High-Frequency Trading Strategy Based on Deep Neural Networks

Author(s):  
Andrés Arévalo ◽  
Jaime Niño ◽  
German Hernández ◽  
Javier Sandoval
2019 ◽  
Vol 9 (9) ◽  
pp. 1796 ◽  
Author(s):  
Rundo ◽  
Trenta ◽  
di Stallo ◽  
Battiato

Grid algorithmic trading has become quite popular among traders because it shows several advantages with respect to similar approaches. Basically, a grid trading strategy is a method that seeks to make profit on the market movements of the underlying financial instrument by positioning buy and sell orders properly time-spaced (grid distance). The main advantage of the grid trading strategy is the financial sustainability of the algorithm because it provides a robust way to mediate losses in financial transactions even though this also means very complicated trades management algorithm. For these reasons, grid trading is certainly one of the best approaches to be used in high frequency trading (HFT) strategies. Due to the high level of unpredictability of the financial markets, many investment funds and institutional traders are opting for the HFT (high frequency trading) systems, which allow them to obtain high performance due to the large number of financial transactions executed in the short-term timeframe. The combination of HFT strategies with the use of machine learning methods for the financial time series forecast, has significantly improved the capability and overall performance of the modern automated trading systems. Taking this into account, the authors propose an automatic HFT grid trading system that operates in the FOREX (foreign exchange) market. The performance of the proposed algorithm together with the reduced drawdown confirmed the effectiveness and robustness of the proposed approach.


2021 ◽  
pp. 1-1
Author(s):  
Venu Babu Thati ◽  
Nikolay Smagin ◽  
Hatem Dahmani ◽  
Julien Carlier ◽  
Ihsen Alouani

2020 ◽  
Author(s):  
Peter Decrem ◽  
Sasha Stoikov ◽  
Shuo Shen ◽  
Jiaxin Yin ◽  
Yikai Hua ◽  
...  

Author(s):  
Alex Hernández-García ◽  
Johannes Mehrer ◽  
Nikolaus Kriegeskorte ◽  
Peter König ◽  
Tim C. Kietzmann

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