Exploring the Cross-Correlations between Tesla Stock Price, New Energy Vehicles and Oil Prices: A Multifractal and Causality Analysis

IF 1.2 4区工程技术 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Fluctuation and Noise Letters Pub Date : 2024-03-20 DOI:10.1142/s021947752450024x

Xingyue Gong, Guo-Zhu Jia

{"title":"Exploring the Cross-Correlations between Tesla Stock Price, New Energy Vehicles and Oil Prices: A Multifractal and Causality Analysis","authors":"Xingyue Gong, Guo-Zhu Jia","doi":"10.1142/s021947752450024x","DOIUrl":null,"url":null,"abstract":"<p>The interaction between new energy vehicle (NEV) stock prices and the crude oil market is crucial for resource allocation and risk management. This study employs Multifractal detrended cross-correlation analysis (MF-DCCA) to investigate the multifractal characteristics of the cross-correlation between Tesla stock price (TSLA) and crude oil price (Brent), as well as between TSLA and other NEV stocks (excluding TSLA). The experimental results reveal long-term persistence and multiple fractal characteristics in the cross-correlations. Additionally, multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) demonstrates the asymmetry of the cross-correlation during upward or downward trends between TSLA and Brent, as well as between TSLA and other NEV stocks (excluding TSLA). Furthermore, utilizing the transfer entropy (TE) method, we assess the strength and direction of information flows between TSLA and Brent, and between TSLA and other NEV stocks (excluding TSLA). Interestingly, we observe bidirectional information transmission between TSLA and other NEV stocks, while only unidirectional information transmission from NIO to TSLA is evident. These findings provide valuable insights for resource allocation, supply chain management and sustainable development strategies for decision-makers in the NEV market.</p>","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":"13 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fluctuation and Noise Letters","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1142/s021947752450024x","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}

引用次数: 0

Abstract

The interaction between new energy vehicle (NEV) stock prices and the crude oil market is crucial for resource allocation and risk management. This study employs Multifractal detrended cross-correlation analysis (MF-DCCA) to investigate the multifractal characteristics of the cross-correlation between Tesla stock price (TSLA) and crude oil price (Brent), as well as between TSLA and other NEV stocks (excluding TSLA). The experimental results reveal long-term persistence and multiple fractal characteristics in the cross-correlations. Additionally, multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) demonstrates the asymmetry of the cross-correlation during upward or downward trends between TSLA and Brent, as well as between TSLA and other NEV stocks (excluding TSLA). Furthermore, utilizing the transfer entropy (TE) method, we assess the strength and direction of information flows between TSLA and Brent, and between TSLA and other NEV stocks (excluding TSLA). Interestingly, we observe bidirectional information transmission between TSLA and other NEV stocks, while only unidirectional information transmission from NIO to TSLA is evident. These findings provide valuable insights for resource allocation, supply chain management and sustainable development strategies for decision-makers in the NEV market.

查看原文本刊更多论文

探索特斯拉股价、新能源汽车和石油价格之间的交叉相关性：多分形和因果关系分析

新能源汽车（NEV）股票价格与原油市场之间的相互作用对于资源配置和风险管理至关重要。本研究采用多分形去趋势交叉相关分析法（MF-DCCA）研究特斯拉股票价格（TSLA）与原油价格（布伦特）之间以及特斯拉与其他新能源汽车股票（不包括特斯拉）之间交叉相关的多分形特征。实验结果揭示了交叉相关性的长期持续性和多重分形特征。此外，多分形非对称去趋势交叉相关分析（MF-ADCCA）显示了 TSLA 和布伦特以及 TSLA 和其他 NEV 股票（不包括 TSLA）之间在上升或下降趋势中交叉相关的非对称性。此外，我们还利用转移熵 (TE) 方法评估了 TSLA 和布伦特之间以及 TSLA 和其他 NEV 股票（不包括 TSLA）之间的信息流强度和方向。有趣的是，我们观察到 TSLA 与其他 NEV 股票之间存在双向信息传递，而从 NIO 到 TSLA 之间只有明显的单向信息传递。这些发现为新能源汽车市场决策者的资源分配、供应链管理和可持续发展战略提供了宝贵的启示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Fluctuation and Noise Letters 工程技术-数学跨学科应用

CiteScore

2.90

自引率

22.20%

发文量

审稿时长

>12 weeks

期刊介绍： Fluctuation and Noise Letters (FNL) is unique. It is the only specialist journal for fluctuations and noise, and it covers that topic throughout the whole of science in a completely interdisciplinary way. High standards of refereeing and editorial judgment are guaranteed by the selection of Editors from among the leading scientists of the field. FNL places equal emphasis on both fundamental and applied science and the name "Letters" is to indicate speed of publication, rather than a limitation on the lengths of papers. The journal uses on-line submission and provides for immediate on-line publication of accepted papers. FNL is interested in interdisciplinary articles on random fluctuations, quite generally. For example: noise enhanced phenomena including stochastic resonance; 1/f noise; shot noise; fluctuation-dissipation; cardiovascular dynamics; ion channels; single molecules; neural systems; quantum fluctuations; quantum computation; classical and quantum information; statistical physics; degradation and aging phenomena; percolation systems; fluctuations in social systems; traffic; the stock market; environment and climate; etc.