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TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN

Year 2019, Volume: 10 Issue: 1, 7 - 11, 30.12.2019

Abstract

Amaç- Bu çalışmanın amacı, Makine Öğrenmesi yöntemlerinden yararlanarak geliştirilen modellerin zaman serilerinin öngörüsünde alternatif bir yöntem olup olmadığının incelenmesidir.
Yöntem- Geleneksel olarak, Otoregresif Entegre Hareketli Ortalama (ARIMA) modeli, zaman serisi tahmininde en yaygın kullanılan doğrusal modellerden biridir. Çalışmada,ARIMA modellerinin yanı sıra Rassal Orman ve Hibrit Rassal Orman yöntemleri kullanılmış ve Türkiye Konut Fiyat Endeksi serisi için bu modellerin öngörü performansları karşılaştırılmıştır.
Bulgular- Hibrit modelin konut fiyat endeksini öngörmede diğer yöntemlerden daha başarılı olduğu tespit edilmiştir.
Sonuç- Sonuç olarak, ARIMA ve Makine Öğrenmesi yöntemini birleştiren hibrit modellerin, ekonomik ve finansal verilerin öngörüsünde alternatif bir yöntem olarak kullanılabileceği tespit edilmiştir.

References

  • Franses, P. H., & Van Dijk, D. (2003). Non-linear Time Series Models in Empirical Finance. Cambridge University Press.
  • Hastie, T., Tibshirani, R., &Friedman, J. (2009). The Elements of Statistical Learning. New York: Springer-Verlag.
  • Kumar, M., &Thenmozhi, M. (2014). Forecasting Stock Index Returns using ARIMA-SVM, ARIMA-ANN, and ARIMA-Random Forest Hybrid Models. Int. J. Banking, Accounting and Finance, 284 – 308.
  • Pai, P-F., & Lin, C-S. (2005). A Hybrid ARIMA and Support Vector Machines Model in Stock Price Forecasting. Omega, 497 – 505.
  • Pedregosa, F.(2016). Hyperparameter Optimization With Approximate Gradient. JMLR: W&CP vol.48, 737-746.
  • TCMB(2019, 27 Ekim). KonutFiyatEndeksi. https://www.tcmb.gov.tr/wps/wcm/connect/b4628fa9-11a7-4426-aee6-dae67fc56200/KFE-Metaveri.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-b4628fa9-11a7-4426-aee6-dae67fc56200-mDXEz4N
  • Wang, P. (2008). Financial Econometrics. Routledge.
  • Zhang, G. P. (2003). Time Series Forecasting using A Hybrid ARIMA and Neural Network Model. Neurocomputing, 159 – 175.
  • Zhang, G., Patuwo, B. E., & Hu M. Y. (1998). Forecasting with Artificial Neural Networks: The State of The Art. International Journal of Forecasting, 35–62

FORECASTING OF TURKISH HOUSING PRICE INDEX: ARIMA, RANDOM FOREST, ARIMA-RANDOM FOREST

Year 2019, Volume: 10 Issue: 1, 7 - 11, 30.12.2019

Abstract

Purpose- The aim of this study is to investigate whether the models developed by using Machine Learning methods are an alternative method for forecasting time series.
Methodology-Traditionally, the Autoregressive Integrated Moving Average (ARIMA) model has been one of the most widely used linear models in time series forecasting. In the study, we use Random Forest and Hybrid Random Forest-ARIMA models besides the ARIMA model and compare their forecasting performance for the Turkish Housing Price Index series.
Findings- The hybrid model was found to be more successful than other methods in forecasting the housing price index.
Conclusion- As a result, hybrid models that combine ARIMA and machine learning method can be used an alternative method in forecasting economic and financial data

References

  • Franses, P. H., & Van Dijk, D. (2003). Non-linear Time Series Models in Empirical Finance. Cambridge University Press.
  • Hastie, T., Tibshirani, R., &Friedman, J. (2009). The Elements of Statistical Learning. New York: Springer-Verlag.
  • Kumar, M., &Thenmozhi, M. (2014). Forecasting Stock Index Returns using ARIMA-SVM, ARIMA-ANN, and ARIMA-Random Forest Hybrid Models. Int. J. Banking, Accounting and Finance, 284 – 308.
  • Pai, P-F., & Lin, C-S. (2005). A Hybrid ARIMA and Support Vector Machines Model in Stock Price Forecasting. Omega, 497 – 505.
  • Pedregosa, F.(2016). Hyperparameter Optimization With Approximate Gradient. JMLR: W&CP vol.48, 737-746.
  • TCMB(2019, 27 Ekim). KonutFiyatEndeksi. https://www.tcmb.gov.tr/wps/wcm/connect/b4628fa9-11a7-4426-aee6-dae67fc56200/KFE-Metaveri.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-b4628fa9-11a7-4426-aee6-dae67fc56200-mDXEz4N
  • Wang, P. (2008). Financial Econometrics. Routledge.
  • Zhang, G. P. (2003). Time Series Forecasting using A Hybrid ARIMA and Neural Network Model. Neurocomputing, 159 – 175.
  • Zhang, G., Patuwo, B. E., & Hu M. Y. (1998). Forecasting with Artificial Neural Networks: The State of The Art. International Journal of Forecasting, 35–62
There are 9 citations in total.

Details

Primary Language Turkish
Subjects Finance, Business Administration
Journal Section Articles
Authors

Ebru Çaglayan Akay 0000-0002-9998-5334

Kadriye Hilal Topal This is me 0000-0001-5203-8017

Saban Kizilarslan 0000-0003-1545-9597

Hoseng Bulbul 0000-0002-4541-8916

Publication Date December 30, 2019
Published in Issue Year 2019 Volume: 10 Issue: 1

Cite

APA Akay, E. Ç., Topal, K. H., Kizilarslan, S., Bulbul, H. (2019). TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN. PressAcademia Procedia, 10(1), 7-11.
AMA Akay EÇ, Topal KH, Kizilarslan S, Bulbul H. TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN. PAP. December 2019;10(1):7-11.
Chicago Akay, Ebru Çaglayan, Kadriye Hilal Topal, Saban Kizilarslan, and Hoseng Bulbul. “TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN”. PressAcademia Procedia 10, no. 1 (December 2019): 7-11.
EndNote Akay EÇ, Topal KH, Kizilarslan S, Bulbul H (December 1, 2019) TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN. PressAcademia Procedia 10 1 7–11.
IEEE E. Ç. Akay, K. H. Topal, S. Kizilarslan, and H. Bulbul, “TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN”, PAP, vol. 10, no. 1, pp. 7–11, 2019.
ISNAD Akay, Ebru Çaglayan et al. “TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN”. PressAcademia Procedia 10/1 (December 2019), 7-11.
JAMA Akay EÇ, Topal KH, Kizilarslan S, Bulbul H. TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN. PAP. 2019;10:7–11.
MLA Akay, Ebru Çaglayan et al. “TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN”. PressAcademia Procedia, vol. 10, no. 1, 2019, pp. 7-11.
Vancouver Akay EÇ, Topal KH, Kizilarslan S, Bulbul H. TÜRKİYE KONUT FİYAT ENDEKSİ ÖNGÖRÜSÜ: ARIMA, RASSAL ORMAN VE ARIMA-RASSAL ORMAN. PAP. 2019;10(1):7-11.

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