Annual Revenue of Hundreds of Millions, Aggressive Buybacks: Why is Pump.fun Still Being 'Shorted' by the Market?

marsbit2026-03-19 tarihinde yayınlandı2026-03-19 tarihinde güncellendi

Özet

Despite circulating rumors, on-chain evidence and multiple independent data sources (DeFiLlama, Dune, and verifiable wallet transactions) confirm that Pump.fun's revenue and aggressive buyback program are legitimate. Over eight months, 99.5% of daily protocol revenue—totaling $328 million—was used to repurchase and burn 105.1 billion PUMP tokens, offsetting 29.52% of the circulating supply. Statistical analyses of the 747-day revenue data further validate its authenticity, showing expected patterns like weekend effects, autocorrelation, and structural breaks aligned with product updates. However, PUMP's valuation remains suppressed due to three key factors: its classification as a "sin stock" (98.6% of tokens launched on the platform are alleged scam "rug pulls"), trust issues (anonymous founders, discretionary buyback policy, and historical controversies), and insider selling pressure (notable wallets dumping tokens at market prices despite the buyback). While community token emissions will stop in July 2026—reducing monthly inflation from 10 billion to 9.2 billion tokens—current buybacks already absorb twice the new supply. The trust discount, rather than fundamentals, explains the undervaluation of a protocol generating $1.25 million in daily verifiable revenue.

Original Author: Four Pillars

Original Compilation: AididiaoJP, Foresight News

Key Points

Completed a $328 million buyback in eight months using 99.5% of daily protocol revenue. Two independent data aggregators, despite not being interconnected, reached the same conclusion. To manipulate the data, one would need to simultaneously deceive DeFiLlama, maintain a stable 68-69% ratio with Adam_tech's Dune data (which only indexes Solana), and have 105.17 billion PUMP tokens in verifiable wallets as support.

The "dilution curve" in August 2026 is actually a supply replacement rather than an addition. At current revenue levels, the buyback can absorb twice the new supply. Community emissions will cease when team and investor unlocks begin. Monthly emissions will drop from 10 billion tokens to 9.2 billion tokens.

The real reasons for the current suppressed valuation multiples are: industry classification (the nature of "original sin stocks"), trust foundation (anonymous team, discretionary buybacks), and capital flow (insiders allegedly using buybacks to sell).

1. Proof of the $328 Million Buyback

Rumors of Pump.fun's fabricated revenue have been circulating on Twitter. The following analysis shows these rumors are false.

As of March 15, 2026, data from fees.pump.fun shows a cumulative buyback amount of $328 million. This means 2,283,518 SOL was used to purchase 104.5 billion PUMP, accounting for 10.45% of the total supply and offsetting 29.52% of the circulating supply. Over eight months, the daily buyback amount remained between 99.5% and 100.5% of protocol revenue, averaging $1.25 million per day as of February 2026. Fabricating revenue would require massive capital support: for every dollar bought back, one dollar of SOL flows out from a verifiable wallet to purchase tokens stored in an auditable address. To fake $328 million in revenue, one would need to actually spend $328 million.

The relevant tokens are stored on-chain and can be verified (as of March 17, wallet G8CcfRff holds 103.96 billion PUMP, 8PSmqJy6 holds 1.21 billion PUMP, totaling 105.17 billion). The initial execution wallet 3vkpy5Y (marked as "Pump Buy Back" on Solscan) completed transfers to the holding wallets and was rotated in August 2025, now with a zero balance.

DeFiLlama recorded total protocol revenue from July 15, 2025, to February 21, 2026, as $300,041,880. During the same period, the cumulative buyback amount on fees.pump.fun was $300,178,162. The match is 100.05%, with only a $136,000 difference between two independent systems on a total of $300 million.

Adam_tech's Dune dashboard provides a third layer of verification. This platform only tracks Solana chain revenue, consistently representing 68-69% of DeFiLlama's multi-chain data, as it does not index Padre revenue launched on Base, Ethereum, and BNB Chain in October 2025. This ratio remains stable daily, indicating both are independently reading the same on-chain events.

