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Master Thesis İhracat Miktarlarının Gelişmiş Zaman Serisi Tahmini İçin Transformatör Modellerinden Yararlanma(2024) Coşkun, Çağrı; Yıldız, Beytullah; Yazıcı, AliForecasting export amounts is crucial for small and medium-sized enterprises (SMEs) to remain competitive in global markets. Traditional machine learning methods often struggle with the complexities of multiple multivariate time-series analysis, where financial data is recorded annually for each company, showing irregular fluctuations and long-term dependencies. Address these challenges, we introduce a Transformer based approach for forecasting export amounts using annually repeated financial data. The Transformer model, with its advanced attention mechanisms, outperformed Random Forest and Long Short-Term Memory (LSTM) models on our dataset, which spans nine years for each enterprise. When the number of time points in the dataset was reduced, the Transformer model exhibited a significant drop in performance. However, its performance increased notably with the use of an extended time series, clearly showing that successful and impactful results require sufficiently long, feature rich time series, enhanced by effective feature engineering. These findings indicate that Transformer models can significantly improve the accuracy of forecasting complex time series based on financial data and offer valuable insights for SMEs and policymakers.Article Citation - WoS: 10Citation - Scopus: 12Forecasting Elections in Turkey(Elsevier, 2011) Toros, EmreThis paper proposes a model for forecasting elections in Turkey. In doing so, this study is based on three theoretical premises: first, that the voters reward or punish parties according to their performances relative to the macroeconomic conditions; second, that the popularity of the political parties in Turkey are closely connected to their performances in local elections; and third, that the centre-periphery distinction affects the fortunes of the political parties in Turkey. The contribution of this analysis is the introduction of an explicit model on which can forecast the impact of economic and political variables on the elections in Turkey by using reliable, public and macro level data. Our findings show that the dynamics of the evaluation of political parties in Turkey follow a similar pattern to those of contemporary democracies, being driven by both economic and political factors. " ... why did AKP win? There cannot be a scientific and sociological explanation of this." Ozdemir Ince, 17 August 2007, Hurriyet, emphasis added. (C) 2011 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
