FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES)
Year:2017 | Volume:10 | Issue:34|Papers Count:7

Several studies about microstructure noise in capital markets have found that it is a vital aspect of a liquid market. In the absence of noise traders trading volume would severely decrease. However, on the other hand, market microstructure noise deviates prices from their fundamental values. In this paper, we separate the microstructure noise from the price process and then we ask whether high frequency estimates of microstructure noise contain a risk factor and whether that risk factor is priced in the market, meaning that stocks that covary with our high-frequency measure of noise tend to get compensated in the form of higher returns. We examine this question through a portfolio switching approach by looking at the returns of portfolios sorted on our high frequency measurement of the magnitude of the market microstructure noise. The results show that the portfolio corresponding to the highest quartile noise outperforms the portfolio with the lowest quartile noise.

Certainly, information is one of the most important factors in financial markets and stocks trading. Information symmetry is among the basic principles of an efficient market which is milestone in price clearance mechanism. Also, information risk is a considerable factor for investors in the stock markets. Existence of private information can cause increasing of investment risk. Information risk is a very important factor in trading of stocks that have low liquidity and low transaction numbers. Therefore, ignoring private information and information risk in this stocks’ trading, can cause irreparable losses.This work aims to investigate information asymmetry and information risk in Tehran Stock Exchange via using information risk models. Volume-Synchronized Probability of Informed Trading market microstructure model (VPIN) is one of the newest methods of calculating information risk in financial and stock markets. Intraday information of the active companies is used to compute information asymmetry for the stocks of Tehran Stock Exchange.

In its most basic form, overconfidence can be summarized as unwarranted faith in one’s intuitive reasoning, judgments, and cognitive abilities. The objective of this study is to examine the effects of this important bias on decisions of investors. Here, besides measuring various aspects of overconfidence (mis calibration, illusion of control, optimism about future, better than average effect, volatility estimation), the relation between individual overconfidence aspects and three performance measures including trading volume of individual investors, number of orders and individual return has been tested. The result shows correlation coefficient of 0.747 with99 percent confidence level between overconfidence and number of orders. Also correlation coefficient of 0.695 with99 percent confidence level exists between overconfidence and order volume and finally more overconfidence does not result in more individual returns.

Developments for investigation in the area of artificial intelligence and machine learning, especially in the field of evolutionary computation not only enabled us for having more effective analysis of data, but also providing the ability to use it for understanding any underlying model of financial markets. Economists, statisticians, and finance teachers were always interested in the development and experiment of stock price behavioral models. XCS is a compound system of genetic algorithm and reinforcement learning, which has on-line interaction with the environment and the ability of learning from its own experience. In this study we will provide a model which predicts the movements of next day‘s stock price on one of the corporations in Tehran stock exchange based on historical data and different technical indicators by using XCS. Then, efficiency of the proposed model was measured in comparison with the random walk model. Results showed that the proposed model has more predicting accuracy in comparison with that random walk model.

In this paper, with the aim of examining the feasibility of Credit Risk+ methodologyon the evaluation of bank' scredit risk, we try to estimate the risk of Refah Bank’ scredit portfolio. For this purpose, we use existing data on the number of default (default here means the transfer of the facilities granted to the headlines of bad debts) and carry out some statistical calculations. In this attempt to achieve a clear vision about credit risk assessment, we use data on the number of default in different years and also elementary statistical methods such as mean and standard deviation of default for classical estimation of default risk of bank's credit portfolio. Then by using advanced methods based on actuarial modeling, mean, standard deviation and also the type of distribution is estimated precisely.

Project finance investments are a key backbone for a wide range of sustainable and bankable new infrastructures; being long term investments, they are highly exposed to inflation risk, which in Public Private Partners hips is mostly borne by the private counterpart and its backing lenders. Prompt monitoring and resilient contractual designed as inflation risk detection, man Project finance investments are a key backbone for a wide range of sustainable and bankable new infrastructures; being long term investments, they are highly exposed to inflation risk, which in Public Private Partners hips is mostly borne by the private counterpart and its backing lenders Prompt monitoring and resilient contractual designed as inflation risk detection, management and mitigation, together with proper and flexible financial modelling, alleviating its potentially is erupting impact, especially if unpredictable or chronically enduring. Inflation risk periodically emerges as an extreme-albeit hardly perceived-event, to which infrastructural investments especially in developing countries are particularly vulnerable, creating disrupting agency costs among different take holders. An increasingly wide target audience of both practitioners and academics is interested in the precocious detection, assessment and management of this relevant interdisciplinary problem, so as to find resilient solutions able to mitigate its potentially devastating systemic repercussion segment and mitigation, together with proper and flexible financial modelling, alleviating its potentially disrupting impact, especially if unpredictable or chronically enduring. Inflation risk periodically emerges as an extreme hardly perceived-event, to which infrastructural investments especially in developing countries are particularly vulnerable, creating disrupting agency costs among different take holders. An increasingly wide target audience of both practitioners and academics is interested in the precocious detection, assessment and management of this relevant interdisciplinary problem, so as to find resilient solutions able to mitigate its potentially devastating systemic repercussions.

Today analysis of financial markets as a part of the capital market and its impact on development and portfolio design and investment strategy of each country has become an important and most critical issue. The aim of this study was to investigate how the connection and distribution of stocks related to 30 large companies index of Tehran Stock Exchange and the effects of relationship between clusters of related stocks to every industry. In this study, using a variety of methods of hierarchical clustering, structure, classification and hierarchy of the stocks in the year 1393 reviewed. The results showed that With a focus on each of the hierarchical clustering methods and their implementation on the target stocks, were identified different clusters of stocks due to the similarity and economic relationships and also the key clusters and the vital stocks in the desired set were obtained. The results indicate that the choice best hierarchical clustering algorithm for clustering stocks depends on the desired purpose of cluster analysis and consideration of the advantages and disadvantages of each method.