WuBlockchain ၏ ပရိုဖိုင်

Author | @agintender
Complied by | WuBlockchain
Original Link: https://x.com/agintender/status/2047556448562073604
On March 12, 2020, BitMEX’s Arthur Hayes made a decision that went against everything his predecessors had done but ultimately saved the world: he disconnected his own servers from the internet, or, in other words, pulled the plug. The official announcement claimed that BitMEX had “suffered a DDoS attack.” But what was the truth?!
The truth was this: only $20 million in buy orders remained on the order book, while $200 million in liquidation sell orders were waiting to be executed. If BitMEX had not gone offline, the liquidation engine would have driven the BTC contract price all the way down to zero.
At that moment, the entire crypto perpetual futures market was only minutes away from systemic collapse.
All the sophisticated mechanisms in perpetual futures that now seem “self-evident”, including mark prices, tiered liquidations, USDT-margined contracts, and portfolio margin, were rewritten out of necessity after that moment.
Introduction: An Idea That Lay Dormant for Twenty Years
In 1993, Robert J. Shiller proposed an unusual type of derivative: it would have no expiration date, require no physical delivery, anchor its price to an external data source, and require long and short positions to make payments to each other at a specified rate. He envisioned it as a way to hedge liquidity risk in the real estate market. At the time, it was a classic example of something that was “elegant in theory but impossible to engineer”: traditional financial clearing infrastructure was too outdated, regulatory frameworks were too rigid, and no exchange was willing to touch a contract that “never expired.”
The idea remained dormant in academia for exactly twenty-three years.
On May 13, 2016, BitMEX pulled it out of the archives, poured Bitcoin fuel over it, and set it alight.
When the XBTUSD perpetual contract launched that day, no one realized that, ten years later, it would account for 93% of all derivatives trading activity in the crypto market. At the time, it looked more like a technical experiment: a 100x-leverage toy for a group of geeks with no fear of death. Yet over the following decade, that toy went through hundreds of crises, mass liquidations, manipulation attempts, and rounds in which its rules were weaponized and then patched. It ultimately evolved into a global pricing machine that processes nearly $200 billion in trading volume every day.
This article seeks to answer one specific question: how did every cog in this machine come into existence?
The answer was not drawn up by engineers on a whiteboard. Behind every cog was a specific disaster.
1.Genesis — The Pricing Triad and the Original Sin of Coin-Margined Contracts (2016–2018)
Engineering Shiller’s Concept
Perpetual futures faced one fundamental challenge: without an expiration date, there was no “mandatory point of convergence.” Traditional futures inevitably converge with spot prices on the settlement date. Without a specially designed anchoring mechanism, however, the price of a perpetual contract would become a purely speculative instrument left to drift.
BitMEX’s solution consisted of three interlocking components:
The index price is calculated as a weighted average of trading prices collected from multiple external spot exchanges. It serves as the entire system’s “physical anchor.” Its design rests on the assumption that even if a malicious actor has enough capital to corrupt a single data source, it would be difficult to corrupt all of them simultaneously.
The mark price, meanwhile, serves as the “liquidation anchor.” It is based on the index price, with the spot-futures basis smoothed using an exponential moving average, or EMA:
Mark Price = Index Price + EMA(Basis)
The liquidation engine recognizes only the mark price. Sudden “wicks” on the order book are smoothed out by the EMA and do not feed into liquidation decisions. This is the core mechanism designed to prevent “stop-hunting through price wicks.”
The funding rate acts as the “gravity” that pulls the contract price back toward the index price:
F = P + clamp(I — P, -0.05%, +0.05%)
Here, P is the premium index, while I is the fixed interest rate component, set at 0.01%. When the contract trades at a premium, F is positive and longs pay shorts, increasing the cost of maintaining a long position. When it trades at a discount, the opposite occurs. BitMEX initially settled funding every eight hours, with each payment capped at +/-0.75%.
This three-part system appears simple and elegant, but every parameter contains an implicit assumption. The fixed interest rate of 0.01% reflects the economic judgment that “holding stablecoins offers a slight interest-rate advantage over holding crypto assets.” This later became the basis of the well-known “structural anchor,” or “The Anchor,” effect discussed in BitMEX Research. The eight-hour settlement interval represented a compromise between market liquidity and server computing capacity. The +/-0.75% cap was a relatively conservative estimate of what constituted an “extreme deviation.”
These assumptions all held under stable market conditions. But markets never remain stable for long.
