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Algorithm transaction system and algorithm transaction model training method based on the system

A trading system and training method technology, applied in biological neural network models, computing, instruments, etc., can solve the problem of not fully excavating the inherent characteristics of the stock market.

Pending Publication Date: 2021-08-20
NANJING UNIV
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Problems solved by technology

Traditional algorithmic trading strategies are based on information such as prices and trading volumes in the stock market, perform some calculations and guide the execution of transactions, and have not fully explored the inherent characteristics of the stock market

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  • Algorithm transaction system and algorithm transaction model training method based on the system
  • Algorithm transaction system and algorithm transaction model training method based on the system

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Embodiment Construction

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0027] It should be noted that the terms "first" and "second" in the description and claims of the present application and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It should be understood that the data so used may be interchanged under appropriate circumstances for...

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Abstract

The invention discloses an algorithm transaction system based on a self-attention mechanism and an algorithm transaction model training method based on the system. The system comprises: a full-connection neural network module which is used for carrying out feature extraction, conversion and mapping on input transaction data; the self-attention mechanism module that is used for measuring different importance degrees of features at different moments and extracting relatively important effective information; and the long and short term memory network module that is used for outputting a transaction decision according to the serialized information processed by the self-attention mechanism module. The training method comprises the following steps: training a strategy function pi and a value function V by using a near-end strategy optimization algorithm, wherein the parameters of the strategy function pi and the value function V are respectively theta and theta; The invention provides an algorithm transaction system based on a self-attention mechanism and an algorithm transaction model training method based on the system. According to the invention, the advantages of a near-end strategy optimization algorithm and a long-short term memory network are combined, so that deep mining of market features is realized.

Description

technical field [0001] The present application relates to the technical field of algorithmic trading, in particular, to an algorithmic trading system based on a self-attention mechanism and a training method for an algorithmic trading model based on the system. Background technique [0002] The modern stock market itself is a highly complex system, and algorithmic trading is gaining prominence in order to reduce costs in trade execution. The core of algorithmic trading is to use computer programs to convert large orders into a combination of many small orders, so as to find the best transaction execution path and reduce the cost incurred in the process. Traditional algorithmic trading strategies are based on information such as prices and trading volumes in the stock market, perform some calculations and guide the execution of transactions, and have not fully explored the inherent characteristics of the stock market. Contents of the invention [0003] In order to solve th...

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Application Information

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IPC IPC(8): G06Q40/04G06N3/04
CPCG06Q40/04G06N3/044
Inventor 俞扬詹德川周志华雷宇
Owner NANJING UNIV
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