Sky同學

About Sky同學

Sky同學 (@skyclassmate) is a Hong Kong-based YouTube creator focused on finance, technology, and cryptocurrency. The channel, launched by an individual with a background in family offices, venture capital, international consulting, and startups, provides content on practical AI technology skills, stock market investing, and crypto assets. With 182 videos published to date, Sky同學 has accumulated 610,764 total views. The creator identifies as an enthusiast and angel investor in AI, cryptocurrencies, and stock investments, with a stated goal of guiding viewers toward financial independence through these domains. Key investment holdings mentioned include QQQ, GOOGLE, and TESLA. The channel's content is presented in an unknown primary language, catering to an audience interested in the intersection of advanced technology and personal finance strategies.

Sky同學's estimated sponsorship rates

The estimated rate for a sponsored video integration on Sky同學's YouTube channel ranges from $74 to $184. The typical estimated rate is $123. This pricing places Sky同學 in the 'low' audience tier, reflecting the current subscriber count of 11,700. The creator's niche in finance, specifically covering AI, cryptocurrency, and stock investments, influences the potential CPM (cost per mille) for brand partnerships. Categories such as fintech apps, online brokerages, and personal finance education platforms often exhibit higher CPMs due to the direct monetization potential of their target audience. The Hong Kong geographic focus may also play a role in rate calibration, as regional market dynamics and advertiser demand can vary. The rate estimate is algorithmically derived, considering subscriber count, niche-specific CPMs, and platform/format multipliers. For a detailed breakdown of the pricing model, refer to the /methodology page.

Who should partner with Sky同學?

Sky同學's audience, currently at 11,700 subscribers, is primarily interested in finance, technology, and cryptocurrency. This demographic typically engages with content related to investment strategies, market analysis, and the application of AI in financial contexts. Specific brand categories that align well with this audience include fintech apps, online brokerages, personal-finance education platforms, and technology companies developing AI tools or blockchain solutions. The content's focus on stock market giants like QQQ, Google, and Tesla, alongside broader crypto discussions, indicates an audience seeking actionable insights and long-term investment perspectives. Peer creators in the finance niche, such as 投资实战 (@arvineasternx) and 두배당 (@double-dividend), share a similar subscriber base and content focus, suggesting a consistent audience profile across these channels. The engagement with practical AI skills also points to a segment interested in leveraging technology for financial advantage.

Sky同學's growth and performance

Sky同學's subscriber growth data is currently limited to a single snapshot. The channel was first tracked on 2026-05-18 with 11,700 subscribers. The latest snapshot, also on 2026-05-18, shows the same subscriber count. This provides a span of 1 day with a delta of +0 subscribers. We do not yet have historical data to analyze long-term subscriber trends or significant growth periods. Information regarding average views over the last 30 days is also not available at this time. As more data becomes available, this section will provide a more comprehensive analysis of the channel's growth trajectory and audience acquisition patterns.

How our pricing estimate works for Sky同學

The algorithmic price estimate for Sky同學's sponsored content is generated through a proprietary model that considers several key factors. This calculation begins with the creator's subscriber count, which is then weighted by a niche-specific CPM (cost per mille) relevant to the finance, tech, and crypto categories. Further adjustments are applied through platform and format multipliers, accounting for the specific engagement dynamics of YouTube video integrations. The estimate is currently based on a metric-driven approach, with 0 community data points contributing to its calibration. This means the model relies solely on its internal parameters rather than observed market rates from similar creators. For a comprehensive explanation of the variables, data sources, and computational steps involved in generating these estimates, please visit our detailed methodology page at /methodology.