References
- Babu, A. S., & Reddy, S. K. (2015). Exchange rate forecasting using ARIMA, neural network and fuzzy neuron. Journal of Stock & Forex Trading, 3(4), 1–5. doi:10.4172/2168-9458.1000155
- Bircan, H., & Karagoz, Y. (2003). Box Jenkins Modelleri İle Aylık Döviz Kuru Tahmini Üzerine Bir Uygulama. Kocaeli Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 6, 49–62. Retrieved from http://dergipark.gov.tr/download/article-file/252067
- Box, G. E., & Jenkins, G. M. (1970). Time series analysis, forecasting, and control. San Francisco, CA: Holden - Day.
- Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 1057–1072. Retrieved from http://www.jstor.org/stable/191251710.2307/1912517
- Hsu, M. W., Lessmann, S., Sung, M. C., Ma, T., & Johnson, J. E. (2016). Bridging the divide in financial market forecasting: Machine learners vs. financial economists. Expert Systems with Applications, 61, 215–234. doi:10.1016/j.eswa.2016.05.033
- Kadilar, C., Şimşek, M., & Aladağ, A. G. Ç. H. (2009). Forecasting the exchange rate series with ANN: The case of Turkey. Ekonometri ve İstatistik e-Dergisi, 9, 17–29. Retrieved from http://www.journals.istanbul.edu.tr/iuekois/article/view/1023005311
- Kaynar, O., & Taştan, S. (2009). Zaman Serisianalizinde MLP Yapay Sinir Ağları Ve Arıma Modelinin Karşılaştırılması. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, (33), 161–172. Retrieved from http://iibf.erciyes.edu.tr/dergi/sayi33/9.k%C4%B1s%C4%B1m.pdf
- Maniatis, P. (2012). Forecasting the exchange rate between Euro and USD: Probabilistic approach versus ARIMA and exponential smoothing techniques. Journal of Applied Business Research (JABR), 28, 171–192. doi:10.19030/jabr.v28i2.6840
- Maria, F. C., & Eva, D. (2011). Exchange-rates forecasting: exponential smoothing techniques and ARIMA models. Annals of Faculty of Economics, 1, 499–508. Retrieved from http://anale.steconomiceuoradea.ro/volume/2011/n1/046.pdf
- Nwankwo, S. C. (2014). Autoregressive integrated moving average (ARIMA) model for exchange rate (Naira to Dollar). Academic Journal of Interdisciplinary Studies, 3, 429. doi:10.5901/ajis.2014.v3n4p42
- Özkan, F. (2011). Döviz Kuru Tahmininde Yapay Sinir Ağlarıyla Alternatif Yaklaşım. Eskişehir Osmangazi Üniversitesi, İİBF Dergisi, (s 6), 2. Retrieved from http://iibfdergi.ogu.edu.tr/makaleler/11352029_6_6-2_Makale_0.pdf
- Pai, P. F., & Lin, C. S. (2005). A hybrid ARIMA and support vector machines model in stock price forecasting. Omega, 33, 497–505. doi:10.1016/j.omega.2004.07.024
- Vergil, H., & Özkan, F. (2007). Döviz Kurları Öngörüsünde Parasal Model ve Arima Modelleri: Türkiye Örneği. Retrieved from http://dergipark.gov.tr/kosbed/issue/25707/271265
- Yao, J., & Tan, C. L. (2000). A case study on using neural networks to perform technical forecasting of forex. Neurocomputing, 34, 79–98. doi:10.1016/S0925-2312(00)00300-3
- Zhang, G. P. (2003). Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing, 50, 159–175. doi:10.1016/S0925-2312(01)00702-0