Before the launch of PumpSwap in March 2025, the error margin between the three data sources was within 1-5%. After PumpSwap launched, the data differentiated into three layers: total fees, protocol revenue, and Solana-only revenue. If someone were to fabricate revenue data, they would need to simultaneously deceive two independent on-chain indexers, maintain stable cross-correlation ratios through three product changes, keep a multi-chain revenue split ratio consistent with actual business expansion, and support it with token purchases in verifiable wallets.

2. Four Statistical Tests

In addition to on-chain evidence, 747 days of fee data can be subjected to four standard tests to verify the authenticity of the financial data. While a single test is not conclusive, when four tests point to the same conclusion, credibility increases significantly.

The first test is the fee-to-revenue ratio, the hardest indicator to fake. Pump.fun collects fees from each bonding curve transaction, but not all count as protocol revenue; some go to LPs, creators, and referral rewards. In the dataset, the total fee to net revenue ratio dropped from 1.0 to about 0.48, but not gradually. It dropped sharply in three stages, each corresponding to a documented on-chain product change:

  • March 20, 2025: PumpSwap launched with an LP fee split mechanism, ratio dropped from 1.00 to 0.70 in two days.
  • May 13, 2025: Creator revenue sharing mechanism launched, ratio dropped from 0.69 to 0.56.
  • September 2-3, 2025: The Ascend project introduced a dynamic fee mechanism, layered pricing allowing creators to get up to 0.95% fees on low-market-cap tokens, with the protocol keeping only 0.05%, ratio dropped from 0.68 to 0.46.

Faking this data would require simulating fee and revenue series undergoing three structural adjustments simultaneously, with the daily ratio fluctuating between 0.40 and 0.55 based on token tier composition. This complexity makes fabrication difficult. The reality is that product iterations naturally caused the changes, not artificial construction aligning with contract deployment times.

The second test examines continuity and digit distribution, aiming to determine if the data shows signs of manual entry. Humans struggle to generate truly random sequences, tend to avoid long streaks, prefer integers, and have unconscious biases toward specific digits. Pump.fun data lacks these characteristics:

The longest consecutive rise or fall is 6 days, with an average streak length of 1.92 days, consistent with expectations for a natural process with moderate momentum. Streak length decreases geometrically: 185 one-day streaks, 111 two-day streaks, 52 three-day streaks, down to 7 six-day streaks.

The last digit of daily fees is nearly uniformly distributed between 0-9, with each digit accounting for 8.7%-11.2%. 88.8% of days do not end with an integer; only 7 out of 743 non-zero days end with 00 or 000.

The third test examines the weekend effect. Pump.fun is a retail platform; users issue tokens more on weekdays than weekends. Average daily fees are $2.14 million on weekdays and $1.81 million on weekends, a consistent ~18% drop, appearing week after week in the two-year data. A Mann-Whitney test shows a p-value of 0.003, statistically significant. If data were fabricated, one would need to deliberately keep weekends consistently lower, increasing the complexity and risk of detection.

The final test examines autocorrelation, measuring the relationship between today's revenue and tomorrow's. Pump.fun's first-order lag autocorrelation is 0.78, meaning today's fees are 78% correlated with yesterday's; it remains 0.65 after one week (lag 7 days); and 0.57 after two weeks (lag 14 days). This slow, smooth decay reflects the momentum characteristic of organic platform activity: active periods cluster, and downturns persist. If daily revenue were generated randomly, correlation between adjacent days would be near zero, and the data would jump like noise rather than flow like a market. Faking high autocorrelation for a single lag is not difficult, but faking the entire decay structure (monotonically decreasing step by step for each lag), while maintaining the weekend effect, streak characteristics, and realistic digit distribution, is nearly impossible.

Four independent tests, four consistent conclusions, three data sources corroborating each other. The revenue data is authentic and reliable.

3. Analysis of Remaining Valuation Discount Factors

Rumors of fabricated revenue are one reason for PUMP's current suppressed valuation. The previous analysis has clarified this. But the token still trades at a discount; other suppressing factors and their validity need exploration.

