Valuation of PV Enterprises Based on Residual Income Model--Taking Longi Green Energy as an Example

DOI

10.2991/978-94-6463-534-8_11How to use a DOI?

Keywords

Photovoltaic firms; Residual income model; DuPont analysis; Mutation series method

Abstract

Under the current background of increasing global environmental problems, the development of photovoltaic (PV) industry has increasingly attracted the attention of countries all over the world, and how to scientifically and reasonably assess the value of PV enterprises is an important issue in China’s capital market. By combining the characteristics of photovoltaic enterprises themselves, this paper chooses to adopt the residual income method as the basic model, and applies the DuPont analysis method and the mutation level method to make the corresponding model improvement in order to improve the accuracy of the valuation results. Compared with the actual value, the deviation rate is only 1.2%, which is a small error, proving that the improved model can reflect the intrinsic value of PV enterprises more accurately and provide investors with more accurate value reference.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yue Liu
AU  - Renwei Hang
AU  - Jiajun Zhu
PY  - 2024
DA  - 2024/10/14
TI  - Valuation of PV Enterprises Based on Residual Income Model--Taking Longi Green Energy as an Example
BT  - Proceedings of the 4th International Conference on Internet Finance and Digital Economy (ICIFDE 2024)
PB  - Atlantis Press
SP  - 108
EP  - 125
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-534-8_11
DO  - 10.2991/978-94-6463-534-8_11
ID  - Liu2024
ER  -