FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)
Year:2010 | Volume:1 | Issue:2|Papers Count:7

Nowadays, leasing industry is reckoned as one of the strategic choices of economic development. According to leasing activities nature, leasing companies have a great profitability and at the same time with the most risks. Some of the most important risks in leasing companies are credit risk, business risk, residual value risk and exchange risk and among them credit risk is the most important of all. Subsequently making logic relationship between risk and return is the essential element in devotion utilized resources and to guarantee profitability leasing companies.In this paper, base on individual costumers data extracted from Leasing Iran Khodro Company database (since 1381-1384) by using tow sample t-student and determinant coefficient five variables were recognized as factors effect credit risk, they include: net monthly costumer income, loan time, loan amount, net monthly guarantor income and experience. In the next step we design tow credit risk models (Logit & Probit) for leasing loans.Wald, Log likelihood and Wilk΄S Lambda tests indicate that efficiency at Logit model (%98.39) is more than Probit model (%97.44).

This paper assess the relation between amount of reduction in prediction error of accounting profit between any stock profit and cash profit with stock output increase.The aim of this paper is to help stock decision making for investors in Tehran Stock Exchange and also help firm managers for profit prediction in financial year budget then at the end of financial year they could compare the amount of realization of real profit and predicted one and impose required adjustments in cash profit division policies. So the amount of prediction error is important for them. For doing this research data about variables from 78 corporations that have been accepted in Tehran Stock Exchange during years 81 and 85 gathered as a statistics sample and after data processing using correlation method, hypothesis had been examined. The results from hypothesis processing shows that a reverse and meaningful relation exists between the amount of EPS and DPS error with stock returning.Also the outputs show us that the effect of both variables error respect to stock returning is same. With regarding the results, firms should pay attention to amount of prediction error in their profits because they interfere in changes of stock returning and investors and other users pay more attention to these parameters. Firms' managers in their scheduling and budgeting specially in prediction of each stock profit and division profit of each stock, regard the amount of error.

Long term and short term volatility in cash flow, can prepare relevant information in stock return prediction. Always operational cash flow has been one of the most important items in financial statement. Results of different researches indicate that cash flows can influence on investors decision because of including information content. Researches which done by now, have focused on relative and incremental and have had lower intonation on short term and long term cash flow volatilities. This research wants to study information content of short term and long term cash flow volatilities.Cash flows annual volatilities percent relative to prior period considered as short term cash flow volatility (CFVOL1).Operational cash flow variances applied to calculate long term cash flow volatilities (CFVOL5). Statistical population in this research is firms listed in Tehran Stock Exchange (TSE), based on considered condition 50 firms selected over 2002-2009. Panel analyses are used for analyzing data.Findings show that volatilities of short term operational cash flows is a relevant information to predict stock return, while volatilities of long term operational cash flows don’t have meaningful impact on stock return. Other achievements confirm that among control variables like beta, size and BE/ME, just BE/ME have effect on stock return.

Attention and focus on customer satisfaction minimizes the spread of negative messages by unhappy customers. It is worth noting that the existing methods of measuring satisfaction are generally of absolute types while their measuring indices are of inexact (Fuzzy), vague and rhetorical kind the assessment of which using fuzzy approach is closer to human thinking than using exact numbers methods.Therefore, this research tries to assess the factors influencing investors’satisfaction with the content of financial reporting of companies in stock exchange considering the information content using fuzzy and classic approaches.Statistical population consists of individual shareholders in Stock Exchange and data gathering tool is a questionnaire designed by fuzzy approach.Dependent variable is investors’ satisfaction and six independent variables are as follows: relevance of information, reliability of information, comparability of information, understandability of information, preparation costs of financial and non-financial information and non-financial information in financial reporting. One main hypothesis and six sub-hypotheses were presented.Kolmogorov-Smirnov normality test was used for hypothesis testing, (T-test and Z-test for statistical average) to calculate the fuzzy score average of each question, and in the end skewness coefficient and kurtosis coefficient used for Comparison between classic and fuzzy approach.The results show that the content of financial reporting of the companies in Stock Exchange affects investors’ satisfaction. It was also found that skewness coefficient and kurtosis coefficient for fuzzy data are much less than those of classical data. This shows that in this study, fuzzy data are more appropriate than the classic data.

In economic studies of industrial and mine projects, there are many factors as uncertain variables related to the future (sales, demand, net present value and etc). Therefore, such studies should be carried out based on forecasting. To obtain reliable results in these situations, we should use risk analysis methods. One of these uncertainty methods is to employ models to be simulated.One of the methods that can be use in these models is Mont Carlo simulation, in which, some factors as random variables will be studied for the future. Future prediction of each random variable is assessed considering a probability distribution function. The aim of this research work are to describe Mont Carlo simulation and its application in risk and decision management of evaluation industrial and mine investment project and forecast probability economic conditions. The result of this study indicate that: in economic study of each investment project, first, we should recognize the uncertainty variables and distribution function of them, and then with replacing the distribution functions in appropriate cell of financial model of the project, forecasting of future using Mont Carlo simulation and evaluation of risk can be done.

This research investigated the relationship between working capital management and profitability of listed companies in the Tehran’s stock Exchange. Hence the number 86 in the 1381-1386 period studied were selected. In this research have studied the effect of different variables of working capital management including the Average collection period, Inventory turnover in days, Average payment period, Cash conversion cycle on the Net operating profitability of Pakistani firms and Current ratio, Debt ratio and size of the firm (measured in terms of natural logarithm of sales) have been used as control variables. Pearson’s Correlation and regression analysis are used for analysis.The results show that there is a negative relationship between variables of the working capital management and profitability of the firm. It means that as the cash conversion cycle, average collection period, inventory turnover in days and Average payment period increases it will lead to decreasing profitability of the firm, and managers can create a positive value for the shareholders by reducing the cash conversion cycle, average collection period, inventory turnover in days and Average payment period to a possible minimum level.

In this paper study of Heterogeneity in Tehran Stock Exchange concerning technical strategy will be analyzed. Research indicators divided into two categories:1. Trend - following indicators: Which comprised Moving Average (MA) and Exponential Moving Average (EMA).2. Oscillator indicators: Including Relative Strength Index (RSI), Money Flow Index (MFI), and Moving Average Convergence Divergence. (MACD).Achieving the result for this investigation reveals there is a logical and direct relation between stock return of all technical indicators and with Holding Period Return. Ultimate after comparison of average, heterogeneity have been observed in Tehran Stock Exchange. Finally, the maximum and minimum of heterogeneity can be observed in MA and RSI respectively.