First, analyze the August team unlock. Community emissions are 10 billion tokens monthly, will reach 240 billion tokens by July and then stop, coinciding with the start of team and investor unlocks, totaling 9.2 billion tokens monthly. Monthly emissions will drop from 10 billion to 9.2 billion tokens, an 8% decrease in inflation rate. At the current average daily revenue of $1.25 million, the monthly average buyback is $38 million. At a price of $0.0021 per token, this can absorb about twice the $19 million worth of new monthly supply. After August, emissions decrease while buybacks continue, further improving this ratio.

Revenue shows no sign of decline either. Over fourteen months, monthly average fees fluctuated between $2.3 million and $4.8 million daily: down 49% in July 2025, rebounded 94% in August, surged 72% in September, and jumped 45% in January 2026. Overall, it mean-reverts around a daily average of $2.5-3 million, with weekly trading volume stable at $640-700 million. The so-called "Q3 to Q1 decline" is a one-sided conclusion drawn by selectively picking September peak data.

The remaining suppressing factors are as follows:

The "original sin stock" discount is the most persistent. Solidus Labs found that 98.6% of tokens on the platform have "rug pull" characteristics. This finding had the intended effect: regardless of revenue, institutional allocators will not include a "meme coin casino" in their portfolios. This is a persistent structural factor, completely unrelated to revenue quality.

Source: Solidus Labs

Alleged insider selling constitutes tangible recent pressure. Wallet 77DsB received 3.75 billion PUMP in July 2025 from an address marked "Token Custody Wallet" on Solscan, allegedly liquidated its position for 8.02 million USDC between February 16 and 22, 2026. Wallet GpCfm transferred 1.21 billion PUMP ($2.57 million) to Bitget during the same period. A third wallet deposited 1.757 billion PUMP ($3.54 million) into Bitget on March 6. Although no source confirms actual ownership, at least $14 million flowed to exchanges at a market price of $0.002 within thirty days while the protocol was buying back, compared to a private round price of $0.004. This situation raises questions, regardless of the wallet owners' identities.

The trust aspect is the hardest to price. The founders are anonymous (co-founder Dylan has a "rug pull" record from 2017); buybacks are explicitly "discretionary" ("pump.fun may modify or中止 the plan at any time"); Bubblemaps once alleged Hayden Davis was associated with a $50 million private placement, but later deleted the claim after co-founder Alon called it "defamation." On-chain associations exist, but attribution is disputed and unverified.

None of these factors relate to business fundamentals. The revenue is real, supported by data, and the unlock arrangement is favorable to holders. The "original sin stock" label, anonymous founders, and insider fund flows are all trust discounts applied to a protocol with $1.25 million in daily verifiable on-chain revenue, whose buybacks can absorb twice the new supply. The trust discount will eventually narrow; revenue of this scale will not be mispriced forever.

İlgili Sorular

QWhat evidence supports the claim that Pump.fun's $328 million in buybacks and revenue are real and not fabricated?

AMultiple independent data sources (DeFiLlama, fees.pump.fun, and Adam_tech's Dune dashboard) align, showing a 100.05% match on $300 million in total revenue and buybacks. The buybacks are verifiable on-chain, with 105.17 billion PUMP tokens held in public wallets. The data also passes statistical tests for authenticity, including fee-to-revenue ratio changes corresponding to product updates, natural number distribution, a consistent weekend effect, and realistic autocorrelation patterns, making a coordinated fraud across all these metrics highly improbable.

QHow does the upcoming 'dilution curve' in August 2026 affect PUMP token supply and inflation?

AThe community emissions of 10 billion tokens per month will cease upon the start of team and investor token unlocks in August 2026. The new combined monthly issuance from unlocks will be 9.2 billion tokens. This represents an 8% reduction in the monthly inflation rate, from 10 billion to 9.2 billion tokens. Furthermore, at current revenue levels, the protocol's buybacks are sufficient to absorb twice the amount of new supply being created.

QWhat are the key factors cited as the real reasons for PUMP's discounted valuation, despite its high revenue?

AThe three main factors suppressing PUMP valuation are: 1. The 'sin stock' discount, as the platform is associated with meme coins and rug pulls, deterring institutional investment. 2. Trust issues stemming from an anonymous founding team, a discretionary buyback policy that can be changed, and past controversies. 3. Insider selling pressure, with significant amounts of tokens from early wallets being sold on exchanges concurrently with the protocol's buyback program.

