جستجوی مقالات مرتبط با کلیدواژه "volatility" در نشریات گروه "حسابداری"

The current research examines the factors affecting the uncertainty of stock investors based on the time asymmetry of profit announcements.

This is a descriptive-correlational research and the statistical population of the research is the companies that are members of the Tehran Stock Exchange, 107 companies between 1388 and 1400 were the basis of hypothesis analysis. The research hypotheses were tested using the ordinary least squares method and with the help of Stat Plus software.

The results of the hypothesis test show that the time asymmetry of profit announcements can neither reduce the volume of transactions nor increase the volatility of transactions, while it does not have a negative effect on price discovery.

It can be said that the time asymmetry of profit announcements has no effect on the aforementioned variables, and therefore this variable can be left out in future research or its effect on other variables can be investigated. Therefore, the variable is not considered meaningful and important.

Today, competitiveness and maintaining competitive advantage is a condition for survival and a means to achieve optimal performance in companies. The performance of the company is one of the most important criteria for measuring the success of commercial companies, and along with financial resources, they are important indicators in the evaluation of an economic unit, which are used in financial decisions, securities valuation models, and methods of evaluating capital plans. Ai and... have a central role. On the other hand, due to the variety of customer demands, intense competition, globalization and financial weakness, businesses have become a more complex environment, which affects the performance and policies of different managers to deal with uncertainty and environmental changes. The purpose of this research is to investigate the effect of financial weakness on the dynamics, development and performance in the conditions of competitiveness and complexity of the companies' environment. Therefore, 147 companies admitted to the Tehran Stock Exchange in the years 2012 to 2014 were selected. To collect data and information, using the library method, by referring to financial statements, explanatory notes were made. In order to analyze the data, multivariate regression test and Eviuse software were used. The results showed that financial weakness has an effect on the development and performance of the company, the volatility of industry returns; In addition, the complexity of the companies' environment has a moderating role on the relationship between financial weakness, development and company performance. Also, the optimal management of cash and financial flexibility of companies in the competitive product market can lead to the preservation of valuable investment opportunities for companies, which ultimately leads to the improvement of the company's performance and value. be made

The current research was conducted with the aim of investigating the relationship between stock returns and volatility with the liquidity of the stock market during the outbreak of the Corona disease in companies listed on the Tehran Stock Exchange. The research method is descriptive, in terms of practical purpose and in terms of the type of post-event information collection. The statistical population of this research includes all the companies admitted to the Tehran Stock Exchange, which have been determined using the systematic sampling and elimination method for the period between 2018 and 2019, which is 133 companies. Multivariate regression analysis and statistical tests such as Durbin-Watson, Shapiro, Dickey and variance inflation factor have been used to analyze the data and test the research hypotheses. Finally, Fisher's test was used to check the significance of the regression line equation, and Student's t-test was used to check the significance of the coefficients. The data related to research variables after being collected in Excel software have been analyzed using the statistical software Eviews. The results of the hypothesis test showed that there is a significant direct relationship between stock returns and fluctuations with the liquidity of the stock market during the outbreak of the Corona disease.

In this study, we investigate the differentiated effect of changing Financial transaction tax on liquidity and volatility among small, medium and large companies. For this purpose, the companies admitted to the Tehran Stock Exchange are divided into three sectors based on market value, and by using the reduction in the share transfer tax rate in September 2018, the changes in trading volume, liquidity, volatility and price efficiency are evaluated and compared for three portfolios, small, medium and large using high frequency data in the period from July to November 2018. The findings show that effects of reducing stock exchange tax on market quality measures are inversely related to the size of companies. In other words, relative to large companies, the tax reduction would further reduce the volatility of small companies and would increase the volume of transactions, liquidity and price efficiency of small companies. Therefore, it can be said that overall, the desirability of tax reduction has appeared more on small and medium-sized companies, and it seems plausible to reduce or exempt smaller companies in stock market from the financial transaction tax. This result could be very enlightening for the design of policies related to small and medium enterprises.

