Prediction of the Best Portfolio for Bitcoin and Gold based on the ARIMA Model
DOI:
https://doi.org/10.54097/fbem.v4i3.1284Keywords:
ARIMA model, Bitcoin, Gold.Abstract
With the prosperity of the financial market, more and more people are involved in securities trading. How to combine investment in bitcoin and gold to achieve the highest profit is one of the issues that market traders think about. To solve this problem, we build a model that predicts future prices in order to better help investors. We constructed an ARIMA model through differential stationarity processing, AEC, white noise test and other methods, and used the data of the current day and the previous day to predict the price of the next day. At the same time, we use the model to predict the average for the next N days. If it is predicted that the price of the asset will decrease in the future, it will be sold on the same day. If the price of the asset will increase in the future, and the income obtained is greater than the transaction cost and the expected income of the investor, the purchase will continue until the end. Last until the last day $323841.52. Finally, it can be verified that the accuracy of the ARIMA model is the highest by comparing other mainstream machine learning models. In other words, the ARIMA model is the best strategy for this problem.
Downloads
References
Huiping Huang, Bloomberg. Market Valuation and Value Investment Strategy —— Based on China Securities Market [J]. Accounting Research, 2010, (10): 40-46 + 96.
Xin Yang,Zhanhui Chen. Empirical research on inertia and reverse investment strategy in Chinese stock market [J]. Journal of Tsinghua University (Natural Science Edition), 2004, (06): 758-761.
Peng Zhang. No comparative mean-variance and mean-VaR portfolio studies without short selling [J]. China Management Science, 2008, (04): 30-35.
Lei Yuan. Study on Stock Index Prediction based on the ARIMA-LSSVM mixed model [D]. Harbin Institute of Technology, 2015.
Tianlun Yu. Research on Stock Investment Strategy Based on Piotroski Method and ARIMA-SVR Model [D]. South China University of Technology, 2016.
Liping Xu,Mingzhi Luo. Short-term analysis and prediction of gold prices based on the ARIMA model [J]. Financial Science, 2011 (01): 26-34.
Yan Zhang. Prediction of the RMB exchange rate based on the ARIMA and GRNN combination model [D]. Hubei University of Technology, 2017.
Jingwen Fei. Analysis and prediction of Gold Futures Price in China based on ARIMA model [J]. Contemporary Economy, 2017 (09): 148-150.
Libin Zhu. Application of the ARIMA model in stock market prediction [J]. Jiangsu statistics, 1999 (01): 27-28.
Shuang Ji. Predictive and empirical study of the RMB exchange rate based on the ARIMA-SVM combination model [D]. Jiangxi University of Finance and Economics, 2019.
Lei Ding,Wanshan Guo. Gold price prediction study based on the ARIMA-GARCH family mixed model [J]. Journal of Xuchang College, 2019,38 (06): 124-129.
