Gold and stock trading decision-making system based on ARIMA and DP

Wenmin Liu; Yishan Qian; Xingkai Wen; Zhiji Yang

doi:10.1117/12.2646312

23 August 2022 Gold and stock trading decision-making system based on ARIMA and DP

Wenmin Liu, Yishan Qian, Xingkai Wen, Zhiji Yang

Proceedings Volume 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022); 123300O (2022) https://doi.org/10.1117/12.2646312
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 2022, Huzhou, China

Abstract

As a product of the market economy, the stock market plays a crucial role in the financial field of a country. And gold as an important choice for hedging and maintaining value, it has also attracted wide attention. To help traders make the best decisions based on historical data, this paper establishes prediction and decision models for gold and equity data. Firstly, the time series prediction model Autoregressive Comprehensive Moving Average model (ARIMA) is used to analyze the historical data and predict the results of the next day. After that, based on the principle of maximizing returns, a decision model is established based on dynamic programming (DP) to develop the best portfolio for investors. The sensitivity of the transaction cost of the decision model is analyzed according to real transaction rules. It provides a more accurate model for the relationship between variables in the financial market. The quantitative investment decision model established in this paper has certain practical value and can provide a certain reference for investors in the financial market.

Citation Download Citation

Wenmin Liu, Yishan Qian, Xingkai Wen, and Zhiji Yang "Gold and stock trading decision-making system based on ARIMA and DP", Proc. SPIE 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 123300O (23 August 2022); https://doi.org/10.1117/12.2646312

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