Forecasting the İstanbul stock exchange composite index

Besler, Batuhan


Forecasting Turkey's Short Term Hourly Load with Artificial Neural Networks
Load forecasting is important necessity to provide economic, reliable, high grade energy. In this study, short term hourly load forecasting systems were developed for nine load distribution regions of Turkey using artificial neural networks (ANN) approach. ANN is the most commonly preferred approach for load forecasting. The mean average percent error (MAPE) of total hourly load forecast for Turkey is found as 1.81%.
Forecasting the primary energy demand in Turkey and analysis of cyclic patterns
Ediger, VS; Tatlidil, H (2002-03-01)
The planning and estimation of future energy demand via modern statistical methods have been officially used in Turkey since 1984. However, almost all previous forecasts proved significantly higher than actual observations because of several reasons discussed here. The cycle analysis, which is a semi-statistical technique that makes use of any cyclicity in the historical data of annual additional amounts of energy demand, appears to give better results than the other techniques for forecasting energy demand...
Forecasting Turkey's sectoral energy demand
Oğuz, Mustafa Efe; Ekici, Tufan; Sarı, Ramazan; Sustainable Environment and Energy Systems (2013-6)
This study forecasts the sectoral energy demand of Turkey in the agriculture, industry, transportation, residence and services sectors for 2023 by means of the ARIMA, Vector Autoregressive and Decomposition statistical methods, and their products are then combined to arrived at a composite, or ensemble forecast. Each of these methods has their own merits and compliments each other. Two scenarios are considered; either the use of entire, unedited data (scenario one), or the absence of the last 3 years of the...
Forecasting financial performance using the FSCORE
İRGE, AHMET GÜRŞAT; Danışoğlu, Seza; Department of Financial Mathematics (2022-7-18)
This study examines whether the industry effect variables can be used to detect investable high book-to-market firms that are neglected by the classic FSCORE method. Industry winners in the neglected firms' cluster are called Underdogs. While the FSCORE method takes a financial picture of the high book-to-market firms, the industry effects variables identify the standing of the firm’s performance relative to its peers. When industry effects are taken into consideration in combination with the FSCORE, a comp...
Forecasting carbon dioxide emissions of Turkey’s international civil aviation through 2030
Kaymak, Deniz; Tuncel, Süleyman Gürdal; Department of Environmental Engineering (2019)
Nowadays, the aviation sector plays a vital role in the economic development of countries by connecting the continents. Air transportation is preferred more and more thanks to its advantages over the other transportation modes. After implementation of liberalization policies in Turkey, the aviation industry has shown a rapid development and the country has taken its place at the forefront in the world air transport. Due to the increasing demand for the aviation industry, inevitably CO2 emissions of the sect...
Citation Formats
B. Besler, “Forecasting the İstanbul stock exchange composite index,” Middle East Technical University, 1995.