A scheme of CAPM models considering distress risk and Firms life cycle

Document Type : Research Paper

Authors

1 PhD student, Department of Accounting, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran

2 Professor, Department of Accounting, Khatam University, Management and Finance, Tehran, Iran

3 Associate professor, Department of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran

4 Assistance professor, Department of Accounting, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran

Abstract

Given the growing complexity of financial markets and the specialization of investment, financial market participants need tools, methods and models to choose the best investment. This has led to a variety of models for capital asset pricing and calculation of stock return forecasting. For this purpose, the researcher uses a theoretical matrix of the most widely used and most effective variables of the predicted model for accurate analysis. More data and calculation of the final model. Also, by using the multivariate correlation and regression analysis and the parent test, we compared the predicted model in the corporate life cycle. The results of 88 companies during the period of 2007 to 2016 in the Tehran Stock Exchange show that the distress risk in the experimental pricing model explains the average return on a portfolio based on momentum. The rate of return expected in the aftermath of the financial risk mitigation has decreased. Also, in healthy firms, the return on a portfolio consisting of a losing company is less than the return on a portfolio of winning shares. On the other hand, the results show that among the various stages of the company's life cycle, the average return on the portfolio of portfolios is higher for the valuation of capital assets at the maturity stage. Finally, the new adjustment modality can be explained by 59% of variations of the variables dependent on the independent variables of the model. Which has a higher coefficient than previous models. It indicates the high power of the conjunction and the higher explanatory power of the new model.

Keywords

References

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History

  • Receive Date: 17 May 2018
  • Revise Date: 15 December 2018
  • Accept Date: 21 December 2018

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