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Academic Journal of Computing & Information Science, 2022, 5(7); doi: 10.25236/AJCIS.2022.050713.

Prediction on the Value Trends of Bitcoin and Gold-on Account of ARMA Time Series Forecasting Model

Author(s)

Ronghuan Li, Weijie Chen, Wenhao Xu, Chen Li

Corresponding Author:
Ronghuan Li
Affiliation(s)

School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu, China

Abstract

In this paper, we aimed to build a quantitative investment trading model based on a combination of a multivariate cycle ARMA model and Apriori. We first note that in order to have a sound investment strategy, a forecast for the next trading day needs to be made. To do this, a basic time series forecasting model was first built to predict the value of gold and bitcoin for the next day based on the market volatility of the previous 40 days. The next step is developing a trading strategy model with a stable rate of return and some risk tolerance. At the same time, we developed a fixed stop-loss strategy to protect the strategy's stability and improve the risk resistance performance. Ultimately, using this model, we calculated that on 10 September 2021, we will have a return of $4816941 in Bitcoin and $1129.0503 in gold.

Keywords

Quantitative Trading; Trading Strategies; Apriori; ARMA model; time series forecasting model

Cite This Paper

Ronghuan Li, Weijie Chen, Wenhao Xu, Chen Li. Prediction on the Value Trends of Bitcoin and Gold-on Account of ARMA Time Series Forecasting Model. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 7: 79-84. https://doi.org/10.25236/AJCIS.2022.050713.

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