Digital Assets and the Global Economy: How the Use of Statistical Models Can Help Bitcoin Price Prediction

IF 7.6 1区 经济学 Q1 ECONOMICS Review of Economics and Statistics Pub Date : 2023-05-02 DOI:10.21686/2500-3925-2023-2-68-79
L. Bakumenko, N. S. Vasileva
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Abstract

The purpose of the study is to analyze the potential of statistical modeling in predicting the prices of the Bitcoin cryptocurrency and its impact on the economy. In the course of the article, answers were received to such questions as: What is the impact of macroeconomic events on the dynamics of the Bitcoin price? How quickly does the cryptocurrency market stabilize after the falls? How effective is statistical modeling to solve the problem of predicting the price of Bitcoin? Which model shows the best results? What measures of regulation and control of the cryptocurrency market are necessary at the stage of its formation in the Russian Federation?Materials and methods. Historical data on average monthly Bitcoin closing prices and macroeconomic events such as the COVID-19 pandemic and the Russian-Ukrainian conflict were collected and analyzed. The paper uses statistical models, including ARIMA and LSTM, to predict future Bitcoin prices based on historical data. The accuracy of the models was calculated based on such indexes as the mean absolute error (MAE) and the mean square error (MSE). Results. Analysis of the impact of macroeconomic events showed that during the crisis, the attractiveness of Bitcoin increased and investors used this asset as a new investment tool. During the analysis of the consequences of the Russian-Ukrainian conflict for the cryptocurrency market, its reaction to geopolitical events was revealed according to the increased liquidity indexes in the market. In the process of modeling the dynamics of the average monthly Bitcoin price, the model with parameters (1, 1, 0) at MAE = 15.03% was recognized as the best ARIMA model. The LSTM neural network model on a similar data set showed a MAE error equal to 2.57%.Conclusion. The analysis shows that itcoin was the most attractive investment tool during the crisis, which led to a sharp increase in its price in 2021. The Russian-Ukrainian conflict has also affected its price, causing a significant decline in 2022. However, statistical modeling methods predict an increase in the price of Bitcoin in the first half of 2023, and governments may consider regulating or controlling its use to reduce risks associated with the cryptocurrency market. The recommended measures are the introduction of regulations, the introduction of transaction taxes, the development of national digital currencies, public education and the prevention of criminal activity.
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数字资产与全球经济:统计模型如何帮助比特币价格预测
该研究的目的是分析统计模型在预测比特币加密货币价格及其对经济影响方面的潜力。在这篇文章的过程中,我们收到了以下问题的答案:宏观经济事件对比特币价格动态的影响是什么?在下跌之后,加密货币市场稳定的速度有多快?统计建模在解决预测比特币价格的问题上有多有效?哪种模型效果最好?在俄罗斯联邦的加密货币市场形成阶段,需要采取哪些监管措施?材料和方法。收集并分析了比特币月均收盘价和新冠肺炎疫情、俄乌冲突等宏观经济事件的历史数据。本文使用包括ARIMA和LSTM在内的统计模型,根据历史数据预测未来的比特币价格。根据平均绝对误差(MAE)和均方误差(MSE)等指标计算模型的精度。结果。对宏观经济事件影响的分析表明,在危机期间,比特币的吸引力增加,投资者将这种资产作为新的投资工具。在分析俄乌冲突对加密货币市场的影响时,根据市场流动性指数的增加,揭示了其对地缘政治事件的反应。在对比特币月平均价格动态建模的过程中,在MAE = 15.03%时,参数(1,1,0)的模型被认为是最佳的ARIMA模型。LSTM神经网络模型在相似数据集上的MAE误差为2.57%。分析显示,在危机期间,比特币是最具吸引力的投资工具,这导致其价格在2021年大幅上涨。俄乌冲突也影响了其价格,导致其在2022年大幅下跌。然而,统计建模方法预测,比特币的价格将在2023年上半年上涨,政府可能会考虑监管或控制比特币的使用,以降低与加密货币市场相关的风险。建议的措施是引入法规,引入交易税,发展国家数字货币,公共教育和预防犯罪活动。
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来源期刊
CiteScore
8.50
自引率
0.00%
发文量
175
期刊介绍: The Review of Economics and Statistics is a 100-year-old general journal of applied (especially quantitative) economics. Edited at the Harvard Kennedy School, the Review has published some of the most important articles in empirical economics.
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