جستجوی مقالات مرتبط با کلیدواژه « قیمت سهام » در نشریات گروه « اقتصاد »

One of the basic dimensions in the discussion of financial instability is the volatility of asset prices. The reason for the change in asset prices is not only the policies of the central bank, but examining its impact interprets an important part of its changes.
In this research, based on the method of Bayesian averaging and principal component analysis, the monetary policy index effective on the stock price has been determined and through the TVP-FAVAR model, the effect of this variable on the stock price has been investigated in MATLAB software.
According to the results, the changes of one standard deviation in the monetary policy index over time on stock prices have been U-shaped. Changes of one standard deviation in the monetary policy index had a positive and strong impact on stock prices in the beginning to the end of the period.

The present research aimed to investigate the relationship between Iran’s stock price index and nine macroeconomic variables during 1996–2019. Three methods were employed to reduce uncertainty, namely three Bayesian averaging methods (BMA, BMS, BAS), weighted average least squares (WALS), and Vselect. The experimental results of the Bayesian methods and WALS showed that the exchange rate and the consumer price index are the most important variables among the nine macroeconomic variables considered in the model. Moreover, the results revealed that the exchange rate has a minor impact on the stock price index, while the stock price index exerts a substantial effect on the exchange rate. The findings of Vselect validated the conclusion that these two variables are the primary drivers of stock price estimation and are present in nearly all predictive modelsIntroductionThe harmonization of financial markets with the macroeconomic sector is crucial for stabilizing the economy and achieving the adopted policies. In recent years, several significant studies have been conducted on financial markets, particularly the stock market, highlighting their pivotal role in allocating capital resources efficiently in advanced economies. Empirical evidence supports the view that financial markets have evolved in tandem with all sectors of the economy. Therefore, it can be argued that financial markets constitute one of the most vital components of any country’s economy. Throughout history, major economic crises have resulted from the collapse of financial markets, which underscores their critical significance. The financial market comprises several components, with the stock market being a crucial part. Economists view it as a barometer of a country’s economic health due to its ability to reflect macroeconomic asset prices more accurately than other markets. The uncertainty surrounding stock prices in stock markets is a significant aspect of the entire economy, capable of generating and disrupting unsustainable growth. For investors, the risk of participating in an investment is a crucial consideration. To comprehend total risk, it is beneficial to examine two aspects: systematic and non-systematic risk.The present study aimed to examine the impact of economic factors on stock market prices in Iran with the high degree of risk involved. There is a consensus among economists that asset prices are responsive to economic news, and that stock prices and economic factors are strongly interconnected. Thus, this research investigated the potential impact of macroeconomic factors on the Iranian stock price index from 1996 to 2019 using Bayesian averaging methods, followed by an analysis of the effect size of each variable through the weighted average least square method (WALS).Materials and MethodsResearchers often draw conclusions based on the assumptions of their selected model, assuming that it can accurately predict real-world situations. However, this approach may overlook true uncertainty, leading to non-conservative conclusions. Statistical models comprise two parts: variables and assumptions, and the model selected based on these assumptions to estimate the variables. Uncertainty exists at both levels. For instance, a researcher estimating the impact of influential factors on an independent variable may choose a model based on their assumptions and report their estimates. But is this the best answer? Another researcher with different assumptions may opt for a different model with lower variance and error. In other words, numerous models may fit the sample data equally well but with different coefficient estimates and standard errors. Bayesian model averaging (BMA) is a robust method that aims to remove uncertainty. It assesses the robustness of results to alternative specifications by computing posterior distributions for coefficients and models. This study employed three models of BMA, BMS, and BAS, using various averaging methods to verify the reliability of the results. Moreover, two non-Bayesian methods, namely WALS and Vselect, were used to select the best variables for predicting the optimal models.ConclusionThis study tried to investigate the relationship between Iran’s stock market index and nine macroeconomic variables during 1996–2019 by using the models that identify and limit uncertainty. The models selected include three Bayesian averaging models as well as WALS and Vselect which were used to verify the results obtained. The results indicated that only two variables, the exchange rate and consumer price index, are statistically significant when assuming a uniform distribution of the prior distribution function, which is the assumption of the BMS method. The remaining variables are not statistically significant. Furthermore, the estimates derived from the BMA and BAS models were quite similar, with the exception of less important variables. However, the similarity decreased in the BAS method. Moreover, WALS and Vselect confirmed the results obtained from all the three methods.

