Earnings management and its techniques are one of the most important issues from the legislative bodies and researchers' perspective. So, knowing the factors affect managers’ financial reporting behavior is attracted a lot of attention. In this research, the earnings management pattern during different phases of firm's life cycle and the role of growth perspective on it are investigated. In this regard, discretionary accruals and cost stickiness are used to measure accrual and real activities earnings management respectively. Life cycle phases also are determined using net cash flow from operating, financing and investing activities. In order to test hypotheses, financial data of 149 firms listed in TSE during 2008 to 2015 are collected with considering some criteria. The PCSE method is run to analyze data. The results reveal managers use almost earnings management through accrual pattern in introductory and decline phases; although, earnings are manipulated through real activities in growth and maturity phases. In addition, an increase in growth perspective leads to increase in accruals level of firms operating in growth and maturity phases.

Objective: This research is aimed at introducing firms' life cycles as a new and effective factor on stock return and comparing the performance of the new multifactor asset pricing models (augmented by firm's life cycle factor) with corresponding conventional multifactor asset pricing models in explaining stock returns. Methods: To this end, Dickinson's cash flows pattern has been used to measure the firm's life cycle. A Firm's life cycle factors are constructed based on the difference in average returns of firms in maturity stage and firms in other firm's life cycle stages. Then, this factor waS combined with the conventional multi-factor pricing model, namely the Fama and French three-factor model, Carhart four-factor model, Fama and French five-factor model and Ho, Xue, and Zhang four-factor model. In the following, using time series regression approach, the performance of augmented multifactor asset pricing models and corresponding conventional ones are compared. For this purpose, the accounting and market data from companies listed in Tehran stock exchange and Iran Fara Bourse between the years 2004 and 2018 and the variety of test assets based on different firm's characteristics were used Results: The results show that augmented multifactor pricing models have a better performance compared to corresponding multifactor pricing models in explaining stock returns and outperformance is more evident when test assets are formed using firm's life cycle compared to test assets formed without the firm's life cycle. Conclusion: The addition of a firm's life cycle factor improves the performance of conventional multifactor pricing models in explaining stock returns.

Capital structure is usually very important for companies especially when they want to finance. This subject can be affected by firm's life cycle stages and company performance. The speed of capital structure adjustment through firm's life cycle and the relationship between profitability and capital structure are investigated in this research. Debt to equity ratio and return on asset are used as proxies for capital structure and profitability respectively. Firm's life cycle phases are measured using cash flow patterns in operating, investing and financing aspects. In order to test hypotheses, financial data of 149 firms listed in TSE during 2008 to 2015 are collected with considering some criteria. Linear dynamic panel data models are run to analyze data. The results reveal that firms which are in maturity phase adjust their capital structure faster than those in introduction or growth phases. In addition, changing life cycle phase decreases capital structure adjustment speed. Focus on the profitability relation with debt ratio shows it diminishes external financing and firm's life cycle phase does not affect it. Changing firm's life cycle, however, makes the relationship more strongly negative.

The main subject of this research is examining and analyzing the relationship between accounting earnings and stock returns based on firm size and lifecycle in companies listed in Tehran stock exchange. Earnings per share and change in earning variables were considered as independent variables, while stock return rates were selected as dependent variables. In addition, firm's lifecycle and size were examined as control variables. In this research, data from during 1383 to 1387 were examined. In order to examine the validity of the research hypotheses, the Cross-Sectional data was employed. Results show that firm's size and life-cycle variables influence the relationship between earnings and returns and trigger an increase in the adjusted R2.

The main purpose of this study is to evaluate the role of the firm's life cycle in measuring conservatism based on some conditional conservatism models. The statistical population of the study is 2008-2009, which includes a random sample of 180 company observations that were divided into three stages of life cycle using Dickinson's (2011) model variables. Multivariate regression technique with cross-sectional data was used to test the hypotheses. Then, using the initial models of conservative measurement, the error values of each model were compared with the error values obtained from the life cycle-adjusted models. The results show that the coefficients of determination in Dichfang modified model are not significantly higher than the original model. However, in the wing models of Shivakumar and Khan Watts, the increase of the coefficient of determination is significant compared to the original model. Therefore, except for the Duchess Tung model, in the other two models, the inclusion of life cycle in the model increases the prediction power of the models.

Risk taking behavior over firm's life cycle and its relationship with financial performance are examined in this research. Life cycle is one of the most important factors which determines properties of firm's behavior and affect its resource structure, empowerments and abilities. So an adjusted version of ROA with regard to industry effect is used to measure risk taking behavior; the pattern of cash flow in each category including operating, investing and financing and ROA proxy are considered to define life cycle and financial performance respectively. As a consequence, financial data for 150 firms during 2008 to 2015 with some considerations is collected. In order to include dynamic behavior of risk taking, generalized method of moments (GMM) is run to analyze data. The results reveal that firms show riskier behavior in introduction and decline phases in comparison with maturity phase. In addition, firms which are in introductory and decline phases operate much weaker than others from financial aspect.

Optimal selection of a company for investment considering its financial ratios is a challenge that is expected to be somewhat simplified by reducing the amount of data. Accurately recognizing the relative importance of metrics in any company is not easy for many decision-makers and investors. The purpose of this study is to provide methods for decision-making that can be implemented without specialized financial knowledge. For this purpose, a sample of 172 companies listed on the Tehran Stock Exchange as a company-year, during the period 2008-2019 was examined. First, the financial ratios were prioritized using decision tree regression analysis (type CART) to predict the life cycle. The results showed that the cash ratio and Debt to Equity Ratio were the most and the least important factors, respectively. Then, using fuzzy hierarchical analysis (FAHP) and TOPSIS, financial ratios were prioritized to evaluate the Financial Performance of companies that leverage ratios and profitability ratios had the highest and lowest ranks, respectively.

Objective: The effect of a firm's life cycle, as a characteristic, on stock return has been documented in the literature. The purpose of this research is to introduce and test "firm life cycle" as a new systematic factor for developing multifactor asset pricing models. Method: Using data of 345 companies listed in the Tehran Stock Exchange (TSE) and Iran Farabourse market during 2004 to 2018, we first show there is a significant difference among returns of companies in different firm cycle stages and that the pattern observed cannot be explained by notable multifactor asset pricing models. Regarding two competitive approaches to explain differences between stocks with different characteristics, namely risk or mispricing, empirical evidence on returns of stocks in different life cycle stages shows that return of mature firms are higher compared to that of firms in other life cycle stages and the pattern is consistent with mispricing of mature firms. Considering these results, five structures for the life cycle factor are proposed, based on the difference in monthly average returns of firms in the maturity stage and firms in other stages. Results: The results of spanning regressions show that none of the notable asset pricing models, namely the Fama and French three-factor model, the Carhart four-factor model, the Fama and French five-factor model, and the Fama and French six-factor model, can explain life cycle factor return. Therefore, the life cycle factor with proposed structures can be used as an additional factor to improve the performance of these multi-factor models in explaining the variation in (expected) stock returns

Cheilanthes persica (Bory) Mett. ex Kuhn. (Pteridaceae) is one of the resurrection ferns that fully dries during drought stress and after re-watering will be revived. Fresh material obtained from Kermanshah province, west of Iran (Tagh-e-bostan) and cultured in growth chamber and its developmental stages and life cycle were examined. The spore morphology was studied. The spore had tetrahedral tetrad with discontinuous microreticulate ornamentation.