On SGX's Voyage to Corporate Sustainability:
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On SGX's Voyage to Corporate Sustainability:
Exploring Emerging Topics in Multi-Industry Corpora
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- 0 Rating
- 0 Reviews
- 75 Students Enrolled
Requirements
- DEDA Class Knowledge
General Overview
Description
Topic modeling and LDA (Latent Dirichlet Allocation) have proven valuable in various fields as an innovative approach to studying ar- eas of interest and identifying topics in a dynamic content. The un- derlying assumption is that techniques like LDA can swiftly capture emerging topics in textual documents compared to other categoriza- tion tools. These unsupervised approaches have been used to identify new industries and technological domains. However, our study on the nascent topic of “sustainability” within the corpora of SGX-listed companies highlights clear limitations in employing techniques like LDA on sparse data. The dynamic LDA approach, also called DTM (Dynamic Topic Modelling),based on an 11-year database of annual reports from publicly listed companies in Singapore, could not detect sustainability’s rise as a critical topic in corporate practice following policy changes. Moreover, despite sustainability reporting becoming mandatory, sustainability-related topics may still not receive signifi- cant attention.
Courses that include this CL
Meet the instructors !
Wolfgang Karl HÄRDLE attained his Dr. rer. nat. in Mathematics at Universität Heidelberg in 1982 and in 1988 his habilitation at Universität Bonn. He is Ladislaus von Bortkiewicz Professor of Statistics at Humboldt-Universität zu Berlin and the director of the Sino German Graduate School (洪堡大学 + 厦门大学) IRTG1792 on “High dimensional non stationary time series analysis”. He also serves as head of the joint BRC blockchain-research-center.com (with U Zürich). He is guest professor at WISE, Xiamen U, SMU, Singapore, NYCU, Hsinchu TW, Charles U, Prague CZ.
His research focuses on data sciences, dimension reduction and quantitative finance. He has published over 30 books and more than 300 papers in top statistical, econometrics and finance journals. He is highly ranked and cited on Google Scholar, REPEC and SSRN. He has professional experience in financial engineering, SMART (Specific, Measurable, Achievable, Relevant, Timely) data analytics, machine learning and cryptocurrency markets. He has created the www.quantlet.com platform, a financial risk meter, FRM hu.berlin/frm, a cryptocurrency index, CRIX www.royalton-crix.com and organises regularly blockchainnights.com . He is 玉山学者 （Yushan Scholar), web page hu.berlin/wkh