The Double-Edged Sword of Coin-Margined Inverse Contracts
Early perpetual futures faced a practical limitation: the stablecoin ecosystem was not yet mature. USDT’s circulating supply did not surpass $2 billion until early 2018, far below what was needed to support the derivatives market’s margin requirements. Traders held BTC, so BTC was the only asset they could use as collateral.
This gave rise to the “coin-margined inverse contract”: the contract was denominated in USD, but both margin and profits and losses were settled in BTC. Its payoff formula was nonlinear:
PNL (BTC) = Contracts x (1 / Entry — 1 / Exit)
In a bull market, long traders benefited from both contract profits, which increased the amount of BTC they held, and the appreciation of BTC itself. This created a double multiplier and powered countless early stories of overnight wealth. But profits and losses came from the same mechanism. During a crash, contract losses and the declining value of the collateral reinforced each other, creating a “death spiral.” For a trader holding a 10x leveraged long position, a 10% decline in BTC would not only produce a 100% unrealized loss on the margin allocated to the contract, but also reduce the fiat value of the collateral by 10%. With these two blows compounding each other, the liquidation engine would be triggered much sooner than theoretical models suggested.
Coin-Margined vs. USDT-Margined: How the Same Position Meets a Different Fate (10x Leveraged BTC Long, Price Falls 10%)
This vulnerability would be amplified to the extreme in 2020, but the first time it truly alarmed the market was in August 2018.
The First Lesson: OKEx’s 50,000 BTC Position and the “Socialized Clawback”
On August 3, 2018, a massive long position with a notional value of approximately 50,000 BTC, or around $360 million at the time, appeared in OKEx’s, now OKX, quarterly BTC futures market. The trader behind the position had clearly made a serious misjudgment about the market’s direction. As the price of BTC continued to fall, the position eventually reached its liquidation threshold.
（https://www.okx.com/zh-hans/help/announcement-on-the-investigation-and-handling-of-btc-contract-abnormality-warehouse-crossing-receipt）
At that moment, OKEx’s risk management system faced a dilemma:
Liquidating the position at market price would mean dumping 50,000 BTC worth of sell orders into an order book with an average daily depth of only a few hundred million dollars. This would instantly overwhelm the order book, resulting in a liquidation price far worse than the bankruptcy price. The exchange would have to absorb the resulting shortfall, while the cascading impact would trigger wave after wave of liquidations among smaller and mid-sized positions.
Not liquidating the position would mean breaking the rules and undermining confidence in the system.
OKEx ultimately chose what was then the industry’s “standard tool”: the Socialized Clawback. The system-wide loss caused by this massive bankrupt position was distributed proportionally among all traders who had made a profit that week. Many short sellers made money that week, only to watch as the exchange deducted a portion of their profits on a pro rata basis.
The community reacted with anger.
The problem with this mechanism was that it transferred risk from the “risk-taker” to the “innocent.” A trader who had profited from shorting ETHBTC could have part of that profit deducted because of the liquidation of a BTC long position that had absolutely nothing to do with them. This violated one of the most basic principles of trading: you should be responsible only for your own decisions.
The incident directly drove three major reforms across the industry:
First, exchanges introduced position limits. A single user’s position could no longer exceed a specified proportion of what the order book was capable of absorbing, eliminating “too big to fail” risk at its source.
Second, exchanges established sufficiently large insurance funds to absorb losses from bankrupt positions instead of passing them on to users.
Third, and this is where the story becomes truly interesting, OKEx was forced to abandon the Socialized Clawback and adopt a solution that Huobi had invented and validated several years earlier: the Auto-Deleveraging system, or ADL.
There is an often-overlooked historical detail here: ADL was not invented by BitMEX. It was invented by Huobi. As early as 2014–2015, Huobi, alongside OKCoin at the time, already dominated the crypto dated futures market. During that period, Huobi developed an auto-deleveraging algorithm that ranked positions according to “profit percentage x effective leverage” to distribute losses from bankrupt positions more fairly. When BitMEX launched the XBTUSD perpetual contract in 2016, it directly copied Huobi’s ADL design and made a few minor adjustments. BitMEX explicitly acknowledged this in its own 2025 blog post, “Adapt or Die”:
“We copied the Huobi ADL mechanism but made a few tweaks.”
