Page 206 - IJOCTA-15-1
P. 206

H.H. Yildirim, A. Akusta / IJOCTA, Vol.15, No.1, pp.183-201 (2025)

            [43] Makau, A. (2017). Multivariate regression analy-  [55] Wijaya, Y. A., et al. (2021). Cluster validation
                sis of oil price volatility on GDP growth in Kenya.  techniques in data analysis using Davies-Bouldin
                American Journal of Theoretical and Applied Sta-  Index. Proceedings of the International Confer-
                tistics, 6(1), 44. https://doi.org/10.11648/j     ence on Industrial Technology and Application,
                .ajtas.20170601.16                                101–109.
            [44] Josheski, D., & Lazarov, D. (2012). Exchange rate  [56] Sarıkovanlık, V., Koy, A., Akkaya, M., Yıldırım,
                volatility and trade: A meta-regression analysis.  H.H., & Kantar, L. (2019). Finans Biliminde
                SSRN Electronic Journal. https://doi.org/10       Ekonometri Uygulamaları,  Se¸ckin Yayıncılık,
                .2139/ssrn.2077678                                Ankara.
            [45] Allen, D. E., Singh, A. K., Powell, R., McAleer,  [57] Breusch, T.S., & Pagan, A. R. (1980). The La-
                M., Taylor, J. E., & Thomas, L. C. (2012). The    grange Multiplier Test and Its Applications to
                volatility-return relationship: Insights from linear  Model Specification in Econometrics. The Review
                and non-linear quantile regressions. Research Pa-  of Economic Studies, 239-253. https://doi.or
                pers in Economics.                                g/10.2307/2297111
            [46] Waweru, N. N. (2013). Analysis of the determi-  [58] Peseran, M. H. H. M. (2004). General Diagnos-
                nants of stock price volatility at Nairobi Securities  tic Test for Cross Section Dependence in Panels.
                Exchange.                                         Working Paper, University of Cambridge, Cam-
            [47] Parkinson,  M. (1980). The Extreme Value         bridge, United Kingdom.
                Method for Estimating the Variance of the Rate  [59] Harris, R. D. F., & Tzavalis, E. (1999). Infer-
                of Return. The Journal of Business, 53(1), 61–65.  ence for Unit Roots in Dynamic Panels Where
                http://www.jstor.org/stable/2352357               The Time Dimension is Fixed, Journal of Econo-
            [48] Jolliffe, I. (2013). Principal component analysis.  metrics, 91, 201-226. https://doi.org/10.101
                Springer New York.                                6/S0304-4076(98)00076-1
            [49] Hastie, T., Friedman, J., & Tibshirani, R. (2001).  [60] Hausman, J. A. (1978). Specification Test in
                The elements of statistical learning. Springer. ht  Econometrics, Econometrica, 46(6), 1251-1271.
                tps://doi.org/10.1007/978-0-387-21606-5       [61] Tato˘glu, F. Y. (2012). Panel Veri Ekonometrisi,
                                                                                 ˙
            [50] Sakamoto, Y., et al. (2024). Applications of the  Beta Yayıncılık, Istanbul.
                elbow method in K-means clustering.
            [51] Umargono, E., Suseno, J., & Gunawan, S. K.   Hasan Huseyin Yildirim received his Master’s De-
                (2020). K-means clustering optimization using  gree (2011) in Finance from Marmara University and
                the elbow method and early centroid determina-  obtained PhD Degree (2016) from Istanbul University.
                tion based on mean and median formula. Pro-   Mr. YILDIRIM is Assoc. Prof. in the Burhaniye
                ceedings of the International Conference on En-  Applied Sciences Faculty at Balikesir University. His
                gineering, Technology and Industrial Application,  research interests include the economy, finance and
                19–26. https://doi.org/10.2991/assehr.k.2     banking sector and renewable energy investments.
                01010.019                                        http://orcid.org/0000-0002-5840-8418
            [52] Rousseeuw, P. J. (1987). Silhouettes: A graphical
                aid to the interpretation and validation of cluster
                                                              Ahmet Akusta received his PhD from Necmettin Er-
                analysis. Journal of Computational and Applied
                                                              bakan University. He works at Konya Technical Uni-
                Mathematics, 20, 53–65.
                                                              versity. His research areas include International Fi-
            [53] Lenssen, L., & Schubert, E. (2024). Medoid sil-
                                                              nance, Financial Forecasting and Modelling, Invest-
                houette clustering with automatic cluster number
                                                              ments, and Portfolio Management.
                selection. Information Systems, 120, 102290.
                                                                 http://orcid.org/0000-0002-5160-3210
            [54] Davies, D. L., & Bouldin, D. W. (1979). A cluster
                separation measure. IEEE Transactions on Pat-
                tern Analysis and Machine Intelligence, PAMI-1
                (2), 224–227.


                            An International Journal of Optimization and Control: Theories & Applications
                                             (https://accscience.com/journal/ijocta)






            This work is licensed under a Creative Commons Attribution 4.0 International License. The authors retain ownership of
            the copyright for their article, but they allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles
            in IJOCTA, so long as the original authors and source are credited. To see the complete license contents, please visit
            http://creativecommons.org/licenses/by/4.0/.


                                                           200
   201   202   203   204   205   206   207   208   209   210