How PIPPIN, operating in a regulatory desert, found love on Aster: PerpDEX's reconstruction of the game theory logic of contract trading.

Author: danny

Centralized exchanges are currently conducting indiscriminate OI (Online Inquiry) and account freeze sweeps in their contract trading risk control. Professional traders urgently need a new trench that can withstand stray bullets of risk control, support deep ambushes, and provide covert operations and strategic maneuvering. Could Aster, the highly anticipated protocol, capitalize on this industry structural vacuum, leveraging its permissionless nature and the robust BNBchain ecosystem, to become a new battleground for large-scale on-chain contract trading?

The flames have been lit, but the smoke has not yet risen. Let's see how you all respond.

"Everyone goes through this stage. Seeing a mountain, you want to know what's on the other side."

I. Core Operational Elements of Contract Harvesting Schemes

A successful contract harvesting operation must have two key factors: 1. Absolute control over the spot market 2. Sufficient open interest (OI).

1.1 Spot Market Control: The Remote Control for Manipulating Index Prices

Market makers control the circulating supply of the target token, turning the spot market into a "data disk" that can be manipulated at will. Since the underlying price of a contract (Index Price) is mostly derived from the spot price, and the Index Price is an important component of the Mark Price, controlling the spot market is equivalent to controlling the Mark Price.

Once a market maker controls the circulating supply of spot goods, they can manipulate prices dramatically in the less illiquid spot market with minimal capital costs. These spot price changes are immediately transmitted to the futures market via oracles, thus altering the profit and loss situation of contract holders.

1.2 Massive Online Inquiry: A Fundamental Condition for Profitability

In situations where it is impossible to directly sell through spot trading (not only because spot trading is locked up and monitored, but also because the spot market currently has virtually no liquidity, selling would damage prices and be easily tracked on-chain), contracts have become the only effective way for market makers to make profits.

Assuming a market maker invests $10 million in operations, their costs on the spot side are fixed, including transaction fees, funding costs, wear and tear, and pump-and-dump costs. If they cannot cash out on the spot side, the market maker must earn at least $30 million through the contract side to cover costs and make a profit.

This explains why such a trading platform requires a massive amount of open interest (OI). Only when the contract open interest is large enough can small fluctuations in the spot market generate enough profit on the contract side to cover trading costs.

II. A Relic of the Times: CEXs Tighten Risk Controls, Preventing Massive Online Investment (OI) Transactions

Limitations and account risks of centralized exchanges

With increasing global regulatory compliance requirements, CEXs such as Binance have strengthened their monitoring of abnormal account behavior. For large-scale funds, conducting intensive trading on CEXs faces multiple obstacles:

Account suspension and fund freeze: Due to anti-money laundering and compliance reviews, frequent transfers of large sums of money and abnormal transaction frequency are very likely to trigger the risk control system, resulting in account suspension or long-term asset freeze.

Open Interest Cap (OI Cap): To prevent systemic risks, centralized exchanges set strict limits on the open interest (OI) of a single account or a single currency pair. This makes it exponentially more difficult for market manipulators to build massive positions that can influence market expectations.

Takeover risk: Under extreme volatility, the CEX's liquidation engine and insurance fund mechanism may cause the market maker's position to be automatically taken over by the system or forcibly reduced (ADL), making the original harvesting plan go to waste.

III. Aster: An On-Chain Battleground and a Permissionless Stronghold within the Binance Ecosystem

With the strong endorsement of Yzi and CZ, and the high degree of overlap between Bnbchain's ecosystem and Binance's trading users, with no shortage of active trading users and market makers, Aster has also opened up its own new battlefield in the PerpDEX track.

Aster's API is basically the same as Binance's, which greatly reduces the learning and migration costs.

For traders, the Bnbchain ecosystem and Aster offer unparalleled advantages over other centralized exchanges. It is permissionless, meaning anyone can trade simply by connecting a wallet, with no risk of account bans. On Aster, large traders can open massive positions with impunity, without worrying about intervention from centralized platforms or "black box risk control."

This environment has given rise to a new narrative of "contract harvesting," which involves using information asymmetry and capital advantages on the less liquid PerpDEX to transform the contract market into an "ATM" for obtaining profits that cannot be realized in the spot market.

IV. OI Anomalies Taking Pippin as an Example

Pippin ($PIPPIN), an AI-driven meme coin that became active in early 2026, demonstrates the characteristics of this manipulation model. On-chain data shows that Pippin's internal holders appear to control approximately 80% of the supply through 27 linked wallets, representing a typical high level of control.

