Digital Currency Price Analysis Via Deep Forecasting Approaches for Business Risk Mitigation

Muhammad Raheel Raza, A. Varol
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引用次数: 2

Abstract

Bitcoin, the most well-known of all the cryptocurrencies, have attracted a lot of attention thus far, and their prices have been quite volatile. While some research employ traditional statistical and econometric methods to discover the factors that drive Bitcoin prices, experimenting on the development of prediction models to be utilized as decision support aids in investment approaches is uncommon. The sudden rise and fall of cryptocurrency rates affects the economies and future perspectives of various businesses. In order to minimize business risks, to track the differences and avoid serious economic loss, prediction of daily digital currency rates becomes a crucial task. Our study performs a comparative analysis of Bitcoin price prediction utilizing efficient neural network techniques such as LSTM and GRU. A better RNN-based approach is derived as a result of the study. This approach will assist to facilitate a secure environment for businesses and to alarms to carryout risk management tasks for business risk mitigation purposes.
基于商业风险降低的深度预测方法的数字货币价格分析
比特币是所有加密货币中最知名的,迄今为止吸引了很多关注,其价格波动很大。虽然一些研究采用传统的统计和计量经济学方法来发现驱动比特币价格的因素,但试验开发预测模型作为投资方法中的决策支持辅助工具并不常见。加密货币利率的突然涨跌影响着经济和各种企业的未来前景。为了最大限度地降低业务风险,跟踪差异,避免严重的经济损失,预测每日数字货币汇率成为一项至关重要的任务。我们的研究利用高效的神经网络技术(如LSTM和GRU)对比特币价格预测进行了比较分析。基于rnn的更好的方法是研究的结果。这种方法将有助于为企业创造安全的环境,并有助于执行风险管理任务,以减轻企业风险。
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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