JOURNAL OF ASSET MANAGEMENT AND FINANCING
Year:2015 | Volume:3 | Issue:2 (9) |Papers Count:7

This research deals with providing quantitative criterion for optimal diversification of equities in sector funds portfolio. So, firstly divides mutual funds into two groups of sector fund and nonsector funds by considering 0 to 100 percent as top five weighted shares to total assets of fund ratio. Next provides the optimal diversification of equities in sector funds portfolio by the percentage which causes most difference between the ratio of risk to returns of sector funds and nunsector funds.

One of the most important market in each economy in financial markets that is strongly affected by other economic variables such as oil price shocks. One of the most important problems in oil export in country is the volatility and Instability of oil price. For this reason in this Thesis we are intendent to evaluate effect of oil price shocks on the stock market in iran. Fot this reasen we have used One of the most famous time series model, that is SVAR to analysis this shoks. The result of this research shows that the relative importants of oil price shoks in comparation to other variable of the model is not so high.

In this research, we test for the systematic relationship between distress risk and equity returns based on the two measures of financial distress risk, Altman's Z score and the other Ohlson' O score. Also, we test the role of beta, B/M and size factors in explaining the equity returns by the three factor model of Fama and French (1992). For this reason, we use portfolio formation method like Outecheva (2007) and Garlappi and Yan (2011). We use annual data of TSE from 1382 to 1390. Findings show that returns are negatively related to financial distress. On the other hand, BM and Size effects are independent from financial distress risk. So it seems financial distress risk is unsystematic. Also findings show that Small stocks become highly financially distressed more often than companies of bigger size.

One of the issues that always has been considered is selecting stocks for profitable investments in financial markets. If the investor decides reasonably in the stock selection, a return more than the market average could be achieved. Comparing different companies based on the industry which the company belongs to, and identifying the premier industries through analysis of their efficiency could be useful guideline for stakeholders of this field. The main purpose of this research is ranking the stock industry to help the efficiency of capital markets applying the data envelopment analysis. The nature of the model is constant return to scale and input-oriented that 67 companies in 16 industries were studied and finally 7 industries were introduced as efficient and 9 other as non-efficient. Then determining the efficiency boundary, the inefficient industries are ranking and to improve their performance, some units were introduced as reference units.

Predicting stock returns is one of the major issues to be discussed in the financial literature, and investment. Researchers have proposed various methods for predicting stock returns, that the most famous of them are the Capital Asset Pricing Model by Sharpe and Lintner, arbitrage pricing model by ross and three factors model by Fama and French. F& F three factor model as the most significant factor models in recent years great attention has been. Despite having many strengths of this model is based on the assumption of constant beta coefficient is founded, However, this assumption does not hold absolute in any circumstances. In this study, we tried to model with constant or variable coefficients fitted separately and then compare the accuracy each of them. For this purpose, the state space model and ordinary least squares (OLS) models were fit assuming constant and variable coefficients are used. This research will be done on listed companies in Tehran Stock Exchange for a period of 72 months (October 1385 to September1391). The results show that, compared to state-space model of a linear least squares model for predicting stock returns has a better performance, this means that Beta coefficients in three-factor is on the Tehran Stock Exchange are not constant.

In This study we examined the effect of different variables on the return of Iranian mutual funds. These variables include number of unit of mutual fund, banking or not banking of mutual funds, ranking of brokers (the mutual fund managers), size of mutual fund, activity ratio of mutual fund, age of mutual fund, value of issue and revocation of mutual fund, market return. In this research 39 mutual funds in a 24-month period has been studied and the year was between 2011 and 2013. The model parameters are estimated by ordinary Leastsquares (OLS) regression and panel data. Hypothesis test results show that, there is a significant relationship between number of unit of mutual fund, size of mutual fund, activity ratio of mutual fund, age of mutual fund, value of issue and revocation of mutual fund, market return and its returns and there is not significant relationship between banking or not banking of mutual funds and its returns, and the evidence shows that ranking of brokers and Return of mutual funds are not significantly related to each other.

This study aims at exploring relationship between Working Capital Management with criterions for value-based performance. Therefore, the information of 107 companies listed in Tehran Stock Exchange between 2007-2011 (1386-1390) was studied and the effect of various variables for Working Capital Management (including Days Sales Outstanding, Days Sales of Inventory, Days Payable Outstanding, and Cash Conversion Cycle) on criterions for value-based performance (including Economic Value-Added (EVA), Market Value-Added (MVA), and Q Tobin index) was tested through employing 3 hypotheses and 9 subhypotheses all along with the main research question. Test of hypothesis was carried out by multiple regression analysis by Estimated generalized least square (EGLS). Findings of the study show that the increase of Days Sales Outstanding results in the increase of both Economic Value-Added (EVA) and Market Value-Added (MVA), and the increase of Days Sales of Inventory also results in the decrease of criterion for value-based performance of both Economic Value-Added (EVA) and Market Value-Added (MVA).