Predicting stock prices is complicated; various components, such as the general state of the economy, political events, and investor expectations, affect the stock market. The stock market is in fact a chaotic nonlinear system that depends on various political, economic and psychological factors. To overcome the limitations of traditional analysis techniques in predicting nonlinear patterns, experts over the last two decades have used intelligent techniques, especially networking. They have used artificial neural networks and genetic algorithms to improve stock price forecasting. This study, considering the increasing development of forecasting methods in financial markets and also, since stock price is one of the most important factors influencing investment decisions and its forecasting can play an important role in this field, In this research, an attempt has been made to provide a model based on which the movement of the stock price can be predicted with high accuracy. Accordingly, a hybrid model for predicting stock price movement using artificial neural network is presented. For the statistical sample, the top companies of the stock exchange in the second quarter of 1399 have been selected. Then for each purpose, 32 variables were calculated. These variables are the input of the model and are optimized using the artificial neural network algorithm. The results show that the model performs much better in predicting the movement of stock prices and has a higher accuracy compared to traditional methods.

In recent decades, the role of the capital market and the expansion of financial markets had a relatively high relationship with the economic growth of countries. Countries such as America, Japan, England, South Korea, Singapore and other developed countries have made great use of these financial markets and especially the stock exchange for economic development and growth. In this research, by conducting the ARDL test in the period of 1991-2020, we investigated the long-term and short-term relationships between the variables, with a one percent change in the variables of liquidity and consumer price index, respectively, 26. 4.0.34% will be added to the stock price index of Tehran Stock Exchange. the coefficients of all variables can be interpreted at a significant level of 5%. with a one percent change in the variables of liquidity volume and consumer price index, 1.46, 0.52 percent will be added to the stock price index of Tehran Stock Exchange, respectively. Meanwhile, with a one percent change in monetary base variables and financial development, the stock price index of Tehran Stock Exchange will decrease by 0.86% and 0.67%, respectively. it can be said that with increasing liquidity and after that, the price level increases, the value of assets and production inputs of companies and economic institutions increases. If the price increase of listed companies' products is more than the growth of production costs, the profits of companies will increase and inflation from the future cash flow channel of earnings can have a positive effect on stock prices.

This paper aims at investigating the asymmetric impact of long-term and short-term macroeconomic variables on the capital market prices of Iran.Macroeconomic variables are inflation, exchange rate, non-oil trade balance and crude oil prices. In order to investigate these relationships, the quantile autoregressive distributed lag (QARDL) method introduced by Cho et al. (2015) has been used. For this purpose, monthly data related to Iran's economy in the period 2008: M9-2021: M6, have been used. Findings show that in the short run, the macro variables used except the trade balance and oil prices have an asymmetric effect on the capital market price index. In the long run, all variables except oil price have an asymmetric effect on the stock price index and the effect of oil price is symmetrical and significant. This conclusion shows that in situations where the stock market price index is in a state of prosperity, recession or normal, except for oil prices, the effect of research variables on this index is not the same and even this effect is different in the short and long term.

Causal relationships and dynamic interactions between macroeconomic variables and stock price index are very important in formulating macroeconomic policies and political policies of a country. In this article, the effect of economic variables on the behavior of the stock price of the company admitted to the stock exchange was investigated. The research method of this article is based on the purpose of the article (examining the effect of economic variables on the behavior of the stock price of a company admitted to the stock exchange) and is of an applied type. An attempt was made in this article; By explaining the theory and designing a model and using the econometric methods of the TAR threshold self-return model, the effect of economic variables on the behavior of the stock price of the company admitted to the stock exchange was investigated. In reviewing and compiling the subject literature, statistical tables and global databases were used to collect the required statistics and quantitative information. The statistical population of this research is all the economic variables of the research, which are the data of the research variables from 1370 to 1398 (a period of twenty-nine years). The results of the analyzes using the econometric methods of the TAR threshold self-return model, there is a significant relationship between the economic variables and the stock price index in the stock exchange, but in the regime of the behavior of the variables on the stock price index in the stock exchange. Is different.

