Interpreting the "Black Swan" Case of United Petrochemical from the Perspective of Behavioral Finance

Research Article
Open access

Interpreting the "Black Swan" Case of United Petrochemical from the Perspective of Behavioral Finance

Le Yu 1*
  • 1 School of Finance, Central University of Finance and Economics, Beijing, China    
  • *corresponding author 2024310446@email.cufe.edu.cn
AEMPS Vol.188
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-175-4
ISBN (Online): 978-1-80590-176-1

Abstract

Most of the huge losses of Chinese financial enterprises in the international market are concentrated in the failure of gambling with enterprises in other countries, which is not only due to the mistakes in internal management decisions, but also due to the deliberate set-up of the counterparty through the skillful application of psychological principles. However, most of the current case studies focus on the discussion of the internal management of enterprises, and there is a lack of psychological research based on counterparties. This study aims to analyze and summarize the case studies from the perspective of behavioral finance, deeply explore the psychological principles of China's losses in the international market, and propose corresponding prevention plans. Based on the perspective of the counterparty Goldman Sachs Group, combined with existing research and behavioral finance theories, this study will expose the psychological trap of Sinopec and Sinopec's "black swan" huge losses in 2019 through stage discussion and detailed analysis. Through case review and theoretical analysis, it is found that counterparties such as Goldman Sachs Group mainly use the principles of behavioral finance, and take advantage of China's financial market's incomplete knowledge reserve of derivatives and operation and management methods, and design relevant psychological traps in a targeted manner. On the basis of understanding the relevant principles, it is proposed to strengthen the learning and mastery of behavioral finance theories of corporate management, and improve the ability to identify and dismantle psychological traps, so as to better prevent losses caused by psychological induction.

Keywords:

Behavioral finance, Psychological traps, Counterparty perspectives

Yu,L. (2025). Interpreting the "Black Swan" Case of United Petrochemical from the Perspective of Behavioral Finance. Advances in Economics, Management and Political Sciences,188,44-49.
Export citation

References

[1]. Yining Zhang. (2019). Case Study of Huge Losses in United Petrochemical Futures Trading, Hebei University of Geosciences.

[2]. Wei Xie. (2019) 46 million yuan! Why did Sinopec repeat the "huge loss of China Aviation Oil"?. China Economic Weekly, (03),67-69.

[3]. North Evening Online. (2019). Sinopec's "black swan" event landed in 2018, and its net profit hit a new high in the past five years. Retrieved from https://baijiahao.baidu.com/s?id=1623872601622548100&wfr=spider&for=pc

[4]. Xiaozhou Han, & Shuxin Yuan. (2025). Manager Overconfidence, Analyst Concern and Stock Price Crash Risk. Chinese market, (03),32-36.

[5]. Min Shan. (2024). Breaking through "anchoring" to cultivate empirical awareness. Education, (29),98-100.

[6]. Junmei Lan, Xuguang Hao, & Shun Li. (2017). Research on the irrational bias of securities regulators caused by fear of error. International Business (Journal of University of International Business and Economics), (04),113-123.

[7]. Chenyu Guo. (2023). Herd Psychology - The "Nirvana" of Salesmen, Xiandai Banzu, (08),41.

[8]. Yang Song, Yaocheng Shi & Guangsu Zhou. (2024). Wage premium and formation mechanism of state-owned enterprises. Economic Theory and Economic Management,44(07),72-85.

[9]. Siying Wang. (2024). A study on the venture capital contract model considering both overconfidence and loss aversion. Journal of the Neijiang Teachers College.,39(08),91-95.

[10]. Dayu Han, Yang Li, & Zhida Yuan. (2019). Analysis and reflection on Sinopec's huge loss incident. Plastic packaging, 29(01), 55-58.

Cite this article

Yu,L. (2025). Interpreting the "Black Swan" Case of United Petrochemical from the Perspective of Behavioral Finance. Advances in Economics, Management and Political Sciences,188,44-49.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 3rd International Conference on Management Research and Economic Development

ISBN：978-1-80590-175-4(Print) / 978-1-80590-176-1(Online)
Editor：Lukáš Vartiak
Conference website: https://2025.icmred.org/
Conference date: 30 May 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.188
ISSN：2754-1169(Print) / 2754-1177(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).

References

[1]. Yining Zhang. (2019). Case Study of Huge Losses in United Petrochemical Futures Trading, Hebei University of Geosciences.

[2]. Wei Xie. (2019) 46 million yuan! Why did Sinopec repeat the "huge loss of China Aviation Oil"?. China Economic Weekly, (03),67-69.

[3]. North Evening Online. (2019). Sinopec's "black swan" event landed in 2018, and its net profit hit a new high in the past five years. Retrieved from https://baijiahao.baidu.com/s?id=1623872601622548100&wfr=spider&for=pc

[4]. Xiaozhou Han, & Shuxin Yuan. (2025). Manager Overconfidence, Analyst Concern and Stock Price Crash Risk. Chinese market, (03),32-36.

[5]. Min Shan. (2024). Breaking through "anchoring" to cultivate empirical awareness. Education, (29),98-100.

[6]. Junmei Lan, Xuguang Hao, & Shun Li. (2017). Research on the irrational bias of securities regulators caused by fear of error. International Business (Journal of University of International Business and Economics), (04),113-123.

[7]. Chenyu Guo. (2023). Herd Psychology - The "Nirvana" of Salesmen, Xiandai Banzu, (08),41.

[8]. Yang Song, Yaocheng Shi & Guangsu Zhou. (2024). Wage premium and formation mechanism of state-owned enterprises. Economic Theory and Economic Management,44(07),72-85.

[9]. Siying Wang. (2024). A study on the venture capital contract model considering both overconfidence and loss aversion. Journal of the Neijiang Teachers College.,39(08),91-95.

[10]. Dayu Han, Yang Li, & Zhida Yuan. (2019). Analysis and reflection on Sinopec's huge loss incident. Plastic packaging, 29(01), 55-58.

For authors
Guide for authors Policies for authors Aims and scope Subscription Open access policy
For editors
Policies for editors Editorial board
For reviewers
Policies for reviewers Privacy policy

Cookies are used by this site.
Copyright © 2024 EWA Publishing, its licensors, and contributors. All rights reserved, including text and data mining, AI training, and similar technologies.