David Enke
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View article: Bitcoin price direction prediction using on-chain data and feature selection
Bitcoin price direction prediction using on-chain data and feature selection Open
Bitcoin is the most traded cryptocurrency by volume and market cap. A number of scholars have directed their research towards characterizing Bitcoin’s speculative behavior using a myriad of techniques such as technical analysis, price regr…
View article: Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared
Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared Open
This paper applies deep learning models to predict Bitcoin price directions and the subsequent profitability of trading strategies based on these predictions. The study compares the performance of the convolutional neural network–long shor…
View article: Successfully Blending Distance Students Into The On Campus Classroom
Successfully Blending Distance Students Into The On Campus Classroom Open
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Successfully Blending Distance Students into the On-Campus Classroom Susan L. Murray, Ph.D. David Enke, Ph.D., and Sreeram Ramakrishnan…
View article: Instance Selection Using Genetic Algorithms for an Intelligent Ensemble Trading System
Instance Selection Using Genetic Algorithms for an Intelligent Ensemble Trading System Open
Instance selection is a way to remove unnecessary data that can adversely affect the prediction model, thereby selecting representative and relevant data from the original data set that is expected to improve predictive performance. Instan…
View article: Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry
Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry Open
Multivariate time series classification has been broadly applied in diverse domains over the past few decades. However, before applying the classification algorithms, the vast majority of current studies extract hand-engineered features th…
View article: Developing a rule change trading system for the futures market using rough set analysis
Developing a rule change trading system for the futures market using rough set analysis Open
Many technical indicators have been selected as input variables in order to develop an automated trading system that determines buying and selling trading decision using optimal trading rules within the futures market. However, optimal tec…
View article: An adaptive stock index trading decision support system
An adaptive stock index trading decision support system Open
Predicting the direction and movement of stock index prices is difficult, often leading to excessive trading, transaction costs, and missed opportunities. Often traders need a systematic method to not only spot trading opportunities, but t…
View article: Using Neural Networks to Forecast Volatility for an Asset Allocation Strategy Based on the Target Volatility
Using Neural Networks to Forecast Volatility for an Asset Allocation Strategy Based on the Target Volatility Open
The objective of this study is to use artificial neural networks for volatility forecasting to enhance the ability of an asset allocation strategy based on the target volatility. The target volatility level is achieved by dynamically alloc…
View article: Evaluating Forecasting Methods by Considering Different Accuracy Measures
Evaluating Forecasting Methods by Considering Different Accuracy Measures Open
Choosing the appropriate forecasting technique to employ is a challenging issue and requires a comprehensive analysis of empirical results. Recent research findings reveal that the performance evaluation of forecasting models depends on th…