, having expertise, knowledge and ma...

the research problem investigated in this paper is modeling volatility and analyzing risk and return’s relationship in tehran stock exchange using garch-family models including garch(1,1), garch(2,2), egarch(1,1), pgarch(1,1), tgarch(1,1), garch(1,1)-m and cgarch(1,1). using the daily returns of tehran stock exchange companies, we focused on two portfolios of all the companies during a 10-year-...

We propose a simulation-based algorithm for inference in stochastic volatility models with possible regime switching in which the regime state is governed by a first-order Markov process. Using auxiliary particle filters we developed a strategy to sequentially learn about states and parameters of the model. The methodology is tested against a synthetic time series and validated with a real fina...