The transition from traditional trading to a digital and algorithmic environment has brought about profound changes in the structure of global financial markets. In this context, the concept of liquidity is no longer simply the ability to convert assets into cash but has become a battlefield of information and manipulation. According to observations from the team of experts at Tan Phat Digital, Fake Liquidity is posing serious challenges to market integrity and investor safety, especially in dynamic financial centers such as Ho Chi Minh City.
The Nature and Structure of Fake Liquidity
Fake Liquidity is an intentional distortion, where volume figures trades or pending orders in the order book do not reflect real market demand. Instead, they are generated by computer algorithms, trading bots or "whales" to create an illusion of excitement.
Here are the core differentiating features:
Origin: Real liquidity comes from real investment needs and risk management; while fake liquidity is created by bots, algorithms or self-buying and selling behavior.
Persistence: Real liquidity exists for a long time and gradually increases with asset value; Fake liquidity is only temporary, often appearing and disappearing suddenly.
Reaction to price: Real orders will remain in place to be matched when the price approaches; Fake orders are often withdrawn or canceled as soon as the price approaches (spoofing).
Purpose: Real transactions aim to exchange assets; fake liquidity to manipulate prices, lure psychological traps or increase floor ratings.
Price slippage: Low and stable in the real market, but unusually high in the virtual market when orders disappear.
Operating Mechanism of Wash Trading: Engine to create Virtual Volume
Wash trading is the act of a subject buying and selling the same asset for himself to create artificial trading volume figures. Tan Phat Digital notes that this technique is often used to attract retail investors by creating a false sense of the "hotness" of the asset.
See more: What is Liquidity?
Quantitative Analysis and Behavioral Indicators
To detect this behavior, researchers use two main factors: "Liquidity Jump" and "Liquidity Diffusion" (liquidity diffusion). The combination of both of these factors at a high level is a characteristic sign of manipulation, where nefarious traders deliberately create virtual price pressure to profit from passive investors.
Wash Trading Scale Statistics (Data 2024-2025)
Based on heuristics, the scale of this activity is extremely remarkable said:
Total suspected volume: Ranging from 704 million USD to over 1.87 billion USD depending on authentication method.
Number of participating wallets: More than 23,436 unique wallet addresses have been identified participating in unusual order matching patterns.
Transaction frequency: Several A single wallet can perform more than 54,000 buy-sell transactions that are almost identical in volume in a year.
Focus goal: Liquidity pools on decentralized exchanges (DEX) and newly listed tokens under the Pump-and-Dump model.
The rise of "Volume-as-a-Service" (VaaS) services such as Volume.li has made wash trading more professional, sometimes accounting for up to 43% of the total volume of a token before the project developers carry out the act of "clearing" the goods.
See more: CEX vs DEX 2026
High-Frequency Trading (HFT) and Order Book Manipulation Techniques
Fake Liquidity Lurking in the Order Book Through Flow-Driven Tactics money:
Spoofing and Layering: Spoofing places large orders and then cancels them as soon as the price approaches to create fake signals. Layering is more sophisticated by placing multiple orders at different prices to create a sense of sustained market depth.
Quote Stuffing: Sending tens of thousands of orders per second to clog the system, creating data lag for other investors, allowing HFT institutions to conduct illicit arbitrage trading.
Recognizing Fake Liquidity Through Fractionation Analysis of Price Structure
Investors need to switch from pure chart observation to order flow analysis.
Liquidity Sweeps: Price moves strongly through the old peak/bottom to trigger the crowd's stop loss, helping "Smart Money" match large orders at the best price.
Recognizing signs: Appears Equal Highs/Lows; long-legged candlestick after false breakout; Volume spiked at the sweep point but price did not maintain the breakout momentum.
CVD Analysis: Use Cumulative Volume Delta to measure active bid/ask spreads. If the price is rising but CVD is flat or falling, it is a sign of divergence, signaling an impending liquidity trap.
