Kiwoom Launches U.S. AI Tech High Beta ETF with Passive Strategy

Kiwoom Asset Management announced Wednesday it will list the "KIWOOM U.S. AI Tech High Beta" ETF on the Korea Exchange's main board on May 12. The fund invests in U.S. innovative technology companies with high growth elasticity through a passive strategy. This approach marks a departure from traditional thematic ETFs that often struggle to keep pace with rapidly shifting market flows.

The product addresses a specific pain point in the ETF market. Existing thematic funds are typically structured around static industry classifications or fixed keywords. By the time a specific theme ETF launches, the underlying stocks have often already peaked. Seoul Economic Daily reports that Kiwoom's solution uses keyword analysis powered by large language models to continuously identify AI and frontier tech companies drawing actual market attention.

Here's how the mechanics work. The ETF screens for companies related to artificial intelligence and frontier technologies—defined as next-generation innovations in early commercialization stages. It then selects the top 30 stocks with the highest beta values among them. Beta measures market sensitivity. A beta above 1 means the stock is more volatile than the benchmark. When the S&P 500's beta is set at 1, Tesla has a beta of about 2.3, meaning it reacts more strongly to market volatility. Stocks with higher beta surge in rising markets and plunge when the market retreats.

This high-beta strategy is designed to capture theme-driven surging stocks while maintaining the transparency of passive investing. Lee Kyung-jun, head of the ETF management division at Kiwoom Asset Management, explained the positioning. "This strategy is designed to address the inability of existing thematic ETFs to keep up with sharp rallies, while also offsetting the volatility of active ETFs." The fund pursues both the market responsiveness of active ETFs and the consistency of passive ETFs (a balance that sounds too good to be true, but the quarterly rebalancing helps).

Quarterly rebalancing occurs in March, June, September, and December. This allows the ETF to continuously identify new innovative technology companies and respond to shifting investment trends. The firm says this reduces the "theme extinction" risk that has been cited as a weakness of existing single-theme ETFs. Innovative technology themes change rapidly. It is more important to invest in line with changing flows rather than staying locked into a specific theme.

The current portfolio evenly incorporates innovative technology themes drawing concentrated market interest. Holdings include AI semiconductors, data centers, optical communications, and space technology. Representative names include Vertiv Holdings, a data center infrastructure company; SanDisk, a memory semiconductor maker; Lumentum Holdings, an optical communications equipment provider; and Bloom Energy, a fuel cell company. Individual stock weights are determined by a 50-50 split between market capitalization and beta value. Each stock's weight is capped at 10% to prevent excessive concentration.

The total expense ratio is set at 0.49%. This is described as a management fee level typical for theme ETFs. While higher than index-tracking ETFs, the fee is slightly lower than typical active ETFs. Chosun Biz corroborates the expense structure and notes the product is positioned as suitable for long-term investing, including retirement accounts.

The launch comes as active ETFs have taken hold as the mainstream in the asset management industry. Kiwoom's move stands in contrast to asset managers recently launching active ETFs one after another. Active ETFs may have the advantage of pinpointing rising stocks through precise analysis. However, there have always been concerns that managers have a low likelihood of continuously finding such stocks. This passive, rule-based approach attempts to solve that problem.

Investors clicking through the prospectus will find a 10% concentration cap and a buffer rule to prevent excessive turnover. The physical experience of holding this ETF differs from traditional thematic funds. Instead of watching a single theme stagnate as market attention shifts, the quarterly rebalancing means the portfolio composition refreshes automatically. No manual intervention required.

Whether this hybrid approach actually delivers superior risk-adjusted returns remains to be seen. High-beta stocks exhibit a "high-risk, high-return" profile. Diversification is essential. The algorithm may identify the right themes, but market timing still matters. Whether users actually pay for it remains the real question.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn