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 the firm's life cycle factor) with corresponding conventional multifactor asset pricing models in explaining stock returns.
To this end, Dickinson's cash flow 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 the maturity stage and firms in other firms' 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 the 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 the 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. 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 the firm's life cycle compared to test assets formed without the firm's life cycle. The addition of a firm's life cycle factor improves the performance of conventional multifactor pricing models in explaining stock returns.