On Aster, Pippin exhibited an enormous amount of Open Interest (OI) that was completely disproportionate to its daily trading volume. Pippin's OI reached 71m (it should actually be 35.5m), but its 24-hour trading volume was only 7.6m, resulting in a trading volume/OI ratio of only 0.214, which is a very strange phenomenon.

The logic behind this phenomenon is that market makers accumulate large positions through Aster's permissionless environment without requiring actual trading. When market makers manipulate the spot market by buying and selling (index price rises/falls), their contract positions on Aster generate massive unrealized profits. Because there is no centralized monitoring, this self-manipulation can continue until enough counterparties are found to realize the profits.

V. Despite poor liquidity, see how I turn positions into profits: price transmission and the role of market makers

On PerpDEXs with low liquidity and activity (such as Aster), the core challenge for market makers is how to smoothly exit their positions, i.e., "distribute" their holdings. However, on platforms like Aster with relatively low liquidity, price smoothing and transmission heavily rely on market makers and bots. How exactly is this achieved?

Note: Aster's liquidity for certain trading pairs is actually very good, in no way inferior to CEX.

5.1 Cross-Exchange Price Transmission Mechanism

After accumulating a large number of open interest (OI) positions on Aster, market makers manipulate the spot market to cause price fluctuations. These fluctuations not only generate unrealized profits on Aster (and liquidation of existing positions, but also affect Aster's trading volume and liquidation), but also propagate through the following pathways:

Oracle trigger: Spot price change -> Oracle update -> Aster Index Price change.

CEX contract following: Since Binance is a liquidity hub, market makers simultaneously create volatility in both Binance Alpha and Binance Perp.

Price Spread Control and Transmission: Market makers artificially control the price spread between Aster and Binance through market-making robots. To avoid one-sided risks, market makers transmit price pressure from Binance to Aster, while market makers wait for this liquidity on Aster, their "data platform," to ultimately realize their profits.

Suppose the market maker is a net long position in Aster and creates an "arbitrage opportunity" between Aster and Binance where Aster's price is higher and Binance's price is lower.

According to the theory of price reversion, once arbitrageurs seize this opportunity, they will open short positions on Aster and long positions on Binance. In this way, the market maker can conveniently transfer their own positions (closing short positions) to the arbitrageurs and realize profits, and vice versa.

For example:

When market makers drive up spot prices, they deliberately control the price difference between Aster and Binance (or other major exchanges).

(The image above shows Aster's offer, and the image below shows Binance's offer. Please ignore the formatting; this article uses screenshots directly to show you that this is an opportunity that can be observed with the naked eye.)

Creating a high premium: Market makers first exert pressure in the spot market, while simultaneously pushing up the price on Aster, making Aster's price significantly higher than Binance's index price. (Aster's order book is relatively thin, as shown in the image below.)

Attracting arbitrageurs: Arbitrage bots around the world will quickly detect this price difference. Based on the traditional logic of mean reversion, the bots will expect Aster's price to eventually fall back and anchor to Binance's price.

Therefore, these bots will open short positions on Aster (and earn funding fees) while simultaneously opening long positions on Binance, attempting to profit from the price difference.

Leveraging Market Momentum for Position Building/Reduction: At this point, the robot's short positions become the counterparty to the long positions the market maker wants to close. The market maker uses this "market inertia" to smoothly transfer huge profits to these robots who believe they are engaging in risk-free arbitrage, without triggering a market crash themselves.

Furthermore, the short positions held by bots can become the fuel for arbitrage, as these short positions become the counterparty for the bots to close their long positions when they are liquidated. The bots exploit this "market inertia" to attract more arbitrage bots and retail investors, ultimately pocketing huge profits.

5.2 Price Transmission and Market-Making Robot Collaboration

Market makers not only profit within the market by manipulating the spot market, but also cause correlated fluctuations in Binance Perp. Since market-making bots typically adjust their quotes based on prices from multiple exchanges, market makers' actions on Aster can influence oracle inputs, thereby affecting global index prices.

This "price transmission" effect allows market makers to launch an attack in a smaller, more controllable arena (Aster) and attract players from larger, more liquid arenas (Binance) to this carefully prepared arena to cash out liquidity.

