新聞資訊

January was defined by four key themes: regulatory uncertainty as the CLARITY Act stalled in the Senate, heightened geopolitical concerns between US, Europe, and Greenland, capital outflows into AI adjacent equity names (particularly in US, China, and Hong Kong) and commodities outperformance as the traditional safe haven attracted flows amid risk-off sentiment.

2025 marked a watershed year for digital assets, as both Bitcoin and Ethereum reached new all-time highs amid growing regulatory clarity in the United States and accelerating institutional adoption. The passage of the GENIUS Act, the first comprehensive federal stablecoin legislation, signaled a material shift in U.S. policy, while regulatory enforcement actions against many crypto-native firms moderated.

Agentic commerce, the buzzword of 2025 has become a leading narrative in 2025, promising to transform the way we engage and transact with online services through agents that represent us.

A Digital Asset Treasury (DAT) is a type of publicly listed company whose core strategy is to hold digital assets. In Part 1 of this series, we introduced DAT’s basic concept, operating model, and defining features. This second installment addresses two questions: From an operator’s perspective, how do you build a DAT? From an investor’s perspective, how do you select high-quality DAT companies?

October marked the start of the longest period of US government shutdown in history, with the shutdown continuing into November. Geopolitical tensions also flared up between US and China over rare earth controls, causing gold prices to rise to its highest level on October 17. On the policy front, the Fed has issued its second rate cut of the year and promised to end quantitative tightening in December, although its hawkish tone towards a definitive rate cut in December, kept market euphoria at bay. Market expectations for a rate cut in December has now fallen from 82% to ~67% as of the time of writing with 1/3 expecting rates to stay unchanged. These confluence of factors have led to a divergence in performance between equities and crypto markets.

September marked a significant month for markets as the Federal Reserve cut its rate by 25bps for the first time since December 2024, reaffirming the weakening labour market reports and economic uncertainty. Moving forward, based on Fed dot plot projections, it is likely that the market will see 2 more 25bps rate cuts in October and December this year.

Over the past five years, the Digital Asset Treasury (DAT) model has progressed from a niche experiment into a recognized capital market trend, embraced by firms ranging from MicroStrategy in the United States to Metaplanet in Japan, as well as dozens of other publicly listed companies worldwide. DAT companies have not only reshaped the balance sheet of their companies by incorporating digital assets such as Bitcoin and Ethereum but also provided investors with a way to differentiate themselves from their competitors. By incorporating digital assets such as Bitcoin and Ethereum into their balance sheets, DAT companies not only reshape their capital structure but also provide investors with an alternative investment opportunity that is different from ETFs and funds.

The crypto market briefly touched $4.19T capitalization in mid-August as Bitcoin crossed $124K and Ethereum nearly hit $5K. Despite retracement from profit-taking, markets remained resilient, supported by dovish Fed signals and pro-crypto policy appointments Ethereum outshines Bitcoin in August with ETH/BTC ratio at its highest level since August 2024, led by institutional adoption. Solana passed its Alpenglow consensus upgrade, promising faster finality (12s → 150ms) and lower validator costs.

In a world where foundational LLMs are becoming more powerful in terms of reasoning and tool use, the transition to an agentic economy is already underway where agents, powered by agentic frameworks, tool uses and LLMs are becoming an essential to businesses looking to automate and enhance operational efficiency. However, the sprawling number of agents and agentic frameworks make it hard for agents to verify, communicate and interact with one another.