Vol. 10 No. 2 (2022): Business & Management Studies: An International Journal
Articles

Testing multi-factor asset pricing models in Borsa Istanbul

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  • Gökhan ÖZER,
  • Ayşegül YILDIRIM KUTBAY
Gökhan ÖZER
Prof. Dr., Gebze Technical University Faculty of Business Administration, Gebze, Turkey
Ayşegül YILDIRIM KUTBAY
Lect., Balikesir University, Burhaniye Faculty of Applied Sciences, Balıkesir, Turkey

Published 2022-06-25

Keywords

  • Factor Models, CAPM, Fama-French, Carhart, Momentum, Q- Factor, Value Added Intellectual Coefficient
  • Faktör Modelleri, CAPM, Fama- French, Carhart- Momentum, q- Faktör, Entelektüel Katma Değer Katsayı

How to Cite

Testing multi-factor asset pricing models in Borsa Istanbul. (2022). Business & Management Studies: An International Journal, 10(2), 555-568. https://doi.org/10.15295/bmij.v10i2.2043

Copyright (c) 2022 Gökhan ÖZER- Ayşegül YILDIRIM KUTBAY

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Testing multi-factor asset pricing models in Borsa Istanbul. (2022). Business & Management Studies: An International Journal, 10(2), 555-568. https://doi.org/10.15295/bmij.v10i2.2043

Abstract

This study aims to test the validity of multi-factor asset pricing models on the portfolios of non-financial companies whose shares are traded on Borsa Istanbul and to identify the model with the best explanatory power. Accordingly, the relationships between annual book-to-market equity ratio, firm size, market portfolio return, return on capital, operating profitability, momentum and value-added intellectual coefficient between 2008-2019 were analyzed using panel data analysis. As a result of the analyses made, it has been observed that Fama French's three and five factors, Carhart (momentum), q-factor, and suggested models are successful in explaining the returns of portfolios formed by non-financial companies. Furthermore, according to the GRS-F test statistic, the q-factor model was found to have higher explanatory power than other models.

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