Stock Analysis by Vikram Singh

About Stock Analysis by Vikram Singh

Stock Analysis by Vikram Singh, operating under the handle @thevikramsinghh on YouTube, is a US-based creator focused on the finance category. The channel provides daily US stock analysis, pre-market levels, and insights into market psychology. With a stated goal of helping traders develop their analytical skills rather than relying on direct trading signals, the content emphasizes understanding market dynamics as a precursor to financial success. The channel has published a substantial volume of content, with 8,653 videos to date, accumulating 460,430 total views. As of the latest data, Stock Analysis by Vikram Singh has 22,500 subscribers. A disclaimer is consistently included, noting that any shared investments or trades are for educational purposes only and do not constitute financial, trading, or investment advice, underscoring a commitment to responsible content creation within the sensitive finance niche. The channel's content strategy appears to prioritize consistent, in-depth analysis over broader market commentary, catering to an audience interested in detailed trading perspectives.

Stock Analysis by Vikram Singh's estimated sponsorship rates

The estimated rate for an integrated video on Stock Analysis by Vikram Singh's YouTube channel ranges from $160 to $267, with a typical rate around $196. This pricing falls within the nano audience tier, reflecting the channel's current subscriber count. The finance niche generally commands a higher CPM (cost per mille) compared to many other content categories, with an anchor CPM of $55 in a band of $45-75. This elevated CPM is a significant factor in the channel's estimated rate, as finance content often attracts advertisers seeking to reach an engaged audience with disposable income or an interest in financial products and services. The algorithmic estimate for this creator is based on an average of 3,555 views, which is a fallback calculation derived from subscriber count due to the absence of recent average view data. This reliance on a subscriber-based view estimate indicates a low confidence level in the current pricing model, suggesting that actual performance metrics could lead to adjustments. Factors that could influence future rate adjustments include sustained audience engagement, specific content formats that drive higher interaction, and the development of more granular view-count history. For a detailed breakdown of how these rates are calculated, refer to the /methodology page.

Who should partner with Stock Analysis by Vikram Singh?

Stock Analysis by Vikram Singh primarily serves an audience interested in daily US stock analysis, pre-market levels, and market psychology within the finance sector. The content is geared towards individuals seeking to enhance their understanding of market dynamics and trading execution, rather than those looking for direct trading signals. This focus suggests an audience composed of active traders, aspiring investors, and individuals engaged in personal finance management who are looking for analytical insights. Brands in categories such as fintech apps, online brokerages, investment education platforms, and financial news services would find this audience particularly relevant. Given the channel's emphasis on educational content and responsible trading, the audience is likely to value data-driven analysis and expert commentary. Peer channels in the finance niche, such as Markets Etrading Latam and 黃德几 Dickie Finance事Up, also cater to similar segments, indicating a competitive landscape for attracting and retaining financially-minded viewers. The audience's engagement with detailed market analysis suggests a demographic that is generally well-informed and actively seeking to improve their financial literacy and trading strategies. The channel's disclaimer regarding educational content also helps to filter for an audience that understands the inherent risks and responsibilities associated with financial markets.

Stock Analysis by Vikram Singh's growth and performance

Stock Analysis by Vikram Singh's subscriber growth data currently spans a very short period. The channel was first tracked on 2026-05-30 with 22,500 subscribers. The latest snapshot, also taken on 2026-05-30, shows the same subscriber count of 22,500. This provides a one-day span with a delta of zero subscribers, meaning no growth or decline was recorded within this initial tracking period. We do not yet have historical data for average views over the last 30 days, which would provide more insight into recent content performance and audience engagement trends. Future tracking will provide a more comprehensive view of subscriber accumulation and content reach. The current data reflects a stable subscriber base at the point of initial tracking, but does not offer a trajectory for growth or decline over time.

How our pricing estimate works for Stock Analysis by Vikram Singh

The estimated pricing for Stock Analysis by Vikram Singh's integrated YouTube videos is generated through an algorithmic model. This model calculates a rate based on several key factors, including the creator's subscriber count, the typical CPM (Cost Per Mille) for their specific content niche, and platform-specific multipliers for different content formats. For this creator, the finance niche commands a higher CPM, which influences the overall rate. The current estimate utilizes a subscriber-fallback view count of 3,555, as detailed historical view data is not yet available. This means the confidence level in the current view-based component of the estimate is low. The algorithm then applies various adjustments to arrive at a range (low, typical, high) that reflects market dynamics and creator specifics. It is important to note that these figures are algorithmic estimates and do not represent a fixed rate card or a direct negotiation. For a comprehensive explanation of the data points, formulas, and assumptions used in our creator rate estimations, please refer to the detailed methodology page available at /methodology. This page provides transparency into how each component contributes to the final estimated pricing.