Yazar "Pabuccu, Hakan" seçeneğine göre listele

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    Forecasting the movements of Bitcoin prices: an application of machine learning algorithms
    (Amer Inst Mathematical Sciences-Aims, 2020) Pabuccu, Hakan; Ongan, Serdar; Ongan, Ayse
    Cryptocurrencies, such as Bitcoin, are one of the most controversial and complex technological innovations in today's financial system. This study aims to forecast the movements of Bitcoin prices at a high degree of accuracy. To this aim, four different Machine Learning (ML) algorithms are applied, namely, the Support Vector Machines (SVM), the Artificial Neural Network (ANN), the Naive Bayes (NB) and the Random Forest (RF) besides the logistic regression (LR) as a benchmark model. In order to test these algorithms, besides existing continuous dataset, discrete dataset was also created and used. For the evaluations of algorithm performances, the F statistic, accuracy statistic, the Mean Absolute Error (MAE), the Root Mean Square Error (RMSE) and the Root Absolute Error (RAE) metrics were used. The t test was used to compare the performances of the SVM, ANN, NB and RF with the performance of the LR. Empirical findings reveal that, while the RF has the highest forecasting performance in the continuous dataset, the NB has the lowest. On the other hand, while the ANN has the highest and the NB the lowest performance in the discrete dataset. Furthermore, the discrete dataset improves the overall forecasting performance in all algorithms (models) estimated.
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    Strategy Development for the Turkish Ready-Made Garment Sector Using SWOT Analysis - Fuzzy TOPSIS Method
    (Inst Chemical Fibres, 2020) Ozbek, Ahmet; Pabuccu, Hakan; Esmer, Yusuf
    The aim of this study was to integrate SWOT analysis and the fuzzy TOPSIS method to develop a strategy for the Turkish RMG sector. SWOT analysis was used to determine the strengths & weaknesses and opportunities & threats of the sector. New strategies were developed using SWOT analysis data, and then the fizzy TOPSIS method was used to rank the strategies for the sector. Four strategies were determined: (1) building global brands, (2) providing government incentives to increase the competitive power of the sector (3) effective use of e-commerce, and (4) transforming the sector into an attractive business area for young people. Empirical results indicate that the third strategy is ideal for the sector. However SWOT analysis falls short of determining strategies for any sector. The ability of strategy making processes to yield positive outcomes depends largely on managers' participation in decision-making processes. Fuzzy TOPSIS was used to model the inherent uncertainty in human knowledge and behaviour and to incorporate sector managers 'views into the .system to assess alternatives that integrate SWOT.