방구석 헤지펀드
@algo-assets-hedge-fund
미국에서 데이터 사이언티스트로 일하며, 여유 시간에 방구석에서 알고리즘 트레이딩 전략을 만들고 내 돈을 태워서실험하는 취미를 공유하는 채널입니다. 채널에 나오는 모든 데이터는 직접 받아서 파이썬으로 백테스트, 시뮬레이션, 전략 분석하고 있습니다. - 월-금: 실전투자일지 (최적의 매수/매도 시그널 공유, 시장 방향성 - 주식노출도 5단계 시스템, 주요 자산군 - 원자재, 채권, 비트코인, 빅테크, 리더 섹터/주식 분석) - 그외: 기업분석, 전략탐구,...
12.8K
Subscribers
1.22M
Total views
366
Videos
—
Avg views (recent)
not yet captured
Estimated rate · Integrated video
Subs-based fallback · Low confidenceLow
$91
Typical
$111
High
$152
- Niche CPM
- $45–75anchor $55
- Avg views
- 2,022tier-based estimate
- Format mult
- 1.00×
- Exclusivity
- No exclusivitybaseline
Estimated · benchmark only · not claimed by creator. View count not yet captured — tier-based fallback (low confidence). How this works →
Influence profile
Display only · not a price input- Size tier
- Nano (10K–50K)
- Activity
- Activity unknownavg views not yet captured
- Niche
- Finance
- Country · language
- United States
- US equities coverage
- Not flagged
- SEC §17(b) disclosure
- Not assessed
About 방구석 헤지펀드
방구석 헤지펀드 operates a YouTube channel focused on algorithmic trading strategies and personal finance, primarily targeting an audience interested in data science applications within the financial markets. The creator, identified as a data scientist based in the United States, shares insights derived from their personal experiments in algorithmic trading. Content frequently involves backtesting, simulations, and strategy analysis using Python, with all data directly sourced and processed by the creator. The channel's programming includes a Monday-to-Friday series detailing real-world investment logs, covering optimal buy/sell signals, market direction indicators (a 5-stage stock exposure system), and analysis of key asset classes such as commodities, bonds, Bitcoin, big tech, and leading sectors/stocks. Additional content explores corporate analysis and in-depth strategy discussions. With 366 videos published to date, the channel has accumulated 1,221,447 total views, attracting a subscriber base of 12,800. The primary content category is finance, with a secondary focus on technology, reflecting the creator's emphasis on data-driven approaches to investment.
방구석 헤지펀드's estimated sponsorship rates
The estimated rate for an integrated video on 방구석 헤지펀드's YouTube channel ranges from $91 to $152, with a typical rate projected at $111. This pricing falls within the nano audience tier, which generally encompasses creators with subscriber counts similar to the current 12,800. The creator's niche in finance and technology, specifically algorithmic trading and data science in investing, commands a higher CPM band, estimated between $45 and $75, with an anchor CPM of $55. This niche CPM is a significant factor in the rate calculation, as financial content often attracts advertisers seeking highly engaged and affluent audiences interested in investment products, fintech applications, and financial education. The estimated views used for this calculation are 2,022, based on a subscriber fallback model due to the absence of recent average view data, which introduces a low confidence level to the view basis. Factors such as the creator's specialized content, which appeals to a specific demographic interested in quantitative finance, contribute to the rate. For a detailed breakdown of how these rates are determined, including the specific algorithmic formula and multipliers applied for platform and format, please refer to our /methodology page.
Who should partner with 방구석 헤지펀드?
방구석 헤지펀드's audience consists primarily of individuals interested in finance and technology, with a specific focus on algorithmic trading, data science, and personal investment strategies. Given the creator's background as a data scientist and the channel's emphasis on Python-based analysis, the viewership likely includes aspiring quantitative analysts, retail investors seeking data-driven insights, and individuals interested in the intersection of technology and financial markets. Brand categories that would find this audience particularly valuable include fintech apps, online brokerages, personal-finance education platforms, data analytics tools, and software providers for quantitative trading. The channel's content on asset classes like commodities, bonds, Bitcoin, and big tech also suggests an audience with diverse investment interests. In terms of audience size, 방구석 헤지펀드, with 12,800 subscribers, is comparable to other creators in the finance niche such as Vanessa Stocks (@vanessastocks) and Aria Radnia (@qualityinvest5), both also at 12,800 subscribers. This indicates a consistent engagement level within this specific segment of the financial content landscape, appealing to a demographic that values detailed, analytical approaches to market understanding and investment.
방구석 헤지펀드's growth and performance
방구석 헤지펀드's subscriber growth data currently provides a limited historical view. The channel was first tracked on 2026-05-26, at which point it had 12,800 subscribers. The latest snapshot, taken on the same date, shows the subscriber count remaining at 12,800. This indicates a tracking span of one day with no recorded change in subscriber count during this initial period. We do not yet have historical data to analyze long-term subscriber trends, view-count history, or average views over the last 30 days. Future tracking will provide more comprehensive data points to assess the channel's growth trajectory and audience engagement patterns over time. As more snapshots become available, we will be able to provide a more detailed analysis of subscriber accumulation and content performance.
How our pricing estimate works for 방구석 헤지펀드
The estimated creator rates for 방구석 헤지펀드 are generated through an algorithmic model that considers several key factors. This model primarily bases its calculations on the creator's subscriber count, which is 12,800 in this instance. This subscriber figure is then multiplied by a niche-specific CPM (Cost Per Mille) band, which for the finance category is estimated between $45 and $75, with an anchor CPM of $55. Further adjustments are applied through platform and format multipliers, which account for the specific characteristics of YouTube video content. The current estimate utilizes 2,022 views as a basis, derived from a subscriber fallback method due to the unavailability of recent average view data, leading to a low confidence level in this specific view count. This algorithmic approach aims to provide a data-driven projection of potential earnings for integrated video content. For a comprehensive explanation of the specific formulas, data inputs, and multipliers used in our rate estimation process, please visit our detailed /methodology page.