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Showing 7 results for Stock Market
Application of Wavelets and Fractional Brownian Motion in Weak Efficiency Hypothesis of Testing in Tehran Stock Exchange
Ahmad Jafari Samimi, Roozbeh Balounejad Nouri,
Volume 5, Issue 17 (10-2014)
Abstract
The main objective of this study was to investigate weak efficient market hypothesis of Tehran stock exchange. For this purpose, total  price index, financial index, industry index and the index's top 50 companies data for the period 2013:7-2009:5 daily basis as well as data on prices and yields for the period 2013:2 - 2000:3 are applied on a monthly basis. In this study, the hypothesis of the poor performance of the Tehran stock exchange, using wavelets and fractional Brownian motion is investigated. The results show the aforementioned hypotheses are rejected.
The Test of Multiple Price Bubbles in Tehran Stock Market: an Application of the Generalized Supremum Augmented Dickey–Fuller
Ahmad Jafari Samimi, Roozbeh Balounejad Nouri,
Volume 6, Issue 21 (10-2015)
Abstract

Given the importance and role of capital markets in the economy, its characteristics have been regarded by researchers in this field. Hence, the main purpose of the present study is testing the existence of multiple price bubbles in Tehran stock market. For this purpose, the monthly data on the total price index and price-dividend ratio for periods 2000 – 2013 has been used. In this study generalized supremum Augmented Dickey – Fuller test, which has been recently introduced, is used due to critical review of conventional methods of testing the bubbles and also the possibility of a multiple bubble in time series. In addition to the testing of multiple Bubbles, with using this method there is the possibility of determining their period of creation and decay. The results showed that in the period under review, in the period 2003:3 - 2003:5 and 2004:12 - 2005:7 hypotheses price bubble in the stock market is confirmed.


The Effects of Monetary and Fiscal Policy Shocks on Stock Market of Iran
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Volume 6, Issue 22 (12-2015)
Abstract

In recent decades the development of capital markets in developing countries, economic growth is desirable to have. Developed countries owe much of its development direction of financial markets, especially the stock market knows. The stock market is precisely the collection of savings and private capital to finance investment projects and on the other hand, an official and is confident that the owners of dormant savings can be relatively affordable and safe place to seek investment and their funds to invest in companies operate. The role of the stock market to boost the economy of countries like Iran and wandered from one side to the large amounts of capita and on the other hand, face a shortage of investment, is striking. Therefore, understanding the factors influencing the behavior of the stock market can be considered useful for the capital's economy. In this context, this study examines the impact of fiscal and monetary policy shocks on stock market Iran. Regression model to estimate the structural model and the data for seasonal 1991: 1-2010: 4 was used. The results of the model indicate that the short-term shock to the money supply (monetary policy instrument) and long-term government spending shocks (monetary policy instrument) Fluctuations of stock price indices explain. In other words, the impact of monetary policy on stock prices faster than the impact of fiscal policy. Because government spending through the stock market affects ,First government spending on aggregate demand and thus income consumers and the general level of prices affects subsequent stock price changes, but by changing the money supply, the faster people can spend their surplus cash available to purchase the stock of assets that form part of it. The lag effect of monetary policy is much shorter than the lag effect of monetary policy


Stock Market Fluctuations and Monetary Policy in Iran
Sahar Bashiri, Mosayeb Pahlavani, Reza Boostani,
Volume 7, Issue 23 (3-2016)
Abstract

This paper investigates the relationship between monetary policy and stock market fluctuations for Iranian economy within a DSGE model. This study models the role of monetary policy in two monetary regimes including money growth and Taylor rule with traditional factors and optimal simple rule in the new Keynesian monetary framework with nominal wage and price rigidities in the Iranian economy. Bubbles in our model emerge through a positive feedback loop mechanism supported by self-fulfilling beliefs. Results show that: first, using an optimal simple rule and determining the optimal coefficients of the Taylor rule by policy makers decrease the loss function. Second, the sentiment shock which represents the size of current bubbles relative to newly born bubbles and transfers to the real economy through endogenous credit constraint, drives the movements of stock market fluctuations and variations in real economy, leading to explain the positive contemporaneous correlation between stock prices and the real economy Third, using an optimal simple rule and determining the optimal coefficients of the Taylor rule with stock price Fluctuations by policy makers decrease the loss function and it confirms that monetary policy should respond to stock market bubbles in the economy.


