wendy

Trove Markets wasn’t just another failed crypto project—it appears to have been a carefully executed scam, with retail investors bearing the losses.
Presale Built on Hype, Not Fundamentals
Trove positioned itself as a Perp DEX for Asia-Pacific traders and raised about $11.5M in its presale, implying a $20M valuation—without any VC backing, proven product, or on-chain traction. Retail investors bought in based on marketing narratives rather than substance.
TGE Collapse Reveals the Risks
During the Token Generation Event, $TROVE underwent a 10x supply increase, dropping its implied market cap to around $11M, and then briefly to $1M. Most sellers at this stage were insiders, leaving retail investors as exit liquidity.
Phase 1: Hyperliquid Pivot
Trove promised a Hyperliquid integration and claimed to raise $20M to buy HYPE tokens. Shortly after the ICO, they pivoted to Solana, citing missing liquidity. On-chain data, however, shows 194K HYPE tokens ($10–13M) sold within 24 hours. The pivot conveniently left investors stranded while insiders profited.
Phase 2: Paid Promotion and Influencer Silence
Several influencers promoted $TROVE during the presale, allegedly without proper disclosure. One reportedly received 8,000 USDC. Red flags were ignored, engagement with community questions was minimal, and some promotions may have violated local advertising laws.
Phase 3: Polymarket Manipulation
The team reportedly used presale fundraising numbers to manipulate betting outcomes on Polymarket, causing some traders to lose up to $73,000. The pattern was clear: anyone interacting with Trove could be exploited.
A Project That Extracted Value at Every Layer
Trove Markets profited from presale participants, traders, and early supporters—resembling a pyramid-style extraction where even early participants are expendable.
Key Lessons for Crypto Investors
Early red flags are warning signs—cutting losses is discipline, not weakness.
Projects with no product, users, revenue, or reputable backers that rush token sales are likely extractive.
Geographic origin doesn’t guarantee legitimacy, but high-risk regions demand extra scrutiny.
Verify claims through on-chain analysis and independent sources—never rely solely on marketing narratives.
Bottom line: Trove Markets is a stark reminder that trust in crypto is expensive and can be abused quickly $ETH
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#wendy #Write2Earn #ETH

This is not just another failed crypto launch. What happened with Trove Markets looks like a carefully optimized scam, executed step by step, with retail investors paying the price.
A Presale Built on Hype, Not Substance
Trove Markets positioned itself as a Perp DEX targeting retail traders across Asia–Pacific. During its presale, the project raised roughly 11.5 million USD from retail participants, implying a fully diluted valuation of around 20 million USD. Notably, there were no venture capital firms backing the project, no proven product, and no meaningful on-chain traction.
Despite these red flags, the presale was aggressively marketed, and many retail investors bought in, trusting the narrative rather than the fundamentals.
The TGE Collapse That Said Everything
At the Token Generation Event, $TROVE underwent a massive supply split, roughly a 10x increase. As a result, the token began trading at an implied valuation closer to 11 million USD. Within minutes, it collapsed further, briefly touching around 1 million USD in market cap.
At those levels, the only realistic sellers were insiders. Retail investors were effectively exit liquidity.
Scam Phase One: The Hyperliquid Pivot
Before the presale, Trove announced plans to integrate permissionlessly with Hyperliquid via HIP-3. To do this, they claimed to have raised around 20 million USD to acquire 500,000 HYPE tokens, a key requirement for the integration.
Shortly after the ICO, Trove abruptly announced a pivot away from Hyperliquid to Solana. The official explanation was that a liquidity partner had withdrawn the required HYPE tokens, making the integration impossible.
On-chain data told a very different story. Wallets linked to the project sold approximately 194,273 HYPE tokens, worth an estimated 10 to 12.9 million USD, within a 24-hour window. The selling started small and then accelerated. The founder denied controlling the wallet, but no credible explanation or refund followed.
In short, Hyperliquid was used as a hype engine to raise funds. The HYPE tokens were sold, and the project pivoted, leaving investors stranded.
Scam Phase Two: Paid Shilling and Influencer Silence
During the presale, several large KOLs promoted $TROVE without proper disclosure. One of the most controversial cases involved allegations that a well-known influencer received 8,000 USDC to promote the Trove ICO.
The accusations went beyond payment alone. There were already visible red flags around Trove before the presale, yet these were ignored. Promotional posts were published, but meaningful engagement or answers to community questions were noticeably absent. More concerning, some of this promotion allegedly occurred from jurisdictions where undisclosed paid advertising is not legally permitted.
