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Please use this identifier to cite or link to this item: http://hdl.handle.net/11129/3336

Title: Prediction of International Stock Market Movements Using a Statistical Time Series Analysis Method
Authors: Bodur, Mehmet
Shareef, Jehan Kadhim
Eastern Mediterranean University, Faculty of Engineering, Department of Computer Engineering
Keywords: Computer Engineering
Finance - Statistical methods
Time-series analysis - Stock Market
Time series analysis
ARMA
ARMA
Forecastıng and Investment
Issue Date: Sep-2013
Publisher: Eastern Mediterranean University (EMU) - Doğu Akdeniz Üniversitesi (DAÜ)
Citation: Shareef, Jehan Kadhim. (2013). Prediction of International Stock Market Movements Using a Statistical Time Series Analysis Method. Thesis (M.S.), Eastern Mediterranean University, Institute of Graduate Studies and Research, Dept. of Computer Engineering, Famagusta: North Cyprus.
Abstract: The thesis has used econometric time series models to model and forecast the development in closing prices of main international stock markets. These are New York, London, Tokyo and Shanghai stock market. The time series data set includes the trading days from 1st January, 2008 to 31st December, 2012 i.e. (5 years). After pre-processing the data to substitute the missing values using interpolation method and convert all closing prices to USD currency, the first attempt of this thesis employs the Auto Regressive Moving Average (ARMA) framework, which has been used to model a time series data set. It is found that the model can be used to fit the data in the estimation period. The Root Mean Square Error (RMSE) is used to find an estimating order of the parameter in ARMA model i.e. r, m proper values. The forecasting process is constructed based on the ARMA model to forecast the future value for the data indices in the period (2010-2012) in New York, London, Tokyo, and Shanghai stock market. The idea of forecasting in this work is predicting two-days-ahead closing price based on previous two years closing price for each two days. The forecasting is very important in the analysis of economic and industrial time series, and in sailing and buying movement. The money was invested in these stock markets and the results made it clear that the investment in London stock market is the best investment. Keywords: Time series analysis, ARMA, RMSE, Forecastıng and Investment.
ÖZ: Bu tez uluslararası hisse senedi pazarlarında ekonomik zaman serisi modeli kullanarak kapanış fiyatı öngörüsü yapma yöntemini incelemektedir. Yöntem New York, London, Tokyo and Shanghai hisse senedi pazarlarından elde edilen Ocak 2008 ile Aralık 1012 arasındaki 5 yıllık zaman serisi verilerine uygulanmıştır. Verilerin ön işleme aşamasında eksik değerleri tamamlanmış ve günlük kazanç oranına çevrilerek ARMA modelinde en düşük karekök-ortalama-kare-hatası (RMSE) veren yapısal parametreleri r ve m belirlenmiştir. Öngörüş ARMA modeli kullanılarak NewYork, Londra, Tokyo ve Şankay hisse senedi pazarlarında daha ileri tarihlerdeki fiyatları öngörmek üzere kurulmuştur. ARMA model ile 2008 başından 2010 sonuna kadar üç yıl boyunca her gün için daha önceki iki yıllık veri kullanılarak iki gün sonrasının kapanış fiyatı tahmin edilmiştir. Elde edilen tahmine göre sabit miktardaki kapital dört pazardan en iyi getiri beklenene yatırılma yönünde hisse alım ve satımı kararları oluşturulmuştur. Benzeşimsel yatırım etkinliği sonucu dört hisse senedi pazarı arasında yalnızca Londra’da yatırım yapmak, kapitali dört pazarın en iyisine yatırmaktan daha fazla getiri sağlamıştır. Anahtar Kelimeler: Zaman seriya analizi, ARMA, RMSE, Fiyat tahmini, Yatırım.
Description: Master of Science in Computer Engineering. Thesis (M.S.)--Eastern Mediterranean University, Faculty of Engineering, Dept. of Computer Engineering, 2013. Supervisor: Assist. Prof. Dr. Mehmet Bodur.
URI: http://hdl.handle.net/11129/3336
Appears in Collections:Theses (Master's and Ph.D) – Computer Engineering

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