Speakers

Keynote Speakers

Prof. Hang (Robin) Luo

Deputy Vice Chancellor, Wuhan College, China

Research Area: FinTech, Corporate Finance, Financial Risk Management, International Finance

Introduction:Professor Hang (Robin) Luo, Ph.D., FRM, is the Deputy Vice Chancellor (Academic, Research, and International Affairs) and Distinguished Professor at Wuhan College. He is an editor-in-chief, associate editor, editorial board member of many international peer-reviewed academic journals, a Financial Risk Manager (FRM) charter holder, and a fellow member of the Global Association of Risk Professionals (GARP). He has published more than 80 articles in academic journals and conference proceedings. He has presented numerous keynote speeches and seminars at esteemed universities, such as University of Oxford and Peking University.

Speech title: How does second-largest shareholder influence earnings management of family listed firms? Evidence from China

Abstract: This paper investigates the influence of second-largest shareholder on the earnings management practice in 1952 family firms listed in the Shanghai and Shenzhen Stock Exchanges. Using a sample of around 20000 firm-year observations from 2000 to 2021, we find strong evidence that family listed firms with the presence of a second-largest shareholder holding more than 10% of the shares engage in less real earnings management than those without. And the shareholding percentage of the second-largest shareholder in family firms is negatively associated to the magnitude of real earnings management. 

For the accrual-based earnings management, though we use five different measures, none of them support our hypotheses. The empirical results suggest that the mutual supervision effect of the second-largest shareholder in the Chinese family firms listed in the stock markets might only prevail in the real earnings management, not in the accrual-based earnings management. 

Prof. Tai-Xiang Jiang

School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, China

Research Area: Tensor modeling and computing, computer vision, image processing, financial data mining, trusted artificial intelligence

Introduction: Dr. Jiang's primary research interests revolve around tensor modeling and computational methods.

His expertise has been acknowledged through numerous achievements, including an invitation to contribute a chapter to an academic monograph published by Elsevier. He has an impressive publication record with over 40 academic papers featured in esteemed journals and conferences. Notably, more than 10 of his papers have been recommended as Class A by the Chinese Computer Federation (CCF). His research contributions span reputable journals like Numer. Math., IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Image Processing (TIP), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Geoscience and Remote Sensing (TGRS), IEEE Transactions on Cybernetics (TCyb), as well as distinguished conferences in the field of artificial intelligence such as CVPR, AAAI, IJCAI, and ACM MM. Dr. Jiang's work has garnered over 1500 citations according to Google Scholar, and his publications have been acknowledged with the inclusion of four highly cited papers in the Essential Science Indicators (ESI).

Speech title: Low-Rank Tensor Modeling: From Image Processing to Stock Movements Prediction

Abstract: In many real-world scenarios, data is naturally structured as tensors, which generalize matrices to higher orders. This keynote speech focuses on exploring the inherent correlations within high-order tensors. To achieve this, we employ the fundamental mathematical concept of low-rankness, which captures the low-dimensionality of tensors. We begin by presenting the application of low-rank tensor modeling in the recovery of multi-dimensional images, encompassing videos, multi-spectral images, and MR images. Through incorporating prior knowledge about these multi-dimensional images, we demonstrate that leveraging such information leads to significant performance improvements. Numerical results further substantiate the efficacy of this approach.

Next, we delve into employing tensor low-rankness for predicting stock movements. By exploiting the invariance of correlations among different companies over short time periods, we propose a tensor robust component analysis model. This model effectively separates the low-rank components, which are subsequently utilized to train an attention-based Long Short-Term Memory (LSTM) network for prediction. Our results demonstrate the effectiveness of this strategy.