QWhat statistical tests were performed on the revenue data, and what did they conclude?

AFour statistical tests were performed: 1. Fee-to-Revenue Ratio Test: Showed structural breaks that perfectly matched three specific product updates, a pattern too complex to fake. 2. Continuity and Digit Distribution Test: Found natural sequences and a near-uniform distribution of ending digits, lacking human manipulation patterns. 3. Weekend Effect Test: Confirmed a statistically significant 18% drop in revenue on weekends, consistent with user behavior. 4. Autocorrelation Test: Revealed a high and smoothly decaying correlation between daily revenues, indicating organic market momentum. All tests concluded the data is authentic.

QHow does the protocol's current buyback capacity compare to the new token supply being emitted?

AAt the daily revenue rate of $1.25 million, the protocol generates approximately $38 million monthly for buybacks. At the current price of $0.0021 per PUMP, this allows it to buy back roughly 18 billion tokens per month. This buyback power is double the current monthly community emission of 9.2 billion tokens, meaning the buyback absorbs twice the new supply being created. This ratio is expected to improve further after August 2026 when emissions decrease.

İlgili Okumalar

The Essence of AI Layoffs: Why More AI Adoption Leads to More Corporate Anxiety?

The author, awaiting potential inclusion on an 8000-person layoff list, analyzes the true nature of recent "AI-driven" layoffs. They argue that while AI use, particularly tools like Claude for code generation, has skyrocketed and boosted developer output (e.g., 2-5x more code commits), this has not translated into proportional business growth or revenue. The core issue is a misalignment between increased "Input" (code) and tangible "Outcomes" (user value, revenue). AI acts as a costly B2B SaaS, inflating operational expenses without guaranteed returns. Two key problems emerge: 1) The friction that once filtered out bad ideas is gone, as AI allows cheap pursuit of even weak concepts. 2) Organizational "alignment tax"—the difficulty of coordinating across teams—becomes crippling when development velocity outpaces consensus-building. Thus, layoffs serve two immediate purposes: 1) To offset ballooning AI costs (Token consumption) and maintain cash flow, as rising input costs without outcome growth destroys unit economics. 2) To reduce organizational bloat and alignment friction by simply removing teams, thereby speeding up execution in the short term. Therefore, these layoffs are fundamentally caused by AI, even if AI doesn't directly replace roles. They represent a painful correction until companies learn to convert AI-driven productivity into real business outcomes and streamline organizational coordination to match the new pace of work. The cycle will continue until this learning curve is mastered.

marsbit4 dk önce

The Essence of AI Layoffs: Why More AI Adoption Leads to More Corporate Anxiety?

marsbit4 dk önce

Can the Solana Foundation and Google's Collaboration on Pay.sh Bridge the Payment Link Between Web2 and Web3 in the Agent Economy?

Solana Foundation, in collaboration with Google Cloud, has launched Pay.sh, a payment gateway designed to bridge the gap between AI agents and enterprise-grade service infrastructure. The initiative aims to solve a key bottleneck in the "agent economy": existing payment systems are ill-suited for autonomous AI agents. Traditional methods like credit cards require human verification, while newer on-chain protocols like x402 and MPP create a separate, Web3-native system that raises barriers for service providers. Pay.sh functions as a universal payment layer. It allows users to fund a Solana wallet via credit card or stablecoin, which then acts as an identity and payment proxy for AI agents. When an agent needs to access a paid API service (e.g., Google Cloud, Alibaba Cloud), Pay.sh handles the transaction seamlessly. It leverages the HTTP 402 status code ("Payment Required") to initiate payments, intelligently choosing between one-time transfers (x402-style) or session-based authorizations (MPC-style) based on the service's billing model. This spares agents from manual account registration and API key management. A key feature for service providers is low integration effort. They can adopt Pay.sh by providing a declarative configuration file, enabling features like tiered pricing, free tiers, and automatic revenue splitting to multiple addresses (e.g., for royalties, cloud costs). Providers can also list their APIs in a central Pay Skill Registry for agent discovery. The collaboration with Google Cloud provides crucial infrastructure for API proxying, traffic routing, and compliance logging, aiming to keep agent activities within regulated boundaries. By connecting Web2 services with Web3 payment rails, Pay.sh positions the Solana wallet as a foundational identity and payment tool for AI agents, potentially driving more transaction volume to the Solana ecosystem. However, the report notes challenges. The service registry currently lacks robust vetting, risking exposure to unauthorized or malicious third-party APIs. Pay.sh also inherits security and compatibility risks from its underlying payment protocols (x402, MPC). Furthermore, adoption may be hindered by varying regional data privacy and payment compliance regulations among API providers. Despite these hurdles, Pay.sh represents a significant step towards integrating Web2 and Web3 for autonomous agent commerce.

