IDEAS home Printed from https://ideas.repec.org/a/jfi/journl/v1y2015i2p5.html
   My bibliography  Save this article

Strategic Financial Performance Evaluation of the Iranian automotive industry Using Imperialist competitive Algorithm

Author

Listed:
  • Meysam Kaviani
  • Maziyar Yazdani

Abstract

Purpose. This paper evaluates strategic financial performance of 10 Iranian stock exchange listed automotive companies over the period 2005-2009 at the hand of value-creating performance indicators and the Free Cash Flow derived value indicators. Design. To this effect, profiting from the Imperialist Competitive Algorithm (ICA), the understudy companies were assigned to three clusters in terms of debt structure, firm size, and growth opportunities Findings. The results, in general, indicate a significant correlation between value-based indicators Economic Value Added (EVA) and True Value Added (TVA) and the FCF-derived indicators Created Value from Free Cash Flow to Firm (CVFCFF) and Created Value from Free Cash Flow to Equity (CVFCFE), and between Market Value Added (MVA) and CVFCFF (one of the two FCF-derived indicators), while, according to the results, there is no significant correlation between the value-driven performance indicators Refined Economic Value Added (REVA) and Equity Economic Value Added (EEVA) and either of the FCF-derived indicators CVFCFF and CVFCFE. Originality. Present Paper, by company clustering in ICA environment, the companies are clustered based on their close similarity in all three criteria and subsequently for examination of each strategic performance indicator were subjected to correlation and Fisher (F) tests.

Suggested Citation

  • Meysam Kaviani & Maziyar Yazdani, 2015. "Strategic Financial Performance Evaluation of the Iranian automotive industry Using Imperialist competitive Algorithm," Journal of Financial Innovation, IBRIF - Instituto Brasileiro de Inovação Financeira, vol. 1(2), pages 1-5.
    • Handle: RePEc:jfi:journl:v:1:y:2015:i:2:p:5
    as

    Download full text from publisher

    File URL: http://ibrif.org/ojs/index.php/jofi/article/download/25/28
    Download Restriction: no
    File URL: http://ibrif.org/ojs/index.php/jofi/article/view/25
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew C. Worthington & Tracey West, 2004. "Australian Evidence Concerning the Information Content of Economic Value-Added," Australian Journal of Management, Australian School of Business, vol. 29(2), pages 201-223, December.
    2. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
    3. Varetto, Franco, 1998. "Genetic algorithms applications in the analysis of insolvency risk," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1421-1439, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zbysław Dobrowolski & Grzegorz Drozdowski & Mirela Panait & Arkadiusz Babczuk, 2022. "Can the Economic Value Added Be Used as the Universal Financial Metric?," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    2. Moina Ajmeri & Ahmad Ali, 2017. "Analytical design of modified Smith predictor for unstable second-order processes with time delay," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(8), pages 1671-1681, June.
    3. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
    4. Viet, Nguyen Quoc & Behdani, Behzad & Bloemhof, Jacqueline, 2018. "Value of Information to Improve Daily Operations in High-Density Logistics," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(1), January.
    5. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    6. P.R. Ouyang & V. Pano & T. Dam, 2015. "PID position domain control for contour tracking," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(1), pages 111-124, January.
    7. M. Kang & J. Cheong & H.M. Do & Y. Son & S.-I. Niculescu, 2017. "A practical iterative PID tuning method for mechanical systems using parameter chart," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(13), pages 2887-2900, October.
    8. Md. Majharul Haque & Suraiya Pervin & Anowar Hossain & Zerina Begum, 2020. "Approaches and Trends of Automatic Bangla Text Summarization: Challenges and Opportunities," International Journal of Technology Diffusion (IJTD), IGI Global, vol. 11(4), pages 67-83, October.
    9. Mourad Kchaou & Ahmed El-Hajjaji, 2017. "Resilient sliding mode control for discrete-time descriptor fuzzy systems with multiple time delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(2), pages 288-301, January.
    10. Changyin Sun & Qing Wang & Yao Yu, 2017. "Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(6), pages 1173-1181, April.
    11. Fatima Alali & Silvia Romero, 2013. "Characteristics of failed U.S. commercial banks: an exploratory study," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(4), pages 1149-1174, December.
    12. Haitong Wei & Xinghai Wang, 2024. "Financial Risk Management Early-Warning Model for Chinese Enterprises," JRFM, MDPI, vol. 17(7), pages 1-28, June.
    13. Hassan Ghiti Sarand & Bahram Karimi, 2016. "Synchronisation of high-order MIMO nonlinear systems using distributed neuro-adaptive control," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(9), pages 2214-2224, July.
    14. Zhouhua Peng & Dan Wang & Gang Sun & Hao Wang, 2014. "Distributed cooperative stabilisation of continuous-time uncertain nonlinear multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(10), pages 2031-2041, October.
    15. Nadja Bömmel & Guido Heineck, 2023. "Revisiting the causal effect of education on political participation and interest," Education Economics, Taylor & Francis Journals, vol. 31(6), pages 664-682, November.
    16. Catherine Refait, 2004. "La prévision de la faillite fondée sur l’analyse financière de l’entreprise : un état des lieux," Économie et Prévision, Programme National Persée, vol. 162(1), pages 129-147.
    17. Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring," European Journal of Operational Research, Elsevier, vol. 195(3), pages 942-959, June.
    18. Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
    19. Ashita Agrawal & Pitabas Mohanty & Navindra Kumar Totala, 2019. "Does EVA Beat ROA and ROE in Explaining the Stock Returns in Indian Scenario? An Evidence Using Mixed Effects Panel Data Regression Model," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 44(2), pages 103-134, May.
    20. Zhengmin Liu & Peide Liu, 2017. "Intuitionistic uncertain linguistic partitioned Bonferroni means and their application to multiple attribute decision-making," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(5), pages 1092-1105, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jfi:journl:v:1:y:2015:i:2:p:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wesley Mendes-Da-Silva (email available below). General contact details of provider: http://www.ibrif.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.