The fundamental difference between ADL and socialized clawbacks lies in how precisely losses are allocated. A socialized clawback spreads the burden across the board, requiring everyone who made a profit to share the loss. ADL, by contrast, uses a precision-targeted ranking algorithm:
Ranking Score = PNL% / Effective%
Only counterparties that “use the highest leverage and have the largest unrealized profits” are forcibly closed. Their profitable positions are used to absorb the bankrupt positions of liquidated traders. Ordinary traders with low leverage and limited profits are unaffected.
Socialized Clawback vs. ADL: Two Loss-Allocation Philosophies for the Same Bankruptcy Crisis
Before 2018, both BitMEX and Huobi had already adopted ADL. OKEx alone continued to use the simpler and more heavy-handed Socialized Clawback. It was only after the 50,000 BTC position pushed the entire system to the brink of collapse that OKEx was forced to switch to ADL. From that point on, socialized clawbacks were consigned to history.
This episode offers an instructive lesson: one of the most important innovations in the evolution of crypto derivatives liquidation systems was developed by a Chinese exchange before BitMEX invented the perpetual contract. BitMEX holds an important place in history as the inventor of perpetual contracts, but Huobi was the true inventor of one of the critical risk management mechanisms that has enabled them to survive to this day.
Insurance Funds: The First Line of Defense Against Bankruptcy Losses
But ADL is not, and should not be, the first mechanism used to allocate losses. At its core, ADL means “forcibly closing the positions of profitable traders” under extreme circumstances. For a trader holding a profitable position over the long term, this still amounts to an unsolicited intervention. A sound risk management system should have a buffer capable of absorbing losses before ADL is triggered.
That buffer is the Insurance Fund.
The core logic of an insurance fund is remarkably simple. It captures a structural “surplus” generated during the liquidation process. When a user’s position is liquidated, the liquidation engine must close it in the market at the prevailing price. However, the exchange’s liquidation price is not the same as the bankruptcy price, which is the price at which the user’s account equity falls to zero. The difference between the two creates a surplus:
Insurance Fund Inflow = Liquidation Price — Bankruptcy Price
Consider a specific example. A trader opens a 100x leveraged BTC long position at $50,000. When BTC falls to $49,500, a decline of approximately 1%, the account’s maintenance margin is exhausted. However, the liquidation engine has already taken control of the position at $49,600. The account’s bankruptcy price is $49,500, while the liquidation execution price is $49,600. The $100 difference is neither returned to the user, whose position has already been liquidated and whose account equity has fallen to zero, nor recorded as revenue by the exchange. Instead, the entire amount is transferred into the Insurance Fund.
How the Insurance Fund Works:
This mechanism creates a subtle structural equilibrium. Under most normal market conditions, sufficient liquidity allows liquidated positions to be executed at prices better than their bankruptcy prices, generating a continuous stream of inflows into the fund. The fund then grows cumulatively over time. When extreme market conditions produce bankruptcy losses, the fund absorbs them first, leaving profitable traders completely unaffected. ADL is triggered only when the fund has been fully depleted and still cannot cover the remaining shortfall.
This is the three-tier defense system used by modern crypto derivatives exchanges:
If the first layer is sufficiently deep, the second is rarely reached. If the second is sufficiently precise, everyone else remains safe. At major modern centralized exchanges, including Binance, OKX, Bybit, and Bitget, insurance funds typically range from several hundred million dollars to more than $1 billion, enough to absorb the losses generated by most bankrupt positions. According to public data, Binance’s futures insurance funds remained between $500 million and $800 million for an extended period in early 2026, while Bybit’s USDT perpetual insurance fund remained above $400 million.
The insurance fund also serves another purpose: transparency. Because changes in an insurance fund’s balance directly reflect the frequency of “extreme liquidation events,” major exchanges such as Binance, OKX, and Bybit publicly display historical charts of their insurance fund balances. To some extent, changes in the fund’s balance serve as a barometer of the health of an exchange’s liquidation engine. A steadily rising balance indicates that liquidations are being executed smoothly and bankrupt positions are rare. A sudden sharp decline, by contrast, reveals that the liquidation engine encountered a liquidity gap during an extreme market event.
Historical Milestones:
2015–2017: Early exchanges, including BitMEX, OKCoin, and Huobi, had each introduced rudimentary forms of insurance funds, although they remained relatively small.
The 2018 OKEx 50,000 BTC Incident: This was the first time insurance funds became the subject of systematic industry-wide discussion. If OKEx had already established a sufficiently large insurance fund at the time, the fund could have absorbed the $400 million shortfall, eliminating the need for a Socialized Clawback altogether. After this incident, insurance funds came to be widely regarded as essential infrastructure across the industry.