Real Measuring Indicators from Tan Phat Digital
To appraise a market, we recommend the following criteria:
Volume/Depth Ratio: If the reported volume is hundreds of times larger times the actual order book depth (usually 1% or 2%), which is a "red flag" for virtual liquidity.
Liquidity Score Index (CoinMarketCap): Prioritize exchanges with scores between 400-1,000, as this index measures actual slippage for orders from $100 to $10,000 rather than relying on self-reported volume report.
Web Traffic Factor: Large volume but low number of visitors is often a sign of a self-trading bot.
Typical Manipulation Cases and Legal Updates 2026
History and reality record many serious cases:
Bitfinex and Tether: Accused of using unsecured USDT to create virtual demand for Bitcoin.
Fine in Vietnam - PAS Stock (February 2026): The State Securities Commission fined Ms. Bui Thi Phuong Thuy 1.5 billion VND for using 19 accounts to create fake supply and demand and manipulate PAS shares. At the same time, 16 related individuals were also suspended from trading for 2 years.
Developments of Mr. Pips (Pho Duc Nam): As of early 2026, authorities have recovered and frozen assets amounting to more than 5,315 billion VND from this fraud ring. The case shows the dangers of virtual trading floors programmed by individuals to deceive investors.
Risk Management Strategy for Investors
Tan Phat Digital proposes a 4-step appraisal process:
Check the reputation of the floor: Exchange Rank score above 6.0 and have Web Traffic Factor high.
Check volume quality: Volume/Depth ratio does not exceed the industry average (usually less than 50-100 times).
Check slippage: Liquidity Score above 400 for major trading pairs.
Order flow confirmation: Use tools like Bookmap Heatmap or CVD to See the consensus between price and real volume.
In addition, investors should be wary of projects with sudden increases in volume without supporting news, or "trading" groups on Telegram and TikTok, which are often used to create liquidity to exit goods for group owners.
Case Study Details on Liquidity and Price Manipulation
Below is a summary of typical cases exposing the patterns Manipulation in practice:
1. Navinder Singh Sarao case (Flash Crash 2010): A trader in the UK used custom software to perform "dynamic layering", placing thousands of virtual orders on the E-mini S&P 500 futures contract, causing the US market to evaporate nearly 1,000 billion USD in 36 minutes.
2. Great case of J.P. Morgan ($920 million fine):Traders at the precious metals and treasury desks of J.P. Morgan performed tens of thousands of spoofing episodes over the course of 8 years to manipulate prices according to the bank's wishes.
3. Trinh Van Quyet case (FLC Group): FLC Chairman directed the use of hundreds of accounts to continuously buy and sell, creating fake supply and demand for 5 stock codes (AMD, HAI, GAB, FLC, ART) to push up prices and gain illegal profits of more than 723 billion VND.
4. Mango Markets and Avraham Eisenberg: The attacker used 10 million USD to dramatically increase the price of MNGO tokens through oracle manipulation, then used this virtual asset value as collateral to drain 110 million USD from the platform.
5. Bui Thi Phuong Thuy and PAS Stock (February 2026): Ms. Thuy used 19 stock accounts to create fake supply and demand for the PAS code. The management agency fined 1.5 billion VND and banned transactions for 16 individuals lending related accounts.
6. FBI Sting - Operation Token Mirrors (NexFundAI): The FBI created its own NexFundAI token to lure market maker companies (ZM Quant, Gotbit, CLS Global) to participate in providing wash trading services, exposing the "manipulation-as-a-service" model.
7. KuCoin and the 300 million USD fine (January 2025): KuCoin exchange was fined for lacking KYC/AML mechanisms, allowing wash trading and illegal cash flows to circulate through the platform, forced to withdraw from the US market.
8. OKX and Allegation of $5 Billion Money Laundering: OKX admitted wrongdoing related to operating an unauthorized money transfer business, allowing criminal organizations to circulate more than 5 billion USD in suspicious transactions through the system.
