فصلنامه دانش سرمایه گذاری
پیاپی 1 (بهار 1391)

This thesis investigates the day of the week effect in TSE. The day of the week effect is calendar anomaly that has been widely studied and documented in finance literature. This anomaly indicates the repetitive trends or patterns in the time series behavior of stock market.
In this study various indexes of TSE for the period of 1385 - 1388 are examined to specify the probable pattern in trading days of TSE in term of return. Furthermore in this study the daily correlation between main variable of this study are examined.
Various descriptive statistics for the sample are calculated and classified in this research and show obvious differences in the days of the week.
The results of testing in term of compare the day of the week effect in TSE for return are accepted. This study finds that the highest return is occurred in Wednesday. The implicit results of this research are the negative risk premium for major indexes of TSE.

Value at Risk (VaR) is the maximum loss which could be incurred within a given time horizon, except for a small percentage, that its application has sharply increased after the 90s. Parallel to the increase in usage of value-at-risk in risk management areas, validation of VaR measures has gain great importance. In prevalent back testing approaches, returns which are yielded from VaR estimators are not regarded as a criterion. It's may not be desirable for the investors who emphasize on return more than the risk. What distinguishes this study from other researches in the field of back testing VaR estimation models is the simultaneous consideration of actual return and loss(CVaR) which were yielded from VaR estimators as criteria of risk and return that are the primary basis for financial studies. On the other hand, due to relativeness of risk and return in terms of investors, we considered the weight of these two indexes as fuzzy. In this paper, we constitute and optimize our risky portfolio with safety-first investor's rule. We need to estimate quantile of risky portfolio's return in objective function of safety-first investor's rule to optimize the portfolio. VaR estimators were used to calculate it. On the other hand, given the non- convexity of VaR function and also other reasons, we applied one of the most popular meta-heuristic models namely genetic algorithms for optimization. Our findings show that GEV and HS models are more conservative than parametric models (t-student and normal) and also have better performance in portfolio optimization. The empirical findings also indicate that safety-first investor will choose significantly different amounts of borrowing. Thus, the scale of the risky portfolio and the amount borrowed is diverse across methods. There is another interesting finding. Despite the computational simplicity of historical simulation method, it has shown the best performance of all.

Macroeconomic factors are important for multifactor asset pricing at the industry level. Apart from oil prices, the market portfolio is a significant pricing factor in all industry excess returns. Exchange rates are also an influential factor for excess returns.
This paper aims to examine the impact of crude oil prices and exchange rate on industry relating to petroleum stock returns. Multifactor static and dynamic models consider crude oil and exchange rate as pricing factors in the industries excess returns from 1384 to 1388. The macroeconomic factors comprise the market portfolio, oil prices, and exchange rates.
Oil prices are an important determinant of returns in all of the studying industries. The findings also suggest oil price movements are persistent. Nonetheless, the proportion of variation in excess returns explained by the one to three lagged oil prices appears to have significant for just oil products industry and one month lag is significant for plastic industry and finally no legs are significant for remaining industries.

In this paper the new model of Locally Stationary Wavelet (LSW) processes is introduced which is based on reconstruction of functions using wavelets. This model creates a new class of time series that can have a non-stationary behavior. It is observed that, LSW model has a construction similar to moving average model. Finally time series data for Consumer Price Index (CPI) of the country (Iran) in a definite time interval is investigated using this model .

The purpose of this paper is research affect Tobin q ratio and Revenue growth rate on the level of investment.The order One handrered companies from Tehran Stock Exchange (1381-7) have selected for they research. Company’s have Tobin q ratio to two groups from Tobin q ratio point of view that are firms with a Tobin q ratio smaller than One and firms with a Tobin q ratio greater than One. The regression test results showed that; for the total of firms, Tobin q ratio has significant affect on the level of investment,but Revenue growth rate has significant affect on the level of investment. Also results showed that; for the of firms with q 1 Tobin q ratio has significant affect on the level of investment.

The goal of the present article is extending and developing Multiple Disciminant Analysis (MDA) method which is able to distinguish buble price in Tehran stock exchange. The principal goal of the present study is to offer model for approximating buble price and also the factors efficient to make the model work at Tehran stock exchange. In order to do so by applying separation method a sample consisting of 397 companies accepted at Tehran stock exchange were selected and information related to their price and volume of trades during years 2001 until 2009 were collected and then through performing runs test, skewness test and duration correlative test the selected companies were divided into 2 sets of with bubble price and non bubbled companies. In the next stage by investigating cumulative return process and volume of trades in bubbledted companies, the date of starting bubble price was specified and in this way the multiple discriminant analysis, and by using information related to size of company, clarity of information, ratio of P/E and liquidity of stock one year prior bubble price; a model for forecasting bubble price of stocks of companies present in Tehran stock exchange were designed. At the end the power of forecasting model was studied by using data of test set. Whereas the power of forecasting MDA model was 90.2%; the model has high power to anticipate bubble price.

Choosing the strategy of investing in stock markets holds a special amount of importance. Amongst them there are two main strategies: Value Investing and Growth Investing. Identification of the financial ratios which are capable of separating these two strategies hold a special amount of importance for researchers of stock markets and investors, since it helps them to have a better perspective of the stocks’ performance, and thus to use better and more suitable procedures to choose prosperous stocks and gain higher level of returns.
This research examines the operation of value and growth stocks in Tehran Stock Exchange. For this purpose the portfolios of the value and growth stocks based on the ratios of six factors model of Haugen as well as P/E ratio for the duration of 2004-2009 are collected, utilized and evaluated. Then the results of these portfolios are compared with the growth percentage of stock index.(as bullish and bearish index).
The results indicate that, in the years of bullish market, the value portfolios and in the years of bearish market, growth portfolios have shown higher returns.