Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

Browse

Search Results

Now showing 1 - 2 of 2
  • Conference Object
    Citation - Scopus: 1
    Sustainable Economic Development Indicators: The Case of Turkey
    (World Scientific Publ Co Pte Ltd, 2016-08) Soylemez, Ismet; Dogan, Ahmet; Ozcan, Ugur
    Sustainable development indicators are a good road map for financial, social and economic targets of countries. This paper aims to show which indicators are affect sustainable development of Turkey for last twelve years. 132 sustainable development indicators determined by European Union Statistical Office (Eurostat). Sustainable development indicators are calculated by related unit, institution or establishment in the direction of definitions determined by Eurostat. These indicators are calculated by TUIK (Turkish Statistical Institute) for Turkey. Some indicators as follows: socio-economic development, sustainable consumption and production, climate change and energy, sustainable transport, financing for sustainable development. However, only economic indicators are presented and analyzed in the case study. Official development assistance has tenfold rise in the last 12 years. These indicators will show which areas at economic changes should be considered to the sustainable development of country.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Strategic Investment in BIST100: A Machine Learning Approach Using Symbolic Aggregate Approximation Clustering
    (Univ Cincinnati industrial Engineering, 2025) Nalici, Mehmet Eren; Soylemez, Ismet; Unlu, Ramazan
    This study employs the Symbolic Aggregate Approximation (SAX) clustering method to enhance investor decision-making on the Borsa Istanbul (BIST100) by identifying companies exhibiting analogous stock movements. The data from 81 BIST100 companies over a three-year period has been analyzed, with a focus on risk minimization and strategic investment. The SAX method, integrated with a dendrogram, categorizes stocks into sector-based and non-sector-based clusters, providing insights for portfolio optimization. The results demonstrate the effectiveness of the method in identifying relevant stock patterns across sectors, aiding in more informed investment decisions. This approach highlights the need for considering multiple factors in investment strategies, offering a new perspective on stock market analysis with advanced clustering techniques.