Mirae Asset Global Investments to list 'TIGER Global MLCC & Substrate ETF' focused on key AI server components

[Financial News] Mirae Asset Global Investments will launch an exchange-traded fund (ETF) investing in companies in South Korea, Japan and Taiwan that produce multilayer ceramic capacitors (MLCCs) and semiconductor substrates, key components for artificial intelligence (AI) servers.
According to Mirae Asset Global Investments on the 19th, the 'TIGER Global MLCC & Substrate ETF' will invest in electronic components companies expected to see rising demand as investment in AI data centers expands.
As the AI industry expands from model training to inference, server computing loads and power consumption are increasing. As a result, the importance is growing of MLCCs, which maintain stable voltage, and substrates, which connect semiconductor chips.
AI server MLCCs, in particular, require high capacitance and reliability, limiting the number of companies capable of producing them. Mirae Asset Global Investments projected that demand for server MLCCs would grow by an average of 30% annually from 2025 to 2030. Demand for FC-BGA, a high-performance semiconductor substrate, is also expanding beyond CPUs to include GPUs and application-specific integrated circuits (ASICs).
The ETF tracks the 'Solactive-KEDI Global MLCC and Semiconductor Substrate Index.' The underlying index comprises 13 companies in South Korea, Japan and Taiwan. It allocates weights according to free-float market capitalization, while capping the weight of each individual constituent at 20%.
Major holdings include Samsung Electro-Mechanics, Japan's Murata and TDK, Taiwan's Unimicron, and Japan's Ibiden. The ETF also includes Yageo, Kyocera, Kinsus, Nanya PCB, Daeduck Electronics and Simmtech.
Mirae Asset Global Investments expects the competitiveness of companies with the production technology and facilities needed to make advanced components to become even more important as demand for MLCCs and semiconductor substrates grows with the increasing performance of AI servers.

[email protected] Lee Jeong-hwa Reporter