The purpose of this study is to investigate the relationship between the disclosure of forward-looking information and the volatility of stock returns in companies listed on the Tehran Stock Exchange. This research is applied in terms of purpose and descriptive in terms of cognition method and is in the category of quasi-experimental, correlation and post-event researches. The statistical population of the study includes all companies listed on the Tehran Stock Exchange. The statistical sample of the research includes 114 companies during the years 1391 to 1397 that have been selected through systematic elimination. Necessary information for theoretical foundations and research background has been collected using the library method. In order to collect the data required to measure the research variables, the new Rahvard software as well as the information available on the website of the Tehran Stock Exchange have been used. The research hypotheses were tested using multivariate linear regression model and the combined data was performed using the ninth version of Ives software. Research findings show that there is a relationship between disclosure of forward-looking financial information and volatility of stock returns.

The present study aim is modeling and comparing predictive power of GARCH models in forcasting stock returns volatility in Tehran Stock Exchange. Therefore was selected time period from 03/20/2009 to 03/19/2017 based daily returns of total price index (TEPIX) including 1900 observation and reviewed GARCH ، EGARCH ، PGARCH ، GJR ، GARCH-M ، FIGARCH and FIEGARCH models with time series approach and under the normal distribution assumption and evaluated Predictive performance of those models based Mean Squared Error (MSE), Median Squared Error (MedSE), Mean Absolute Error Statistic (MAE), Root Mean Square Error (RMSE) and Theil Inequality Coefficient (TIC) measures. The results showed the FIGARCH models have least error In terms of three criteria MSE, MAE and RMSE Which shows the Fitness of this model is better than all other models to predict the volatility of stock returns. It was also found that returns of the total stock price index (TEPIX) have cluster volatilities which means that with low fluctuations, have small volatility in subsequent periods and severe volatility with high fluctuations.

The Stock Market is Largely Influenced by the Flow of News and Information. In an Efficient Stock Market، Reaction of Investors to the News and Information appears to be a Correct Response. While in an Inefficient Stock Market، Reaction of Investors seems to be Overreaction or Underreaction. Neither in Overreaction nor Underreaction، Stock Price is being Defined Correctly. Through Overreaction modeling of Stock Market processed by Intraday OHLC Prices، which Refer to Open، High، Low، and Close Stock Prices، it is proven that Stock Market Price shows a Geometric Brownian Motion. Then Overreaction and Underreaction is shown to be identified through recognizing the Standardized Volatility Distribution. Furthermore، Discontinuous Flow of News and Information is introduced to extend the Model with more Realistic Assumptions. Two Statistics and Hypotheses are then organized in order to test the Overreaction into good and bad News; ultimately، to ascertain the Results not affected by the Heteroscedasticity، Hypotheses need to be tested again by the Modified Statistics.

Today one of the main problems of oil-exporting countries is severe dependence on oil revenues. The existence of volatility of oil prices and the uncertainty which stems from it exacerbates the problem. Therefore, the investigation of the consequences of oil price volatility on different sectors of the economy, particularly the country's capital markets which represent growth of economic activities, is very important and vital. In this paper, we examine the effect of oil price volatility on investing strategies. Our sample is the listed companies in Tehran Stock Exchange during the period 1379 to 1389. To measure the impact of oil price volatility on investment strategies, GMM (Generalized moment method) is used. Empirical results showed that there is a U shaped relationship between oil price volatility and firm investment.

Stock prices are one of the most volatile economic variables and forecasting stock prices and their returns has proved very challenging, if not impossible. In this paper, we apply a battery of linear and nonlinear models to forecast the returns in nine international stock exchanges for the period 1998-2008. The models are random walk, historical mean, moving average, exponentially something, AR, and GARCH  class  models including ARCH, GARCH, GJR- GARCH" and EGARCH. Volatility is defined as within- month standard deviation of continuously compounded daily returns (log-returns) on the indices of main stock exchanges. We compare the forecasting results of the eight major international stock exchanges with the Tehran stock exchanges (TSE), where the market is highly regulated and therefore less subject to volatility. To evaluate the forecasting results, we use three symmetric loss functions including the mean absolute error, root mean squared error, and the mean absolute percentage error.
Results suggest that the GJR- GARCH model provides the superior forecasting    performance   in   comparison    with   other   volatility forecasting models in international exchanges. However, the simple smoothing model provides superior performance in TSE.  While random walk model provides the worst performance for international exchanges, it is a good performing model, second in order, in TSE. Historical average model provides the worst performance and ARCH class models do not rank high in forecasting competition for TSE.