An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange
By Melek Acar Boyacioglu, Derya Avcı. Expert systems with applications, 2010
409 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Economics and Econometrics, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/1f558d054b5aea012a935df047036369c4bdcc33
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Mohsen Akbari
- Jingshuang Liu
- Yusuf Yaslan
- Ahmad Bagheri
- Qiubin Liang
- Zhang Xiong
- Hamed Mohammadi Peyhani
- Jiayi Zhang
In Economics and Econometrics
- Mohsen Akbari
- Yusuf Yaslan
- Ahmad Bagheri
- Hamed Mohammadi Peyhani
- Zehra Cataltepe
- Hakan Gunduz
- Weiwei Jiang
- Omer Berat Sezer
In Management Science and Operations Research
- Mohsen Akbari
- Yusuf Yaslan
- Ahmad Bagheri
- Hamed Mohammadi Peyhani
- Zehra Cataltepe
- Hakan Gunduz
- Weiwei Jiang
- M. Ugur Gudelek
Citations in the corpus
- Restricted Boltzmann machine based stock market trend prediction (2017, background): “However, stock market prediction is extremely difficult due to its non-stationary, noisy and chaotic nature [1].”
- Financial forecasting using ANFIS networks with Quantum-behaved Particle Swarm Optimization (2014, methodology): “Boyacioglu and Avci (2010) used six macroeconomic variables and three indices as ANFIS input variables for predicting the Istanbul Stock Exchange index.”
- Intraday prediction of Borsa Istanbul using convolutional neural networks and feature correlations (2017, methodology): “[33] predicted the return of the BIST 100 index with Adaptive Neuro Fuzzy Inference System (ANFIS) classifier.”