FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES)
Year:2016 | Volume:8 | Issue:28|Papers Count:8

One of the major functions of exchange is to enhance stock liquidation. If stock market is not cash and liquid, it will not encourage investment. On the other hand, stock market has intensely been affected by the development of advanced computer technologies, which has caused a large volume of trades to conduct online.The present research analyzes the trades conducted in Tehran Stock Exchange from the viewpoint of high-frequent trading (HFT). It also discusses the effect of such trades on market liquidation.Based on this, it studies five major and influential factors on liquidation power, including number of trades, number of buyers, number of the traded stocks, number of trading days and value of the stocks traded in Tehran Stock Exchange between 21 Mars 2011 and 22 September 2012. Correlations between these factors and the variable of the HFTs were tested through multivariate regression and SPSS.According to the results, there is a positive and significant relationship among the HFTs with 3 variables including number of trades, number of buyers and number of trading days at confidence level of 95%. Therefore, HFTs are effective in liquidation power.

The goal of this paper is to introduce a new model to predict the high volatility of Tehran Stock Exchange. For do it, a Markov switching GARCH models was modeled. With Estimating this model, the transition probability matrix of two states of high and low volatility, was calculated. Using this matrix, we can forecast the probability of market fluctuations in the each period ahead and we can obtain a suitable model for forecasting high volatility. According to the model selection criteria consist of AIC and BIC, the Markov regime switching GARCH model with GED distribution is the best model for forecasting volatility in Tehran Stock Exchange. Based on this model, in this paper, an Early Warning System has been introduced in Tehran Stock Exchange. This model can be used for policy makers to prevent the occurrence of high volatility and to increase the security of investors in Tehran Stock Exchange.

Valuation is a knowledge which helps modeling all effective factors in the company’s cash flow, while helping the share holders to determine stock intrinsic value, through discounting company’s cash flow. One objective of a valuation system is to help students simulate changes in a firm’s financial strategies and discover how these changes affect a firm’s credit health or its value. It also simulates all company’s financial affairs, through which the investors could calculate the relative reports on stock intrinsic value efficiency and regulate their transactions, as regards to the expected profit.Moreover, the Managers could also measure their decisions efficiency before the operations and render the highest return (value) to the stockholders.This research is a study over the efficiency of applying deferent approaches of valuation in obtaining the acceptable stock intrinsic value of private banks in Tehran securities exchange. Tentative instances show that discounted operating cash flow model has the most correlation coefficient with actual price of stock.

Investors invest in stock market to gain benefit, so always trying to make a reasonable relationship between the stock price, return and the financial performance; therefore, it is important to identify the effective factors. In this study, effect of investor’s sensitivity, stocks properties and the momentum effect on stocks return and financial performance were reviewed and analyzed over the period of 1386 to 1392. The statistical population of this research study is the companies listed on the Tehran Exchange Stock, and the linear regression was used for assumption testing.Methodology- This research is practical, and has examined effect of investor’s sensitivity, stocks properties and the momentum effect on stocks return and financial performance. For the shareholder’s sensitivity evaluation, the EMSI indicator has been used.Results- The shareholder’s sensitivity indicator depicted that investors had risk aversion great deal of 37.48%, during the period of investigation. Hypothesis test results presented that the sensitivity of the shareholders indicator, the ratio of book value of company to the market value, firm’s size and stocks volatility had a significant effect on stock returns. With studying effect of mentioned factors on the performance indexes, following result indicated: Shareholder’s sensitivity, firm size and the ratio of book value of company to the market value have a significant effect on company’s asset return.Firm’s size, stocks volatility and the ratio of book value of company to the market value have a significant effect on stockholder’s equity return.Firm’s size and the ratio of book value of company to the market value have a significant effect on Tobin’s Q ratio.Shareholder’s sensitivity, firm size and the ratio of book value of company to the market value have a significant effect on the ratio of stock prices to corporate profits.

Financial distress assumption in studies of Chan and Chen (1991) and Fama and French (1992) lead to pricing the risk of financial distress.Ignoring high risk of financial distress in asset pricing model, will lead to positive or negative risk premium on distressed stocks. Positive risk premium occurs when we overreact to the financial distress. Negative risk premium will happen in stock pricing when we under react to the financial distress.Under reaction to the financial bankruptcy, will lead distressed companies to have lower returns and momentum return will continue for next period.This research investigates investors’ behavior in response to the financial distress and momentum for healthy and bankruptcy companies while controlling risk factors: size, Book to market and market cap.The results indicate that investors underreact to distressed companies and momentum occurs in these companies.

The investors should select which stocks to invest that maximize their wealth in the future. The present study attempts to analyze the relationship between fundamental power of stock and real return through developing an overall variable through combination of different fundamental models. This study was conducted for predicting the best intrinsic value for investors. To do this, a sample of 35 companies which listed in Tehran Stock Exchange in chemical, petroleum, and steel industries were survey foreseen financial statemen in 2012. This study, was use for produce fundamental power from factor analysis and for valuation producted fundamental power profitability from Correlation Coefficient. The findings revealed that profitability of fundamental power is resulted from P/E ration and economic value added (EAV) model which has a positive relationship with weekly and monthly return. In addition, The findings also revealed that the use of fundamental power is resulted from Gordon Growth Model (GM) and Free Cash Flow to Equity (FCFE) has not considerable profitability for weekly and monthly investment.

The evaluation of performance in facilitating organizational effectiveness is an important and vital duty. Balanced score cards is a performance evaluation framework with a set of financial and non-financial scales has comprehensive view to organization performance. One of the most important positions of using balanced score cards is banks as the importance part of economy of Iran. The present study at first collects performance evaluation indices of e-banking of Pasargad bank based on review of literature. Then, based on survey of experts of Pasargad bank of Tehran city in the form of questionnaire, 37 indices are selected as final index. By the opinion of experts of Pasargad bank, the indices are classified and final indices are placed in balanced score cards aspects. To determine the weight of aspects and indices, fuzzy analytic network process is applied. Finally, the indices are prioritized and the aspects and indices are prioritized based on importance.

In this study, Quadratic Discriminant Analysis (QDF) model and the hybrid model of Genetic Algorithm based on Artificial Neural Network) ANN-GA) are used to estimate manipulation of stock prices in Tehran Stock Exchange. In this study, first by using screening data method, a sample of 345 companies listed in Tehran Stock Exchange were selected and then information about the ‘ TEDPIX’ index, closing price, volatility of closing price and trading volume in the timeframe years 1387 to 1391 were collected. Afterwards the selected companies categorized into manipulated and non-manipulated groups by using duration dependence test and run test. Then with scrutiny of the trend of Tedpix’s chart and volume chart of the manipulated group, Start of price manipulation is determined. In next step by using Linear Discriminant Function) LDF), Quadratic Discriminant Function) QDF) and Genetic Algorithm based Artificial Neural Network and by using closing price, volatility of closing price and trading volume variables and also using information in range one year before starting manipulation group and in range four years for non-manipulation group, designed models for forecasting manipulation. At the end, the prediction ability of the models was examined. According to the results, the prediction ability of QDF model compared to the ANN model is better.