marsbit11 dk önce

Can the Solana Foundation and Google's Collaboration on Pay.sh Bridge the Payment Link Between Web2 and Web3 in the Agent Economy?

marsbit11 dk önce

Bitcoin's Bull-Bear Cycle Indicator Turns Positive for the First Time in 7 Months: End of Bear Market or False Breakout?

Bitcoin's "Bull-Bear Market Cycle Indicator" from CryptoQuant has turned positive for the first time since October 2025. This gauge, based on the P&L Index relative to its 365-day moving average, suggests a potential shift from a bear market phase. Concurrently, the Bull Score Index rose to a neutral reading of 50 in late April. The indicator's move into positive territory follows a roughly 35% price rebound from a low near $60,000 in February to above $81,000. The recovery over approximately three months was faster than the 12-month period observed during the 2022 bear market. However, analysts caution against premature optimism, citing a historical precedent from March 2022. Back then, the Bull Score Index briefly hit 50, but it proved to be a false signal as Bitcoin's price subsequently plunged further. Structural differences exist in the current cycle, including consistent inflows into spot Bitcoin ETFs and an increase in large holder addresses. Yet, some models, referencing the four-year halving cycle, suggest a potential deeper bottom near $50,000 might still be possible around late 2026. In summary, while on-chain data shows marked improvement and the worst panic may be over, market participants remain cautious. A convincing trend reversal confirmation likely requires Bitcoin to sustainably break above key resistance, such as the 200-day moving average near $82,000.

marsbit18 dk önce

Bitcoin's Bull-Bear Cycle Indicator Turns Positive for the First Time in 7 Months: End of Bear Market or False Breakout?

marsbit18 dk önce

How to Automate Any Workflow with Claude Skills (Complete Tutorial)

This is a comprehensive guide to mastering Claude Skills, a feature for creating permanent, reusable instruction sets that automate specific workflows. Unlike simple saved prompts, Skills function like trained employees, delivering consistent, high-quality outputs by defining the entire task process, standards, error handling, and output format. The guide is structured in four phases: **Phase 1: Installation (5 minutes).** Skills are folders containing a `SKILL.md` file. The user is instructed to find a relevant Skill online, install it, test it on a real task, and compare its performance to one-off prompts. **Phase 2: Building Your First Custom Skill.** Start by rigorously defining the Skill's purpose, trigger phrases, and providing a concrete example of perfect output. The `SKILL.md` file has two parts: a YAML frontmatter with a specific name/description/triggers, and a detailed, step-by-step workflow written in natural language with examples and quality standards. **Phase 3: Testing & Optimization for Production.** Test the Skill in three scenarios: 1) a standard, common task; 2) edge cases with missing or conflicting data; and 3) a pressure test with maximum complexity. Any failure indicates a needed instruction. Implement a weekly optimization cycle to continuously refine the Skill based on real usage. **Phase 4: Building a Complete Skill Library.** The goal is to create a team of Skills for all repetitive tasks. Examples are given for industries like real estate, marketing, finance, consulting, and e-commerce. The user should list their tasks, prioritize them, and build one new Skill per week, maintaining a master document to track their library. The conclusion emphasizes the compounding time savings: ten Skills saving 30 minutes each per week reclaims over 260 hours (6.5 work weeks) per year, fundamentally transforming one's work system.

marsbit42 dk önce

How to Automate Any Workflow with Claude Skills (Complete Tutorial)

marsbit42 dk önce

İşlemler

Spot
Futures
活动图片