FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES)
Year:2018 | Volume:10 | Issue:36|Papers Count:9

Ordinary investors do not look to their portfolio as a whole. These investors consider their portfolio as a set of mental arithmetic. In mental accounting, the conventional issue of maximizing the expected return is faced with the constraint of maximum likelihood to fail in achieving the return threshold. The present study extracts the capital asset pricing model from Markowitz Mean-Variance Portfolio Model and risk-free asset entering the limitations of this model. Then, MA-CAPM model is extracted by creating a mathematical equivalence between the components of this model and the limitation of mental accounting. In this model, expected investment return for any purpose presented in the form of mental arithmetic is a function of the return on risk-free asset, beta and risk premium of mental arithmetic where the risk premium of mental arithmetic equals the difference between returns of each account and risk-free return on assets. Expected rate of return on assets in the MA-CAPM will be influenced by return threshold and likelihood to fail in reaching this threshold, i.e. mental arithmetic risk.

Technical trading strategies assume that past price trends predict future ones. Their application may be profitable if the past trend reflects fundamental information that has not yet been fully priced. However, if the trend merely reflects temporary pricing pressures, technical trading will presumably fail. We argue that using financial statements as an additional source of information helps to avoid such failure. We implement a trading strategy that uses operating cash flows to identify enduring past price upturns and composite with momentum and contrarian strategy. In this study, using panel data, the impact of technical and fundamental strategies independently and in combination on stock returns 90 companies listed in the Tehran Stock Exchange, in the period 1387 to 1392 were studied. For this purpose, the stock return as dependent variable and momentum, reverse and operating cash flow are considered as independent variables. The results show that due to the timing and strategies have been used to form portfolios, hybrid strategy is best returns.

Tehran Stock Exchange has not lived and somewhat inefficient. Mechanisms and rules governing this market is still not implemented in such a way that the quality of data and information provided by member companies to deliver optimal. and suffered not because of pricing errors. Probably the most attention of users of financial statements, the income statement is focused on the lowest row. In the eyes of most, profit accounting tool for making logical decisions. The hypothesis of this study are as follows: First hypothesis: Earnings Persistence on the absolute value of the excess return a negative influence. The second hypothesis: Earnings Predictability on the absolute value of the excess return a negative influence. Hypothesis: smoothing on the absolute value of the excess return a negative influence. The fourth hypothesis: quality accruals on the absolute value of the excess return a negative influence. Finally, considering conditions and above limitations, among all companies accepted in Tehran Stock Exchange, 86 companies were selected during 2005 to 2015. Also, to analyze data and estimate research models, ordinary squares regression model of panel data in common effects method, permanent effects or random effects are used. In this regard, to analyze data and calculate research variables, excel software 2010, and perform statistical tests, and for final analyses, views software, version 7, were applied. In general indicates that measures the quality of earnings on excess stock returns based on Fama and French three-factor model, taking into account the trend of stock prices of listed companies on Tehran Stock Exchange, is impressive. In this study of four indicators to measure earnings quality, earnings stability, predictability of earnings, accruals quality and smoothing was used as the four hypothesis that the effect of these measures on additional efficiency gains from the difference between the real Return expected return achieved was measured and the results of the test showed that the hypothesis were accepted theories, the literature cited in the literature and theoretical framework also matched.

Market growth and financial instruments, the complexity of financial markets and investment categories of specialization requires investors and employees of financial markets, the tools, methods and models used in the selection of the best and most appropriate investment to its full portfolio What help. This led to theories, models and various methods for pricing financial assets and predict stock returns discussed and every day is developing and changing. This study aims to add momentum to the five-factor test a new model to explain stock returns in Tehran Stock Exchange is expected. Thus, the sample consisting of 108 companies during the years 1389 to 1393 were selected. To test the hypotheses, a hybrid approach to data analysis and multivariate regression were used. The results showed that the addition of momentum to the five-factor model does not increase the explanatory power of the model, but the five-factor model of Fama - French than five factor model and acceleration, more power to explain the expected return on stocks. The findings showed a much empirical validity of five factor model than other models in anticipation of the expected return on stocks.

Value at risk (VaR) risk assessment and diagnosis method that uses standard statistical techniques that are routinely used in other technical fields, is used. The contract, the value at risk in a given period the maximum expected loss at a given confidence level is measured. This article is designed to measure a sequence of high-risk deals with the calculation of Liquidity-adjusted Intraday (LIVaR). Hence, our goal is clear review aspects related to the size of the company's internal liquidity. With the reconstruction of classified information, and significant changes in real output and efficiency without friction (planned) occurred and these two variables were modeled jointly. Risk related to planned cash expenses, was determined at a later stage.

Stock price prediction is a classic problem that has been analyzed by different tools and models. Stock market trend changes depends on supply and demand rule and other macroeconomic forces in the market circumstance. Non liner and full swing process makes it hard to predict future stock price. Traditional statistical techniques and models cannot explain seasonal and non-station time series data in stock markets. Hidden markov model has widely used in the way of predicting statistical time series. It extensively has used in such majors as speech recognition and DNA sequencing and also it can be used in order to next stock price prediction. In this study we tried to use discrete hidden markov model to predict next day’s index in Brussels (Euro Next) and answer the question that "which market will get the more accurate prediction by hidden markov model?

In this study a model based on Constant Market Share (CMS) is presented in order to be applied by bank top mangers due to obtaining a proper method to appraise region managers performance. The mentioned method make the macro elements of variation in deposits and facilities into their phenomenon which causes them. A holistic view is that considering three major factors vary the amount of deposits and facilities which are: 1. Effects caused by financial and monetary policies that bank cannot have and sort of influence on them, 2: those provincial effects mainly are traits of an specific area, bank is not able to make intangible change on them, 3: making competitive advantages, it indicate the extant of region manager’s effort. This research is going to separate the three aforesaid effects then apply the method in an Iranian private bank. Results show that region managers have not has better performance comparing other competitors.

This study examines the financial accelerator theory of Bernanke and et al (1999) for Iran economy using a Dynamic Stochastic General Equilibrium (DSGE) model. In this regard, a DSGE model with financial and banking sectors in the New Keynesian framework is designed, calibrated and simulated and the results are compared with standard DSGE model without financial sector for the quarterly data of Iran during 1371 to 1390. To examine the financial accelerator theory, the impulse responses functions of proposed model are compared with standard model. The results show that, the proposed model has better ability to fit the Economy of Iran than the standard model. The impulse responses functions analysis show that the impact of deposit rate shock on the real sector variables within the proposed model is greater and more persistence and need more time to settlement than standard model. So the theory of financial accelerator is accepted in the Economy of Iran.

In recent years, financial markets, and especially the capital market has been a significant expansion in the international and country levels and sudden changes in economic behavior and perception of investors of the market situation affected. The main problem in choosing the optimal portfolio optimization assets and securities that can be provided with a certain amount of capital. Although minimize risk and maximize return on investment comes in plain view, but in practice has been used several approaches to portfolio optimization.In this study, to determine the optimal portfolio based on canonical correlation analysis on companies active in the Tehran Stock Exchange during the year 1394 were discussed. Methods cross-sectional study of a sample of 42 companies included in the index returns daily adjustment of the top 50 companies in the period is three months. Based on canonical correlation analysis showed, 42 samples in the form of two pairs of canonical variables, each linear combinations of the daily rates of return were, were adjusted and petrochemical allocated and the remaining 155 units will be assigned in other industries desired.