The present study represents an attempt to examine the main macro determinants of stock prices in OPEC oil exporting and importing countries in the study period 1996 to 2016 using Bayesian model averaging (BMA). The oil importers in this study are the United States, Britain and Japan, and three countries, Iran, Saudi Arabia and Kuwait, have been selected as oil exporters. The findings of this study are that to predict and evaluate the stock price index for oil-importing countries, the three variables of exchange rate index, consumer price index and economic growth should be given more importance than other variables, while for oil-exporting countries, The three variables of broad money growth, exchange rate and import are the most important variables that should be considered. For oil-importing countries, among the macro variables studied, OPEC oil prices have a completely negative relationship with the stock price index of those countries, but in oil-importing countries, the gold price has a completely inverse relationship with the stock price index.

In the present study, the transferring and receiving, as well as the causal relationship of volatilities transmission according to the time-frequency across exchange rate, inflation, housing and stock market in the period of 2006:03-2022:03, is investigated using time-varying parameters vector autoregression model. The results show that the main relationship between the volatilities of the variables was in the short run. If short run exchange rate volatilities continue and lead to inflation and housing volatilities in the medium term, inflation and housing price volatilities will create the basis for transferring volatilities to the exchange rate. The stock market will be volatile with the increase in exchange rate volatility. Therefore, the control of exchange rate volatilities in the short term will prevent the increase of inflation and housing price volatilities. If the policymaker does not consider it, the exchange rate will volatile again in the medium term through the inflation and housing channel. Subsequently, the volatilities will transmit to the stock market intensively.

The purpose of this study is to evaluate the mechanism of monetary transmission through the asset price channel in financial development. In this regard, the impact of monetary policy through housing price and stock price channel has been evaluated by using seasonal data of 110 economic variables during 1991:1-2016:4 and FAVAR model. The results of the impulse response functions indicate that in the medium-term and long-term housing price channel increased production, but also had significant inflationary effects in the short and medium term. Also, given the significant impact of the stock price channel on production, it can be said that the capital market has an important role in directing resources and funds towards productive activities, which ultimately increases investment and production. Based on the results and the significant role of the stock price channel in transmitting monetary shocks to the price level, it can be said that this channel plays a significant role in reducing inflationary effects of monetary policy.

Political economy perspective is about the management of economics by political institutions. Political relations and influence not only affect the financial status of businesses but also influence corporate governance policies in order to achieve the desired goals in different fields. Therefore, the present study investigates the relationship between quasi-governmental companies (an indicator of political economy) and corporate governance policies adopted in companies listed on the Tehran Stock Exchange. For this purpose We extracted data on 113 companies listed on the Tehran Stock Exchange for a ten-year period (2008 to 2017). For hypothesis testing, we used regression model of the panel data. The research results show that quasi-governmental companies show less willingness to select Industry specialist auditor. In addition, the results of the study indicate that auditors are demanding more fees for the greater audit risk of these companies. The results also indicate that the related political companies are trying to reduce the quality of corporate governance in order to hide their political goals from the investors.

Without government intervention, grow and achieve high levels of economic wealth is not achievable. Communities where a relatively high level of economic activity has been monopolized by the state, due to bureaucracy, rent-seeking, corruption and inefficiency, have failed to achieve significant economic growth. Easier to say that the involvement of zero or one hundred percent of the state's economy each different reasons to restrict economic growth. Today, unlike in the eighties, economists on issues such as the size of the optimal size of government and small government are concentrated.This study aimed to measure the effect of government size on yields and stock prices in the Tehran Stock Exchange has been done. For comparison, Italy has also been studied. The results show that the size of government in Iran, the stock also increases efficiency and size of government in Italy although higher stock return is negative.

This study aims at the impact of the variables affecting the stock price changes of 85 companies listed in Tehran Stock Exchange. The investigation was done at different level of profitability during the period 2006-2014 by using panel data and a cross-section model. Modeling the impact of those affecting factors by emphasizing the real value of companies was done based on the real-options-based valuation model. The results indicate that variables such as earnings yield, changes in profitability and changes in growth opportunities have a positive and significant effect on the stock return, but the changes in equity capital investment and discount rates have a negative and significant effect. The effect of changes in the profitability and changes in capital investment on the return stock in companies with a high level of profitability is more than that on companies with a low level of profitability. Based on the incremental explanatory power index, earnings yield provides more incremental information for explaining the stock return than other explanatory variables.

The main objective of this study is to predict the factors affecting the risk of future stock price decline under the Circuit Radius Neural Network Method in companies admitted to the Tehran Stock Exchange during the period from 2010 to 2015. To collect theoretical foundations of the research, library method, books, Dissertations and articles have been used. To collect statistical information financial statements and accompanying notes have been utilized. For the analysis of this study Circuit Radius Neural System and SPSS23 software have been used. The results of the research indicate that predicting the factors affecting the risk of future stock price decline is possible on the basis of the Circuit Radius Neural Network Method. The research findings also show that the unusual optional cost, the opportunity to grow, the abnormal operating cash flows, the capital structure, and the size of the company affect the risk of future stock price decline respectively as the first, second, third, fourth and fifth priority.

