Predictive Models
Author:
Publisher
Springer Berlin Heidelberg
Link
https://link.springer.com/content/pdf/10.1007/978-3-662-68313-2_9
Reference40 articles.
1. Angelini, G., & de Angelis, L. (2019). Efficiency of online football betting markets. International Journal of Forecasting, 35(2), 712–721. https://doi.org/10.1016/j.ijforecast.2018.07.008
2. Bernardo, G., Ruberti, M., & Verona, R. (2019). Semi-strong inefficiency in the fixed odds betting market: Underestimating the positive impact of head coach replacement in the main European soccer leagues. The Quarterly Review of Economics and Finance, 71, 239–246. https://doi.org/10.1016/j.qref.2018.08.007
3. Booth, H. (2006). Demographic forecasting: 1980 to 2005 in review. International Journal of Forecasting, 22(3), 547–581. https://doi.org/10.1016/j.ijforecast.2006.04.001
4. Boshnakov, G., Kharrat, T., & McHale, I. G. (2017). A bivariate Weibull count model for forecasting association football scores. International Journal of Forecasting, 33(2), 458–466. https://doi.org/10.1016/j.ijforecast.2016.11.006
5. Brandt, P. T., Freeman, J. R., & Schrodt, P. A. (2014). Evaluating forecasts of political conflict dynamics. International Journal of Forecasting, 30(4), 944–962. https://doi.org/10.1016/j.ijforecast.2014.03.014
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