Wavelet Analysis on APPL and TSLA by Using R

Qinyi Ruan

2022

Abstract

In this paper, we created and analyzed the time series plots of Apple and Tesla stock prices over the past 2 years and wavelet coherence plots connecting them by using R. We found a causal relationship between AAPL and TSLA in different frequency bands: In the first half of 2020, and from 2022 to the present, TSLA and AAPL interact with each other in the 0-128 frequency bands, showing a positive correlation. From the second half of 2020 to the first half of 2021, there was a positive correlation interaction in the 32-128 frequency bands between AAPL and TSLA. Our study provides several significant supports for investors and scholars. For example, in the general environment of vigorous development of clean energy, helping to predict the trends of Apple, Tesla and other similar companies' stock prices in the future, providing a reference not only for Apple and Tesla to compete and develop in the future, but also for other companies with similar conditions to forecast, estimate the company's competitive strength and formulate long-term development strategies.

Paper Citation

in Harvard Style

Ruan Q. (2022). Wavelet Analysis on APPL and TSLA by Using R. In Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME; ISBN 978-989-758-636-1, SciTePress, pages 439-444. DOI: 10.5220/0012034300003620

in Bibtex Style

@conference{icemme22,
author={Qinyi Ruan},
title={Wavelet Analysis on APPL and TSLA by Using R},
booktitle={Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME},
year={2022},
pages={439-444},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012034300003620},
isbn={978-989-758-636-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME
TI - Wavelet Analysis on APPL and TSLA by Using R
SN - 978-989-758-636-1
AU - Ruan Q.
PY - 2022
SP - 439
EP - 444
DO - 10.5220/0012034300003620
PB - SciTePress