scholarly journals Learning Gated Bayesian Networks for Algorithmic Trading

2014 ◽  
pp. 49-64 ◽  
Author(s):  
Marcus Bendtsen ◽  
Jose M. Peña
Keyword(s):  
Bayesian Networks ◽  
Algorithmic Trading

scholarly journals Gated Bayesian networks for algorithmic trading

2016 ◽  
Vol 69 ◽  
pp. 58-80 ◽  
Author(s):  
Marcus Bendtsen ◽  
Jose M. Peña
Keyword(s):  
Bayesian Networks ◽  
Algorithmic Trading

The profitability of algorithmic trading systems based on football sentiment

2020 ◽  
Vol 42 (1) ◽  
pp. 33-46
Author(s):  
Raúl Gómez-Martínez ◽  
Camila Marqués-Bogliani ◽  
Jessica Paule-Vianez
Keyword(s):  
Financial Markets ◽  
Investment Decisions ◽  
Futures Market ◽  
Algorithmic Trading ◽  
Investment Strategies ◽  
Measurable Effect ◽  
Behavioural Finance ◽  
Trading Systems ◽  
European Football

Behavioural finance has shown that investment decisions are the result of not just rational but also emotional brain processes. On the assumption that emotions affect financial markets, it would seem likely that football results might have a measurable effect on financial markets. To test this, this study describes three algorithmic trading systems based exclusively on the results of three top European football teams (Juventus, Bayern München and Paris St Germain) opening long or short positions in the next market season of the futures market of the index of each country (MIB (Milano Italia Borsa), DAX (Deutscher Aktien Index) and CAC (Cotation Assistée en Continu). Depending on the outcome of the last game played a long position was taken after a victory and a short position after a draw or defeat. The results showed that the algorithmic systems were profitable in the case of Juventus and Bayern whereas in the case of PSG, the system was profitable, but in an inverse way. This study shows that investment strategies that take account of sports sentiment could have a profitable outcome.

Bayesian Networks Based Reliability Analysis of Phased-Mission Systems

2009 ◽  
Vol 31 (10) ◽  
pp. 1814-1825 ◽  
Author(s):  
Dong LIU ◽  
Chun-Yuan ZHANG ◽  
Wei-Yan XING ◽  
Rui LI
Keyword(s):  
Bayesian Networks ◽  
Reliability Analysis
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