State-of-the-Art in Applying Machine Learning to Electronic Trading-Reference-Cited by-同舟云学术

State-of-the-Art in Applying Machine Learning to Electronic Trading

Published:2020 Issue: Volume: Page:3-20
ISSN:1865-1348
Container-title:Lecture Notes in Business Information Processing
language:
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Author:

Rabhi Fethi A.,Mehandjiev Nikolay,Baghdadi Ali

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-64466-6_1

Reference51 articles.

1. Azzini, A., Tettamanzi, A.: Automated trading on financial instruments with evolved neural networks. In: Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference, p. 2252 (2007). https://doi.org/10.1145/1276958.1277387

2. Barclays: Algo Wheels: 6 essential building blocks (2018). https://www.investmentbank.barclays.com/our-insights/algo-wheels-6-building-blocks.html#:~:text=An%20algo%20wheel%20is%20an,to%20mostly%20trader%2Ddirected%20flow. Accessed 24 Oct 2018

3. Bifet, A., Gavaldà, R., Holmes, G., Pfahringer, B.: Machine Learning for Data Streams, with Practical Examples in MOA. MIT Press (2018). https://doi.org/10.7551/mitpress/10654.001.0001

4. BoE: Machine learning in UK financial services (2019). http://www.bankofengland.co.uk/report/2019/machine-learning-in-uk-financial-services

5. Boonpeng, S., Jeatrakul, P.: Decision support system for investing in stock market by using OAA-neural network. In: 2016 Eighth International Conference on Advanced Computational Intelligence (ICACI), pp. 1–6 (2016). https://doi.org/10.1109/icaci.2016.7449794

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