The progress of State-of-art Arbitrage Models Based on Bigdata Analysis and Machine Learning Approaches
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DOI: 10.23977/FMESS2022.039
Corresponding Author
Hongpu Chen
ABSTRACT
Starting from the principle of arbitrage, this article introduces the traditional arbitrage models in different forms. Subsequently, the designs of arbitrage model based on big data and neural network in the field of modern innovation are demonstrated, and empirical results are given for evaluation. Afterwards, the drawbacks of the state-of-art models are discussed and the future prospects are proposed accordingly. Overall, these results offer a guideline for future arbitrage models construction.
KEYWORDS
Arbitrage, Underlying Assets, Big Data, Artificial Intelligence
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