Roundhill Memory ETF

TradingKey - On October 8, Asia-Pacific time, Samsung Electronics announced its preliminary results for the third quarter of 2026: consolidated revenue stood at approximately 195 trillion Korean won (about $145.7 billion), up 13.7% quarter-on-quarter and 126.6% year-on-year; operating profit reached approximately 107.4 trillion Korean won, up 20% quarter-on-quarter and 782.5% year-on-year. Both revenue and operating profit hit record quarterly highs.

TradingKey - On June 25, 2026, 14 individuals and three companies filed an antitrust lawsuit in the U.S. District Court for the Northern District of California. Pursuant to Section 1 of the Sherman Act, the plaintiffs accuse Samsung Electronics, SK Hynix, and Micron of coordinating to restrict the supply of legacy DRAM since 2022, while seeking class-action certification, injunctive relief, and treble damages.

TradingKey - During the Asian trading session on September 7, SK Hynix shares closed up 8.26% at 1.783 million won. Meanwhile, the company's progress in advanced DRAM process transitions has also attracted market attention.

TradingKey - On September 1, Asia-Pacific time, the South Korean government unveiled its 2027 budget proposal, with total expenditure reaching 820.9 trillion won (approximately $597 billion), up 12.8% year-on-year. This marks a record high for South Korea's annual budget growth, surpassing the 10.6% recorded during the 2009 global financial crisis.

TradingKey - On August 27 Asia-Pacific time, Kioxia Holdings and SanDisk (SNDK) jointly announced plans to invest over 5 trillion yen (equivalent to $31 billion) in Japan over a six-year period to expand memory chip production capacity. The funds will be allocated toward infrastructure construction and related technology upgrades at the Yokkaichi and Kitakami plants to meet rising memory demand driven by growth in AI and data-centric businesses.

TradingKey - The expansion of AI computing power is driving up data center storage demand. Although HDDs receive less attention in AI storage discussions than high-performance storage media like HBM and NAND flash, they handle the long-term storage of AI training data, inference logs, and model versions.