Improved Markowitz portfolio investment model based on ARIMA model and BP neural network

Jian-Bang Lin
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引用次数: 1

Abstract

A new attempt to apply the ARIMA model and BP neural network algorithm to the daily price prediction of Bitcoin is shown in the paper, and the prediction results performed well. Compared to the ARIMA model, the BP neural network has stronger short-term predictive power for bitcoin price prediction. Second, we apply a modified Markowitz portfolio investment model to the bitcoin portfolio problem. We model the daily price data of gold and bitcoin for October 2016 and calculate that the local optimal return for October is 0.1418, the local minimum risk is 0.000174, and the local optimal portfolio investment of USD, gold, and bitcoin is [8389.8337,0,2.4691].
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基于ARIMA模型和BP神经网络的改进Markowitz组合投资模型
本文将ARIMA模型和BP神经网络算法应用于比特币每日价格预测的新尝试,预测结果良好。与ARIMA模型相比,BP神经网络对比特币价格的短期预测能力更强。其次,我们将改进的Markowitz组合投资模型应用于比特币投资组合问题。我们对2016年10月黄金和比特币的每日价格数据进行建模,计算出10月的局部最优收益为0.1418,局部最小风险为0.000174,美元、黄金和比特币的局部最优组合投资为[8389.8337,0,2.4691]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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