Erkam Güresen
Management Science and Operations Research · 2011
A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Management Science and Operations Research — 16 citations into it; #5,383 of 11,946 by trust here, #3,357 by citations
- Economics and Econometrics — 8 citations into it; #11,155 of 23,481 by trust here, #9,444 by citations
- Artificial Intelligence — 7 citations into it; #18,222 of 35,345 by trust here, #16,166 by citations
Whom Erkam Güresen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- George S. Atsalakis
- Robert F. Engle
- Tim Bollerslev
- Daniel B. Nelson
- Kimon P. Valavanis
- Arie Preminger
- Md. Rafiul Hassan
- Raphaël Franck
- Baikunth Nath
- Mehdi Khashei
Who trusts Erkam Güresen overall
- Ehsan Hoseinzade
- Prodromos Konstandinos Chourmouziadis
- Chih-Feng Liu
- Zhongyang Han
- Omer Berat Sezer
- Saman Haratizadeh
- D. Chatzoglou
- Ritika Singh
- Will Serrano
- Svitlana Galeshchuk
Papers from Erkam Güresen's perspective
Ordered by how strongly the researchers Erkam Güresen trusts endorse each paper. Same corpus, a different order for every researcher.
- Generalized autoregressive conditional heteroskedasticity
- Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
- Forecasting stock market short-term trends using a neuro-fuzzy based methodology
- Neural networks in finance : gaining predictive edge in the market
- Surveying stock market forecasting techniques - Part II: Soft computing methods
- CONDITIONAL HETEROSKEDASTICITY IN ASSET RETURNS: A NEW APPROACH
- A dynamic artificial neural network model for forecasting time series events
- A hybrid forecast marketing timing model based on probabilistic neural network, rough set and C4.5
- Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting
- A fusion model of HMM, ANN and GA for stock market forecasting
Their papers
- Using artificial neural network models in stock market index prediction (2011) — 781 citations