Discover TEJ’s latest product updates and events.
Discover TEJ’s highlights from Neudata Hong Kong Data Summit. Explore our structured Earnings Call Transcripts, 11 categories of PIT Factor Library, and high-fidelity Market Data for Asia.
TEJ held the “TCRI 2026 Industry Outlook Seminar” on March 20, offering an in-depth analysis of how the rapidly changing global political and economic landscape is affecting Taiwan’s industries and creating new development opportunities. The seminar also explored how the rapid evolution of AI is shaping a polarized development pattern in Taiwan’s electronics industry. The seminar covered a broad range of macro-level topics, including the impact of the Middle East conflict on the international political and economic environment, the challenges and transformation faced by traditional industries amid geopolitical tensions, and how Taiwan’s electronics industry is diverging into two distinct development trajectories under the AI trend. The seminar aimed to provide Taiwan’s industrial sector with a clearer roadmap for future development.
Earnings call transcript provides an AI-generated, structural text data solution for Taiwanese corporate earnings calls. By transforming unstructured MOPS audio into searchable text, it enables researchers to execute text mining, sentiment analysis, and keyword tracking. This product bridges corporate qualitative disclosures with quantitative financial research, empowering quantitative funds and analysts to capture market-moving insights efficiently.
Quantitative Investing requires historical data to perform backtesting, examining the feasibility of our investing strategy. Therefore, it is pivotal to ensure that the data used for analyzing always aligns with the information the investors have when making their decisions. For instance, in order to pursue correctness, accounting databases update new numbers when financial restatements occur. However, using the data after financial restatement for backtesting will prevent investors from accurately reconstructing the actual market conditions at that time, and will lead to information bias, reducing the credibility of the backtesting result.