Johnnie E. V. Johnson

According to our database, Johnnie E. V. Johnson authored at least 15 papers between 1995 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Turning the heat on financial decisions: Examining the role temperature plays in the incidence of bias in a time-limited financial market.

Luis Felipe Costa Sperb, Ming-Chien Sung, Tiejun Ma, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2022

Are the least successful traders those most likely to exit the market? A survival analysis contribution to the efficient market debate.

Tiejun Ma, P. A. F. Fraser-Mackenzie, Ming-Chien Sung, A. P. Kansara, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2022

2020

Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices.

Larry Olanrewaju Orimoloye, Ming-Chien Sung, Tiejun Ma, Johnnie E. V. Johnson

Expert Syst. Appl., 2020

Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting.

Alisa Kim, Yaodong Yang, Stefan Lessmann, Tiejun Ma, Ming-Chien Sung, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2020

2019

Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements.

Ming-Chien Sung, David C. J. McDonald, Johnnie E. V. Johnson, Chung-Ching Tai, Eng-Tuck Cheah

Eur. J. Oper. Res., 2019

To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market.

Lawrence Green, Ming-Chien Sung, Tiejun Ma, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2019

2018

It takes all sorts: A heterogeneous agent explanation for prediction market mispricing.

Valerio Restocchi, Frank McGroarty, Enrico H. Gerding, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2018

2016

Bridging the divide in financial market forecasting: machine learners vs. financial economists.

Ming-Wei Hsu, Stefan Lessmann, Ming-Chien Sung, Tiejun Ma, Johnnie E. V. Johnson

Expert Syst. Appl., 2016

Probabilistic forecasting with discrete choice models: Evaluating predictions with pseudo-coefficients of determination.

Ming-Chien Sung, David C. J. McDonald, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2016

Time is money: Costing the impact of duration misperception in market prices.

Tiejun Ma, Leilei Tang, Frank McGroarty, Ming-Chien Sung, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2016

2012

A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction.

Stefan Lessmann, Ming-Chien Sung, Johnnie E. V. Johnson, Tiejun Ma

Eur. J. Oper. Res., 2012

2011

Towards a methodology for measuring the true degree of efficiency in a speculative market.

Stefan Lessmann, Ming-Chien Sung, Johnnie E. V. Johnson

J. Oper. Res. Soc., 2011

2009

Identifying winners of competitive events: A SVM-based classification model for horserace prediction.

Stefan Lessmann, Ming-Chien Sung, Johnnie E. V. Johnson

Eur. J. Oper. Res., 2009

2006

Exploring Decision Makers' Use of Price Information in a Speculative Market.

Johnnie E. V. Johnson, Owen Jones, Leilei Tang

Manag. Sci., 2006

1995

Gender and DSS design: the research implications.

Philip L. Powell, Johnnie E. V. Johnson

Decis. Support Syst., 1995