Author(s)

Yi Qiao, Chuqing Zhang, Kaiwen Xu

Corresponding Author

Chuqing Zhang

ABSTRACT

With the innovation of computer technology and the progress of financial engineering theory, mathematical finance and quantitative trading strategies have become a hot field of research. This article mainly focuses on using the predicted data obtained from the time series model and establishing evaluation models to provide transaction decisions that maximize returns. ARIMA models, entropy, and TOPSIS methods are used to find solutions. We have built ARIMA models based on the given daily price data of Bitcoin and gold, providing predicted data for subsequent analysis. We obtained some basic indicators from the predicted and actual historical data, respectively. We also used the entropy weight method for empowerment to construct the secondary indicators further. By using these metrics, scoring was performed using the TOPSIS model.

KEYWORDS

ARIMA model, entropy weight method, TOPSIS method, quantitative transaction