An optimal portfolio method based on real time prediction of gold and bitcoin prices

IF 3.2 Q2 AUTOMATION & CONTROL SYSTEMS
Zhongqi Miao, Wenxuan Huang
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引用次数: 0

Abstract

Aiming at the portfolio problem of gold and bitcoin with a given linear trading commission, this paper puts forward the stage implementation forecast and optimal portfolio model. In the aspect of data prediction, SMA is used to predict the initial data, LSTM is used to predict the price trend of long-term data, and daily updated real-time price data is predicted. Considering the risk aversion of investors, the heuristic algorithm is used to solve the daily trading strategy of maximizing utility from September 12th, 2016 to September 12th, 2021. The simulation analysis of the sliding window shows that the algorithm can realize reasonable prediction, which verifies the effectiveness of the algorithm.
基于黄金和比特币价格实时预测的最优投资组合方法
针对给定线性交易佣金的黄金和比特币组合问题,提出了阶段实施预测和最优组合模型。在数据预测方面,采用SMA对初始数据进行预测,采用LSTM对长期数据的价格趋势进行预测,并对每日更新的实时价格数据进行预测。考虑到投资者的风险规避,采用启发式算法求解2016年9月12日至2021年9月12日的效用最大化日交易策略。对滑动窗口的仿真分析表明,该算法能够实现合理的预测,验证了算法的有效性。
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来源期刊
Systems Science & Control Engineering
Systems Science & Control Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
9.50
自引率
2.40%
发文量
70
审稿时长
29 weeks
期刊介绍: Systems Science & Control Engineering is a world-leading fully open access journal covering all areas of theoretical and applied systems science and control engineering. The journal encourages the submission of original articles, reviews and short communications in areas including, but not limited to: · artificial intelligence · complex systems · complex networks · control theory · control applications · cybernetics · dynamical systems theory · operations research · systems biology · systems dynamics · systems ecology · systems engineering · systems psychology · systems theory
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