Prof. Li Dengfeng

School of Management and Economics, University of Electronic Science and Technology of China, China

Research Area: Fuzzy decision and System analysis; Artificial Intelligence and Intelligent decision; Blockchain technology and Big Data; Supply chain optimization and management; Economic management decision and game

Introduction: The Ministry of Education "Changjiang Scholar" distinguished professor, "tens of millions of talents Project" national candidate, and was awarded the national "outstanding contribution of young and middle-aged experts" honorary title; Enjoy the special government allowance experts of The State Council. Won the honorary title of "National Excellent Scientific and Technological Worker". Selected in Sichuan Province "Thousand talents Plan", Fujian Province university leading talent funding candidate, the third batch of "hundred people Plan" candidate, the Ministry of Education "New Century Outstanding Talent support plan". The first batch of recipients of the Ministry of Education's "Key Teachers Funding Plan for Colleges and Universities". From 2014 to 2018, he was selected as one of the "Most Cited Scholars in China".

He is now a professor at the School of Economics and Management, University of Electronic Science and Technology of China, and director of the Blockchain Big Data Intelligent Decision and Game Research Center. Doctoral supervisor in management science and Engineering, Business Management, Tourism Management, Economics and Industrial system management and other disciplines/majors. He was the leader of the science and technology innovation team of Fujian Provincial colleges and universities, the leader of the talent training and innovation team construction project of the central financial support for the development of local colleges and universities, the leader of the provincial key discipline construction project "Business Administration" in Fujian Province, and the leader and discipline leader of the Plateau project "Business Administration" of the high-level university construction discipline in Fuzhou University.

He is mainly engaged in the research of economic management decision-making and countermeasures (game), operation research and management. He has presided over more than 20 national, provincial and ministerial projects, including 1 sub-project of the National Science and Technology Innovation 2030-New Generation of artificial Intelligence major project of the Ministry of Science and Technology, 1 key project of the National Natural Science Foundation and 4 surface projects. He has won 30 scientific research awards such as the second prize of the National Natural Science Award, the second prize of the Provincial Natural Science Award, and the first prize of the Natural Science Award of the Ministry of Education Science and Technology Award. He has published 9 monographs funded by Springer and the National Science and Technology Academic Works Publishing Fund. He has published more than 300 papers in important journals at home and abroad such as OMEGA, EJOR, TRE, NRL, among which more than 200 papers have been included in SCI, SSCI, EI, etc., and he has cited more than 8000 times. More than 10 papers are ESI highly cited papers. One paper won the Outstanding Paper Award of IEEE Fuzzy Systems Journal 2013 by IEEE Society for Computational Intelligence. More than 10 papers in the journal TOP25.

Chairman of the Intelligent Decision and Game Branch of the Chinese Society of Advanced Selection Law and Economic Mathematics, and executive director of the Society of Management Science and Engineering. Editor-in-chief of International Journal of Fuzzy System Applications, Deputy editor of Group Decision and Negotiation and International Journal of Fuzzy System, editorial board member of Systems Engineering Theory and Practice, Control and Decision and other journals.

A. Prof. Azlina Binti Md Yassin

Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia

Research Area: Finance, Property and Business Services

Speech title: Consumer Perception Towards Real Estate Online Marketing

Abstract: Today’s internet usage is no longer limited as a networking media, but it is also being used as a main way of transaction for consumers at global market. The usage of internet was grown rapidly over the past years and it has become a major ways for delivery and trading information, services and goods. Therefore, the objectives of this study are to investigate the perception of people in buying real estate by using online medium marketing as well as to identify the key factors in influencing consumer decision towards marketing medium in online shopping for real estate product. This study adopted quantitative research approach in answering research objectives. The findings were based on the 320 set of questionnaires distributed to the professional workers and administration staffs in the Universiti Tun Hussein Onn Malaysia, and subsequently was analysed by using SPSS software. From the results, majority of the respondents were satisfied about the awareness of using online medium marketing due to the security, usefulness, ease of use, and privacy. Moreover, the results had identified six factors in influencing consumer decision towards online marketing namely; Confidentiality of Information, Experiences from forum groups, reliability information, Experiences from peers, saving time and convenience. Hopefully this research will help the sellers, marketers and researcher in improve visibility and reach a much bigger customer base hence it will improve profits by manipulating the available opportunities and also adding knowledge in marketing strategies.