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Can deep learning predict risky retail investors? : A case study in financial risk behavior forecasting
Kim, A.; Yang, Y.; Lessmann, Stefan; Ma, Tiejun; Sung, M.-C. - In: European journal of operational research : EJOR 283 (2020) 1, pp. 217-234
Persistent link: https://www.econbiz.de/10012161963
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A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction
Lessmann, Stefan; Sung, Ming-chien; Johnson, Johnnie E. V. - In: European journal of operational research : EJOR 218 (2012) 1, pp. 163-174
Persistent link: https://www.econbiz.de/10009501053
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Towards a methodology for measuring the true degree of efficiency in a speculative market
Lessmann, Stefan; Sung, M.-C.; Johnson, Johnnie E. V. - In: Journal of the Operational Research Society : OR 62 (2011) 12, pp. 2120-2132
Persistent link: https://www.econbiz.de/10010217555
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Alternative methods of predicting competitive events : an application in horserace betting markets
Lessmann, Stefan; Sung, Ming-chien; Johnson, Johnnie E. V. - In: International journal of forecasting 26 (2010) 3, pp. 518-536
Persistent link: https://www.econbiz.de/10003990967
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Adapting least-square support vector regression models to forecast the outcome of horseraces
Lessmann, Stefan; Sung, Ming-chien; Johnson, Johnnie E. V. - In: The journal of prediction markets 1 (2007) 3, pp. 169-187
Persistent link: https://www.econbiz.de/10003637558
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A new method for predicting the outcome of speculative events
Lessmann, Stefan; Sung, Ming-chien; Johnson, Johnnie E. V. - 2007
Persistent link: https://www.econbiz.de/10003617196
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Adapting least-square support vector regression models to forecast the outcome of horseraces
Lessmann, Stefan; Sung, Ming-Chien; Johnson, Johnnie E. V. - In: The journal of prediction markets 1 (2007) 3, pp. 169-187
Persistent link: https://www.econbiz.de/10009931702