9. Kaiko's Bitforex analysis: Kaiko discovered that Bitforex has a Volume/Depth ratio 280 times higher than normal, with "crosshair" patterns typical of wash trading appearing continuously on the tick trade chart.
10. Volume.li bot and "Volume-as-a-Service":This bot generated up to 43% of the total trading volume for Donald J. Chump tokens on Uniswap in 5 days, demonstrating the professionalization of virtual volume boosting services.
11. ShibaFarm - Scam Token Ecosystem:ShibaFarm's Deployer has created and wash traded more than 50 different tokens by providing 90% of its own liquidity, creating virtual growth price charts to lure investors.
12. Bybit and the Lazarus Hack (February 2025): The Lazarus group manipulated Bybit's Safe wallet infrastructure, causing the exchange to accidentally transfer 1.4 billion USD of Ethereum to the attacker's wallet, causing record liquidity fluctuations.
13. Mt. Gox and Historical Wash Trading Research:Analysis of 18 million transactions shows that wash trading booms most when real liquidity is at its lowest, helping manipulators control prices with minimal cost.
14. Nguyen Ngoc Chien & Tran Quang Canh (SJS Stock): Two individuals borrowed 15 securities accounts to create fake supply and demand for the SJS code in the period 2023-2024, were fined a total of 3 billion VND in January 2026.
15. Manipulation of CRC Stock (Create Capital Vietnam): Mr. N.T.Đ used 10 accounts (including 8 borrowed accounts) to internally trade CRC code to maintain the price, causing great losses to investors when the virtual money flow withdrew.
16. Binance and Huione Group (Cambodia):Data shows that at least $408 million in cryptocurrency has flowed from Huione Group (the unit accused of money laundering for Chinese criminal gangs) into accounts at Binance.
17. Le Anh Tuan - Rug Pull Baller Ape Club case: In 2022, the US Department of Justice accused Le Anh Tuan of carrying out the case of rug pulling the NFT collection "Baller Ape", appropriating 2.6 million USD and then dispersing it through sophisticated on-chain techniques.
18. Poly Network - Hack "for fun" ($611 million): Attackers exploited a multi-chain vulnerability to drain $611 million in assets. Although the hacker later returned the funds, the incident showed the fragility of large decentralized liquidity pools.
19. BNB Chain and the Incident of 2 Million Fake BNB Tokens: In 2022, hackers took control of BSC Token Hub to create 2 million new BNB tokens (worth 570 million USD), tricking the system to withdraw assets from the chain.
20. Petro Times (PPT) and Hai Phong Manipulation Group:The Securities Commission discovered 2 individuals in Hai Phong using 19 accounts to continuously cross-trade PPT code, creating artificial supply and demand to manipulate the market.
21. Sinaloa Cartel and Coinbase:The report shows that a wallet address related to the money launderer of the Sinaloa drug cartel (Mexico) received more than 700,000 USD from accounts at Coinbase.
22. Token Pocket - Virtual Currency Investment Application Scam: Tens of thousands of people have been lured into the Token Pocket app with the promise of high profits, which is actually a scam model that causes many victims to lose from a few billion VND to millions of USD.
23. AGG Stock Scandal (An Gia Real Estate): At the end of 2025, the market noted signs of price inflation and manipulation for the AGG code, leading to investigations into the transparency of sudden trading volumes.
24. LPLtrade, ZenoMarkets network of Mr. Pips: Pho Duc Nam's group created a series of fake brokerage websites such as ZenoMarkets, Londonex, LPLtrade to lure the first 12 victims to lose more than 11.1 billion VND, before being exposed to a fraud scale of 5,200 billion.
25. Case of Land Auction Manipulation in Ninh Binh:The investigation agency prosecuted 27 defendants who used the name of businesses to intervene and manipulate land auctions, causing losses to the state budget of more than 20 billion VND through fake documents.
