David Enke
David Enke
Professor of Engineering Management and Systems Engineering
Verified email at mst.edu - Homepage
Cited by
Cited by
The use of data mining and neural networks for forecasting stock market returns
D Enke, S Thawornwong
Expert Systems with applications 29 (4), 927-940, 2005
Forecasting daily stock market return using dimensionality reduction
X Zhong, D Enke
Expert Systems with Applications 67, 126-139, 2017
The adaptive selection of financial and economic variables for use with artificial neural networks
S Thawornwong, D Enke
Neurocomputing 56, 205-232, 2004
Intelligent technical analysis based equivolume charting for stock trading using neural networks
T Chavarnakul, D Enke
Expert Systems with Applications 34 (2), 1004-1017, 2008
An adaptive stock index trading decision support system
WC Chiang, D Enke, T Wu, R Wang
Expert Systems with Applications 59, 195-207, 2016
Stock market prediction with multiple regression, fuzzy type-2 clustering and neural networks
D Enke, M Grauer, N Mehdiyev
Procedia Computer Science 6, 201-206, 2011
Time series classification using deep learning for process planning: A case from the process industry
N Mehdiyev, J Lahann, A Emrich, D Enke, P Fettke, P Loos
Procedia Computer Science 114, 242-249, 2017
A hybrid stock trading system for intelligent technical analysis-based equivolume charting
T Chavarnakul, D Enke
Neurocomputing 72 (16-18), 3517-3528, 2009
Predicting the daily return direction of the stock market using hybrid machine learning algorithms
X Zhong, D Enke
Financial Innovation 5 (1), 1-20, 2019
Volatility forecasting using a hybrid GJR-GARCH neural network model
SA Monfared, D Enke
Procedia Computer Science 36, 246-253, 2014
Evaluating forecasting methods by considering different accuracy measures
N Mehdiyev, D Enke, P Fettke, P Loos
Procedia Computer Science 95, 264-271, 2016
Developing a rule change trading system for the futures market using rough set analysis
Y Kim, D Enke
Expert Systems with Applications 59, 165-173, 2016
Stock market prediction using a combination of stepwise regression analysis, differential evolution-based fuzzy clustering, and a fuzzy inference neural network
D Enke, N Mehdiyev
Intelligent Automation & Soft Computing 19 (4), 636-648, 2013
An expert advisory system for the ISO 9001 quality system
HT Liao, D Enke, H Wiebe
Expert Systems with Applications 27 (2), 313-322, 2004
A comprehensive cluster and classification mining procedure for daily stock market return forecasting
X Zhong, D Enke
Neurocomputing 267, 152-168, 2017
Determination of rule patterns in complex event processing using machine learning techniques
N Mehdiyev, J Krumeich, D Enke, D Werth, P Loos
Procedia Computer Science 61, 395-401, 2015
Forecasting stock returns with artificial neural networks
S Thawornwong, D Enke
Neural Networks in Business Forecasting, 47-79, 2004
Neural networks as a decision maker for stock trading: a technical analysis approach
S Thawornwong, D Enke, C Dagli
International Journal of Smart Engineering System Design 5 (4), 313-325, 2003
Valuation for the strategic management of research and development projects: the deferral option
N Lewis, D Enke, D Spurlock
Engineering Management Journal 16 (4), 36-48, 2004
An intelligent hybrid trading system for discovering trading rules for the futures market using rough sets and genetic algorithms
Y Kim, W Ahn, KJ Oh, D Enke
Applied Soft Computing 55, 127-140, 2017
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