Regarding the importance of stock market in the economy, this study examines the effects of fluctuations in oil price and foreign exchange rate on stock exchange price index (SEPI) in Iran. For this purpose, we use the seasonal data of variables under study. i.e., stock exchange price index, black market exchange rate, and oil price, during 1992-2014. We also use autoregressive conditional heteroskedasticity (ARCH) method to compute oil price and exchange rate volatilities. We estimate the coefficients of explanatory variables affecting SEPI using autoregressive distributed lags (ARDL) method and check the existence of long-term relationship among variables using bounds test. Findings indicate that the fluctuations of oil price and foreign exchange rate have significant and negative impacts on SEPI, and inflation and money volume affect positively SEPI.

Securities market and currency market have always been considered sensitive parts of financial market. The relationship between exchange rate changes caused by stock prices and price-to-earnings ratio was investigated in this study by using structural equation modeling method accompanied by partial least squares approach. The primary hypothesis was about the existence significant and positive relationship between exchange rate changes (Dollar and Euro) caused by stock prices and price-to-earnings ratio. The sample of study included 49 companies listed in stock exchange. They were selected at random. The time periods included 132 days studied from March 2012 until February 2012. The size of 49-sample was a total of 6468 institute-days. The findings indicated that there was a positive and significant relationship between exchange rate changes caused by stock prices and P/E ratio in Iran’s financial market.

Stock Exchange is an organized and official market for buying and selling companie's shares base on its own rules and laws. Many factors affect the views of the market parties and the company's stock price. Some of these factors are internal and partly due to factors outside the domestic economy. Paying subsidies is one of the important instruments that influence economic variables with a change in relative prices. In this paper we examine the impact of paying subsidies on the stock price and make abnormal return for oil products industry. Five companies in Tehran Stock Exchange have been selected as a sample. Financial information of these companies were collected from 2008 to 2013.Date of Cash subsidies were considered as independent variablesand creating unusual return and cumulative abnormal return was considered as dependent variables and an indicator for market reaction. The cumulative average abnormal returns compared and tested by Use of Event Study and statistical test (test t). The results showed that there is no significantdifference between the abnormal return on the stock for oil products industry before and after the payment of subsidies. On the other hand, the results showed that there is a significant and meaningful difference between average cumulative abnormal return before and after of cash subsidies.

Purpose of this study is to examine the relationship between stock price and exchange rate by considering the oil price in oil-exporting countries. In order to examine the co-integration between variables, Pedroni and Kao tests are performed. In addition, FMOLS and DOLS tests are performed on monthly basis data to obtain long-run vector coefficients over 2009 – 2011 period. Furthermore, Short-run relationship between variables are examined by pooled mean group (PMG) test based on vector error correction model (VECM). I can be inferred from the results that there is co-integration between variables in the long-run. The long-run coefficients indicate a positive relationship between stock price and exchange rate and a negative relationship between oil price and exchange rate. Moreover, the results from PMG test demonstrate mutual causality between all the variables.

One of the main features of regulation of structure is alteration of planned economy to the market economy. In Iran، this alteration accomplish with privatization and free investment through the implementation of Article 44 of the constitution. Therefore، one of the key factors in this regard is value relevance of accounting information for buyers. Value relevance of accounting information indicates the relevance and reliability of accounting information. So it can be used as an indicator for the quality of accounting information. Therefore، in this study we examine the effect of the general policies of Article 44 of the constitution on improving value relevance of accounting information within a 9 years period (from 2004 to 2007، 4 years before and from 2008 to 2012، 5 years after notice of Article 44 of the constitution) in Tehran Stock Exchange. The research sample was consisted of 84 firms، the independent variable of the study is stock market price and dependent variables are earnings per share، book value of shares، and operating cash flow (as a representative of basic financial statements). The results of the analysis of assumptions indicate that implementation of Article 44 of the constitution impresses the relationship between stock prices and earnings per share، book value of shares، and operating cash flow in Tehran Stock Exchange. In general، the results show the improvement in value relevance of accounting information after the implementation of Article 44 of the constitution.