Retail investors were led to believe they were seeing genuine opinions. In reality, much of the narrative was sponsored.
Scam Phase Three: Manipulating Polymarket
The Trove team did not stop at presale investors. They allegedly used presale fundraising figures to manipulate outcomes on Polymarket, exploiting market perception to influence betting results. This manipulation reportedly caused losses of up to 73,000 USD for some traders.
At this point, the pattern was clear. Anyone interacting with the Trove ecosystem became a potential target, whether they were investors, traders, or early supporters.
A Project That Extracted Value From Everyone
Trove Markets appears to have extracted value at every possible layer. Presale participants were diluted and dumped on. Prediction market users were manipulated. Early supporters who helped amplify the project narrative were discarded without hesitation.
It closely resembles a pyramid-style extraction model, where even early participants are sacrificed if doing so maximizes returns for those at the top.
Lessons the Crypto Market Cannot Ignore
Trove Markets should be treated as a case study, not an exception. When a project shows early red flags, the safest move is often to step aside, even if that means missing a potential upside. Cutting losses early is not weakness; it is discipline.
Trend-chasing projects with no product, no users, no revenue, and no reputable backers that rush to sell tokens are almost always designed for extraction rather than long-term value creation.
Geographic origin alone does not define legitimacy, but regions with historically high rates of developer scams demand extra scrutiny. Background checks, on-chain analysis, and independent verification are non-negotiable.
Most importantly, never rely on a single narrative on X. Look for dissenting opinions, follow on-chain data, and question anything that looks too clean, too fast, or too aggressively marketed.
In crypto, trust is expensive. Trove Markets is a reminder of how quickly it can be abused.
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The global economy is a whirlwind of simultaneous decisions made by individuals, corporations, and governments. To decode the resulting chaos of inflation, growth, and employment, economists utilize economic models. These frameworks act as a lens, sharpening our focus on specific forces to understand how a change in one area ripples through the rest of the system.
What is an Economic Model?
At its simplest, an economic model is a simplified map of reality. Rather than capturing every minute detail, it highlights the vital connections between core variables like income, price, and labor.
The primary goals of these models are to:
​Explain: Trace the cause-and-effect relationships between variables.
​Forecast: Predict future trends based on current data.Evaluate: Test the potential impact of government policies or business strategies before they are launched.The Anatomy of a Model
Every robust economic model is built upon four foundational pillars
Variables: The moving parts, such as interest rates or quantities sold. Parameters: Fixed values that represent "sensitivity." For instance, how much does consumer spending drop when taxes rise by 1%?Equations: The mathematical "glue" that links variables and parameters.
\pi = \pi^e - \beta (u - u_n)
This formula demonstrates how actual inflation (\pi) relates to inflation expectations, unemployment rates, and market sensitivity (\beta).
Assumptions: Necessary simplifications, such as ceteris paribus (holding all other factors constant) or the assumption of rational decision-making.
From Theory to Practice: The Apple Market
Consider the market for apples. A model allows us to plot a Demand Curve (buyers want more when prices are low) against a Supply Curve (sellers provide more when prices are high).
Where these two meet is the Equilibrium. If the price is too high, we see a surplus; if it's too low, a shortage. This simple model provides a blueprint for understanding resource allocation in almost any industry.
The Diverse World of Modeling
Economists choose their tools based on the problem at hand:
​Visual Models: Graphs and charts for intuitive understanding.
​Empirical Models: Data-heavy frameworks used to test theories against real-world history.​Mathematical & Simulation Models: Complex equations and computer programs used to project outcomes in highly uncertain environments.​Static vs. Dynamic: Static models provide a "snapshot" in time, while dynamic models track how an economy evolves over a long duration.Economic Models in the Age of Crypto
While traditional models were built for fiat systems, they are increasingly relevant to the Cryptocurrency Market:
​Supply & Demand: Essential for analyzing tokenomics and issuance schedules.
​Transaction Cost Models: Used to study how "gas fees" or network congestion impact user behavior.​Simulations: Vital for stress-testing DeFi protocols or predicting how a "halving" event might shift market sentiment.The Reality Check: Limitations
Models are tools, not crystal balls. Their reliance on "rational behavior" often ignores human psychology, and oversimplification can lead to "blind spots" during black swan events. A model’s value lies in its ability to provide structured guidance, not absolute certainty.
Summary
From a local fruit stand to the complexities of the blockchain, economic models provide the structural foundation needed to make informed decisions. They turn overwhelming data into actionable insights for policymakers, business leaders, and investors alike.
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