2019–2020: Major exchanges began publicly disclosing insurance fund data as a demonstration of risk management transparency.
March 12, 2020, or “3/12”: Insurance funds faced their ultimate stress test. On that day, the insurance funds of Binance and Bybit recorded tens of millions of dollars in net outflows. However, because the funds were sufficiently large, they successfully absorbed most bankruptcy losses and prevented ADL from being triggered on a large scale. This was one of the most important disasters that did not happen during the March 12 crash.
The 2022 FTX Collapse: This provided a counterexample. FTX’s “insurance fund” had long been suspected of being a fabricated figure, and its actual size was far too small to cover the exchange’s derivatives exposure. When FTX ultimately collapsed, the fund failed to provide any meaningful protection.
2024–2026: The size of insurance funds became one dimension of “hard power” competition among major exchanges. Some exchanges even began publishing fund addresses that allowed balances to be verified on-chain in real time.
An insurance fund may appear to be a minor piece of financial engineering, but it occupies an exceptionally important position in the perpetual futures risk management system. It is the cog that transforms “liquidation” from a disaster for an individual user into a routine event that can be absorbed at the system level. Without an insurance fund, every liquidation risks becoming a matter for ADL. With an insurance fund, the vast majority of liquidations remain entirely invisible to other users.
This also explains an apparently puzzling phenomenon: crypto perpetual futures have consistently recorded hundreds of millions of dollars in liquidations each day, and retail traders complain daily about being liquidated and suffering losses, yet the broader market has never experienced a substantive cascading collapse as a result. The answer lies in this rarely discussed buffer.
2.The Liquidation System Comes of Age — The March 12 Crash and the Birth of USDT-Margined Contracts (2019–2020)
From Wholesale Liquidation to Tiered Surgery
Before 2018, the liquidation logic used by nearly every exchange was extremely crude. Once an account reached its maintenance margin threshold, all positions in the account were forcibly closed at market price.
This created two systemic problems. The first was over-liquidation. A large trader holding a $10 million position might need to close only $2 million of it to return to a safe margin level, but the system would indiscriminately liquidate the entire $10 million. The remaining $8 million in “excess liquidation” was not only unfair to the user, but also created enormous pressure on the order book. The second problem was the cascading effect. Market sell orders generated by the liquidation of a large position could overwhelm the order book, push smaller and mid-sized positions past their liquidation thresholds, and produce a waterfall collapse.
Partial Liquidation was the engineering solution to this problem. Its core principle was to divide positions into tiers based on notional value, with each tier assigned a different maintenance margin rate:
(Illustrative figures only. Actual parameters vary across exchanges.)
When liquidation is triggered, the system first closes part of the position, reducing the account’s remaining notional value to a lower tier and therefore lowering its maintenance margin requirement. If the account returns to a safe margin level after moving down a tier, the liquidation stops and the user retains the remaining position. This liquidation model substantially reduces the likelihood of over-liquidation and cascading collapse.
When liquidation is triggered, the system first closes part of the position, reducing the account’s remaining notional value to a lower tier and therefore lowering its maintenance margin requirement. If the account returns to a safe margin level after moving down a tier, the liquidation stops and the user retains the remaining position. This liquidation model substantially reduces the likelihood of over-liquidation and cascading collapse.
Bybit and Binance were among the first exchanges to fully adopt this mechanism around 2019. But whether it could withstand truly extreme market conditions would not become clear until March 12, 2020.
“3/12”: The Coming of Age of Perpetual Futures — The Shift from Coin-Margined to USDT-Margined Contracts
On March 12, 2020, the uncontrolled spread of COVID-19, combined with an oil price war, triggered panic selling across global markets. Bitcoin fell from approximately $7,800 to $3,800 in just over a dozen hours, recording its largest single-day decline at the time.
The crisis exposed three systemic flaws in the derivatives market.
The first was the reflexive collapse of coin-margined contracts. Retail traders used BTC as collateral to go long on BTC contracts. When the price of BTC plunged, contract losses and the declining value of collateral reinforced each other, accelerating the activation of the liquidation engine. This was not a problem limited to a handful of traders, but a structural problem affecting the entire market. During extreme downturns, coin-margined contracts inherently possess dynamics that accelerate their own collapse.