Frequently Asked Questions (FAQ) about Fake Liquidity
1. How is Fake Liquidity different from real liquidity? Real liquidity comes from people's need to buy and sell based on asset value. Fake liquidity is artificially created by bots or virtual orders to deceive psychology, often disappearing as soon as the price gets close to that level.
2. How does wash trading work in practice? This is the act of a person (or group) buying and selling assets to themselves through different wallets. The goal is to fake transaction volume to make the project look vibrant and attract new investors.
3. What is Spoofing and how to recognize it? Spoofing is placing extremely large buy/sell orders with no intention of matching the order. You can notice it on the order book when a large price "wall" suddenly disappears (cancels the order) just a few milliseconds before the price is reached.
4. Is Liquidity Sweep a trap or an opportunity? It is a manipulation by large organizations to push prices through old peak/bottom areas to trigger stop loss orders of small individuals. If you understand how it works, this is an opportunity to enter a position in the same direction as "Smart Money" after the sweep ends.
5. Why should I care about CoinMarketCap's Liquidity Score?Because it ignores self-reported Volume numbers (which are easily faked). It is based on simulating real transactions to measure slippage. The higher the score, the more realistic and safe the liquidity.
6. What does the Volume/Depth ratio reflect about an exchange?This ratio compares trading volume to pending order depth. If Volume is hundreds of times larger than Depth, it is a sign that the floor is using wash trading to "inflate" the data.
7. How does the CVD (Cumulative Volume Delta) tool help in detecting traps? CVD measures the difference between active buying and selling. If the price is increasing but the CVD is moving sideways or decreasing (diverging), it is a warning that the actual buying force is not strong and the price can reverse and collapse at any time.
8. What is the "Crosshair" pattern in tick trade analysis? This is the clearest sign of wash trading: a buy order and a sell order occur at the same time, at the same price and in the same quantity. On the tick chart, they form a crosshair.
9. What is the biggest harm of fake liquidity to individual investors? That is the phenomenon of extremely high slippage. You think you can sell for X price, but when the order is matched, the actual price is much lower because the previous pending orders were only virtual.
10. Mr. case Pips (Pho Duc Nam) has any new updates in 2026? Authorities have recovered and frozen more than 5,315 billion VND in assets. Currently, the process of tracing money flows transferred abroad is being implemented to ensure the rights of more than 600 reported victims.
11. Ms. Bui Thi Phuong Thuy was fined 1.5 billion VND for what act? Ms. Thuy used 19 different securities accounts to continuously cross-trade, creating fake supply and demand to manipulate PAS stock prices from 2021 to 2022. The case just had a penalty conclusion in February 2026.
12. How is quote stuffing a manipulation technique? This is a technique of high-frequency trading (HFT), sending tens of thousands of orders to the exchange and then immediately canceling them to clog the data system, creating a speed advantage for manipulators compared to regular investors.
13. Is Layering the same as Spoofing? Relatively similar in purpose but different in implementation. Spoofing is usually one large order, while Layering is placing multiple orders at different prices on top of each other to create the illusion of a very strong market depth.
14. How to distinguish between a real break (Breakout) and a fake break (Fakeout)? Watch the candle close. If the candlestick breaks through the support/resistance level but retreats quickly and closes inside the old range on high volume, it is usually a liquidity sweep (Fakeout).
15. Should I trade during low liquidity hours? Shouldn't. Thin liquidity hours (like the early morning Asian session for gold/forex) are when it is easiest for bots to manipulate prices at the lowest cost. Prioritize trading during the London or New York sessions for more abundant real liquidity.
Fake liquidity is an inevitable but dangerous part of modern financial markets. In 2026, as trends such as tokenization and AI become more popular, manipulation tactics will also become more sophisticated. Tan Phat Digital believes that knowledge and prudence are the most important weapons to help investors convert risks into opportunities, following the footsteps of smart money instead of becoming victims of the market.
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