The Impact of Monetary Policy on the Stock Market Returns and Instability: Comparison of Monetary Policy Tools in Iran
Qholamreza Rezaei, Hamid Shahrestani, Kambiz Hozhabre Kiani, Mohsen Mehrara,
Volume 10, Issue 36 (6-2019)
Abstract
After the recent financial crisis, especially the financial crisis 2008, This raises the important question of what is the role of monetary policy in occurrence and  prevention of the financial  instability? so, this paper investigate the dynamics impact of monetary policy on the stock market returns and instability using Structural Vector Autoregression (SVARs) model During the period  1992:q2 to 2017:q1. In this study, the effect of monetary policies via the various monetary tools used by the Central Bank on the stock market is studied. to illustrate the performance of monetary policies, the four variables of weighted interest rate, monetary base growth rate, bank reserve ratio, and growth of commercial banks' debt to the central bank have been used as monetary policy tools.  The results of the impulse response function(IRF) show that monetary policy tools do not affect the stock market returns and instability. The results of the Forecast Error Variance Decomposition (FEVD) also show that the share of monetary tools in explaining the changes in stock market returns and instability is insignificant and less than ten percent each. Although, the monetary base share is higher than the others, so the central bank's policy tools do not has a particular impact on the behavior and instability of the stock market.

Comparison of Complex Networks of Stock Markets and Economic Variables in the Period Before and After the Outbreak of Coronavirus (Covid-19)
Matin Saneifar, Parviz Saeedi,
Volume 11, Issue 40 (6-2020)
Abstract
The corona virus has turned a health crisis into an economic crisis and its spread has led to strong negative reactions from stock markets in various countries and price fluctuations in many macroeconomic variables. On the other hand, the spread of the virus provides a basis for examining the effects of its prevalence on stock markets, economic variables and the power of influence and the speed of information dissemination in times of crisis in these markets. The aim of the present study was to investigate the effect of corona virus on the stock markets of 75 countries and the variables of oil, gold, silver and copper by comparing complex networks before and after the outbreak of the virus. Also, for the calculation section, matlab statistical software has been used and for drawing the networks, the maximum filtered flat graph method has been used with the help of daily data in the period from June 2019 to March 2020. the results show that before the outbreak of coronavirus, stock markets tended to move in small continental groups, but the outbreak of the virus led to negative group movements with high correlation for these markets, positive or negative information spreads 32% faster than before on the stock market network, also stock markets are twice as influential as they were before the outbreak. The corona virus has directly led to a 40% drop in stock markets. on the other hand, the virus has caused fluctuations in the global variables of oil, gold, silver and copper, which each respectively affected 55%, 32%, 28% and 35% of stock markets, the impact of these variables before the outbreak of the virus was 31%, 20%, 16% and 18% of stock markets, respectively.‌ it is important to note that in crises due to the collective movements of stock markets, price stability in central stock markets and macroeconomic variables are very important to control and reduce the negative effects of the crisis on stock markets.

Modeling Stock Return Volatility Using Symmetric and Asymmetric Nonlinear State Space Models: Case of Tehran Stock Market
Mojtaba Rostami, Seyed Nezamuddin Makiyan,
Volume 11, Issue 41 (10-2020)
Abstract
Volatility is a measure of uncertainty that plays a central role in financial theory, risk management, and pricing authority. Turbulence is the conditional variance of changes in asset prices that is not directly observable and is considered a hidden variable that is indirectly calculated using some approximations. To do this, two general approaches are presented in the literature of financial economics for modeling and calculating volatility. In the first approach, conditional variance is modeled as a function of the square of the past shocks of return on assets. Models of the GARCH type fall into this category. In the alternative approach, volatility is assumed to be a random variable, which evolves using nonlinear patterns of Gaussian state space. This type of model is known as Stochastic Volatility (SV).  Because, SV models include two kinds of noise processes, one for observations and another for hidden, volatility, thus, they are more realistic and more flexible in calculating volatility than GARCH type.  This study attempts to analyze the volatility in stock returns of 50 companies, which are active in Tehran Stock Market using symmetric and asymmetric methods of Stochastic Volatility, which is different in the presence of leverage effect. The empirical comparison of these two models by calculating the posterior probability of accuracy of each model using the MCMC Bayesian method represents a significant advantage of the ASV model. The results in both symmetric and asymmetric methods represent the very high stability of the volatility generated by the shocks on stock returns; therefore, the Tehran Stock market changes in returns due to this high sustainability will be predictable.

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