5.3 Data Disk and Real Activity

Analysts such as Coinglass have pointed out anomalies in Aster, including a mismatch between trading volume and open interest, and extremely low liquidation data. This further confirms Aster's nature as a "data trading platform."

The bookmakers don't need Aster to provide excellent organic liquidity; they just need Aster to provide a stable settlement board that doesn't ban accounts and supports high leverage.

VI. Limitations and Operating Costs

While bookmakers have considerable freedom on Aster, this approach is far from free. Besides the high funding rates (settled hourly), the friction caused by insufficient liquidity is also a significant cost.

6.1 Expenditure on funding rates

On Aster, the balance between bulls and bears is severely disrupted because the open interest (OI) created by market makers often far exceeds that of natural traders. As the main bulls, market makers must continuously pay funding fees to their counterparts.

In some extreme cases, the annualized funding rate may exceed 200%. This means that market makers must complete the entire process of pumping and dumping shares in a very short time; otherwise, the huge interest expenses will quickly erode their operating capital.

The chart above shows that when opening a long position, the daily funding fees on Aster are 0.64% higher than on Binance and 0.81% higher than on Bybit. If we assume an OI of 30m (Aster's nominal OI needs to be divided by 2), this means that you have to pay nearly 96,000u more in funding fees to the short side every day compared to Binance.

6.2 Liquidity Friction and Spread

While Aster's liquidity performs well on PerpDex, its overall liquidity depth still lags significantly behind Binance. Large positions can generate substantial slippage when entering and exiting trades.

Aster orderbook

Binance orderbook

It is worth noting that some trading pairs on Aster use dynamic slippage, with the slippage amount proportional to the current OI and the size of the new opening position.

To deal with this slippage, market makers usually do not close their positions directly on the order book all at once. Instead, they use market makers (passive), over-the-counter (OTC) trading, or the aforementioned arbitrage inducement strategies to complete the distribution in batches with minimal slippage (twap).

What?! You're asking me which direction Aster should take after this?

With the launch of the Aster Chain mainnet and the application of its ZK privacy technology, future manipulation activities will become more covert and untraceable—perhaps this is the true meaning of Privacy for Aster.

Compared to trading subsidies, volume manipulation, and zero fees, this is the real necessity. If Aster can capitalize on this window of opportunity presented by Binance and other CEXs tightening risk controls, create its own derivatives trading arena, and seize this opportunity, its future looks promising.

"I wanted to tell him that maybe after you get over the mountain, you'll find there's nothing special, and looking back you'll think this side is better, but he wouldn't believe me. Knowing his personality, he won't be satisfied without trying it himself."

Ashes of Time

postscript

The overlooked, brutal aftermath: the second phase of the game.

This script has an even more brutal second half...

Once the major players have finished distributing their shares, the market structure becomes: the major players have left the market, arbitrage robots hold huge short positions, and prices remain at a high premium.

There are two possible scenarios:

Scenario A: Boiling a frog in lukewarm water (funding rate trap)

Arbitrageurs expect prices to quickly revert to their previous levels. But what if the major players (or new market makers) choose not to actively sell off, but instead allow prices to remain high for a long time in order to maintain some kind of profit?

While bots should be charged funding fees for holding short positions, market makers may have already accumulated enough profits during the price surge to cover the initial funding fees. Even more concerning is that if market sentiment becomes extremely volatile, retail investors' speculative buying could maintain high prices even after the market makers exit. Their long positions on Binance, intended for hedging, might face ADL (Advance Limit on Demand) due to market volatility, but Aster lacks sufficient liquidity to unload these positions.

Scenario B: Hunting (Short Squeeze)

After successfully dumping long positions at high prices to the robot (converting them into short positions for the robot), the market maker may sometimes reverse the operation.

The market makers know that the biggest short sellers in the market right now are those mechanized arbitrage robots.

If the market maker (or in conjunction with other funds) aggressively drives prices up again in the spot and derivatives markets, the arbitrage bot's short positions will instantly face huge unrealized losses. Because the bot has strict risk control and stop-loss lines (or insufficient margin), it will be forced to buy at market price to close its short positions and stop the loss.

A surge of stop-loss buy orders from numerous robots will further drive up prices, triggering even more stop-loss orders from robots. Market makers then use these "buy orders" from robot stop-loss orders to engage in a second round of profit-taking at higher prices (e.g., by opening new short positions).

Finally, after all this back and forth, how much do you think the bookmaker made?