Araştırma Makalesi

Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye

Cilt: 9 Sayı: 2 29 Temmuz 2022
PDF İndir
EN TR

Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye

Öz

Because of its critical position in open economies and its extremely high volatility, the stock market price index has been a popular subject of market research. In modern financial markets, traders and practitioners have had trouble predicting the stock market price index. In order to solve this problem, some methods have been researched by researchers and suitable methods have been found. To analyze and forecast monthly stock market price index, a variety of statistical and econometric models are extensively used. Thus, this study aims to investigate the application of autoregressive integrated moving averages (ARIMA) for forecasting monthly stock market price index in Istanbul for the period from 2009- M01 to 2021-M03. As compared to all other tentative models, the research showed that the ARIMA (3,1,5) model is the best fit model for predicting the stock market price index. Forecasting is conducted by using the developed model ARIMA (3,1,5) and the results indicated that the forecasted values are very similar to the actual ones, reducing forecast errors. In general, the stock market price index in Istanbul; showed a downwards trend over the forecasted period. The results of the study can set an example for researchers and practitioners working in the stock market and can be a guide for economic decision units and investors in the stock market. 

Anahtar Kelimeler

Kaynakça

  1. Al-Zeaud, H. A. (2011). Modelling and forecasting volatility using ARIMA Model. European Journal of Economics, Finance & Administrative Science, 35, 109-125. google scholar
  2. Atsalakis, G. S., & Valavanis, K. P. (2009). Forecasting stock market short-term trends using a neuro-fuzzy based methodology. Expert systems with Applications, 36(7), 10696-10707. google scholar
  3. Atsalakis, G. S., Dimitrakakis, E. M., & Zopounidis, C. D. (2011). Elliott wave theory and neuro-fuzzy systems, in stock market prediction: The WASP system. Expert Systems with Applications, 38(8), 9196-9206. google scholar
  4. Baba, N., & Kozaki, M. (1992). An intelligent forecasting system of stock price using neural networks. In [Proceedings 1992] IJCNN International Joint Conference on Neural Networks (Vol. 1, pp. 371-377). google scholar
  5. Bircan, H., & Karagöz, Y. (2003). Box-Jenkins modelleri ile aylık döviz kuru tahmini üzerine bir uygulama. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, (6), 49-62. google scholar
  6. Çevik, O (2002). İMKB endeksinin Box-Jenkins yöntemi ile modellenmesi. Afyon Kocatepe Üniversitesi İİBF Dergisi, (C.IV, S.1), 17-31. google scholar
  7. Chang, C. L., Sriboonchitta, S., & Wiboonpongse, A. (2009). Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation. Mathematics and computers in simulation, 79(5), 17301744. google scholar
  8. Contreras, J., Espinola, R., Nogales, F. J., & Conejo, A. J. (2003). ARIMA models to predict next-day electricity prices. IEEE transactions on power systems, 18(3), 1014-1020. google scholar

Ayrıntılar

Birincil Dil

İngilizce

Konular

Ekonomi

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

29 Temmuz 2022

Gönderilme Tarihi

12 Ocak 2022

Kabul Tarihi

15 Temmuz 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 9 Sayı: 2

Kaynak Göster

APA
Mashadihasanli, T. (2022). Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye. İktisat Politikası Araştırmaları Dergisi, 9(2), 439-454. https://doi.org/10.26650/JEPR1056771
AMA
1.Mashadihasanli T. Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye. JEPR. 2022;9(2):439-454. doi:10.26650/JEPR1056771
Chicago
Mashadihasanli, Tamerlan. 2022. “Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye”. İktisat Politikası Araştırmaları Dergisi 9 (2): 439-54. https://doi.org/10.26650/JEPR1056771.
EndNote
Mashadihasanli T (01 Temmuz 2022) Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye. İktisat Politikası Araştırmaları Dergisi 9 2 439–454.
IEEE
[1]T. Mashadihasanli, “Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye”, JEPR, c. 9, sy 2, ss. 439–454, Tem. 2022, doi: 10.26650/JEPR1056771.
ISNAD
Mashadihasanli, Tamerlan. “Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye”. İktisat Politikası Araştırmaları Dergisi 9/2 (01 Temmuz 2022): 439-454. https://doi.org/10.26650/JEPR1056771.
JAMA
1.Mashadihasanli T. Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye. JEPR. 2022;9:439–454.
MLA
Mashadihasanli, Tamerlan. “Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye”. İktisat Politikası Araştırmaları Dergisi, c. 9, sy 2, Temmuz 2022, ss. 439-54, doi:10.26650/JEPR1056771.
Vancouver
1.Tamerlan Mashadihasanli. Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye. JEPR. 01 Temmuz 2022;9(2):439-54. doi:10.26650/JEPR1056771