The second was cascading liquidations and the panic-driven withdrawal of market makers. After the system took control of hundreds of millions of dollars in long positions, a flood of market sell orders poured into the order book. Faced with overwhelming one-sided demand for liquidity, market makers simply withdrew. This was not a technical failure, but a rational business decision: providing two-sided quotes in a market in free fall was equivalent to suicide. Once liquidity had been drained, the BitMEX contract price briefly traded $500 below Coinbase’s spot price. This showed that even the anchoring relationship between the mark price and the index price could break down under extreme conditions.
The third was the inability of the underlying blockchain networks to support arbitrage-driven recovery. Under normal circumstances, arbitrageurs should have eliminated a $500 spot-futures spread within minutes by transferring BTC on-chain to BitMEX and opening a long position while simultaneously shorting on Coinbase, thereby locking in a risk-free profit. But on that day, Ethereum gas fees surged to hundreds of Gwei, while the Bitcoin network became severely congested. Arbitrageurs could see the price discrepancy but could not move capital into place. Bottlenecks at the physical network layer disabled the financial system’s ability to repair itself.
The Three-Part Death Spiral of the March 12 Crash:
At the most desperate moment, only around $20 million in bids remained on BitMEX’s order book, while more than $200 million in liquidation sell orders were waiting to be executed. Without intervention, the contract price would have been driven all the way to zero.
BitMEX chose to physically disconnect from the internet, forcing the platform offline on the grounds that it was “under a DDoS attack,” or, in other words, pulling the plug. The outage prevented an almost certain systemic collapse. It also marked the end of BitMEX’s era as the industry’s leading exchange.
The Institutional Legacy: Stablecoin-Margined Contracts Take Over
After the March 12 crash, the industry made a decisive choice: to abandon coin-margined inverse contracts as its mainstream product.
Stablecoin-margined linear contracts, which use USDT or USDC as both collateral and the settlement asset, rapidly gained prominence. Their payoff follows a simple linear relationship:
PNL (USDT) = Contracts x (Entry — Exit)
The collateral asset, USDT, is completely decoupled from the underlying asset of the contract. When BTC crashes, the value of your USDT collateral does not fall with it, eliminating the double death spiral at its source.
By the end of 2021, stablecoin-margined contracts accounted for more than 85% of perpetual futures trading volume across the market. Coin-margined contracts, meanwhile, were relegated to the status of a “specialized product,” primarily serving long-term holders with substantial spot BTC holdings who wanted to hedge using coin-margined contracts.
The March 12 crash did more than reshape the market for different contract types. Its more profound impact was to establish “risk engineering,” for the first time, as a core discipline in the design of CEX derivatives products. Partial liquidation, ADL, multi-source index prices, optimized EMA windows, and portfolio margin were among the mechanisms that became industry standards, with nearly all of them implemented in rapid succession during the two or three years following the crash.
This was the coming of age of crypto derivatives.
3.Institutional Participation and the Capital Efficiency Revolution (2020–2023)
From “Casino” to “Arbitrage Machine”
The bull market cycle that followed the March 12 crash, spanning 2020 and 2021, brought about a structural change: institutional capital began to treat the crypto derivatives market as a legitimate asset class worthy of serious allocation.
This shift began with market makers. Leading crypto-native market makers such as Wintermute, Jump Crypto, and GSR, along with high-frequency trading firms transitioning from traditional finance, entered CEX perpetual futures markets at scale. Rather than making directional bets, they focused on two activities: providing two-sided liquidity to order books and earning the spread, and conducting cash-and-carry arbitrage by going long in the spot market and short in the perpetual market to collect funding payments.
The large-scale entry of market makers and arbitrage funds produced three quantifiable effects:
The Three Quantifiable Effects of Institutional Participation (2020–2023):
Effect One: Funding Rates Were “Pinned Down.” Before 2020, BTC funding rates frequently reached extreme levels of more than +/-0.1% per hour, equivalent to annualized rates of hundreds or even thousands of percent. After 2022, BTC funding rates remained within an annualized range of +/-20% for 98% of the time. This was not because the market had become more “rational,” but because arbitrage bots instantly eliminated any significant deviation. According to BitMEX Research, the frequency of extreme funding rates declined by approximately 90% between 2016 and 2023.
Effect Two: Order Book Spreads Narrowed. In 2019, the top-of-book bid-ask spread for BTC perpetual futures typically ranged from 0.5 to 1 basis point, or bps. By 2023, it had narrowed to less than 0.1 bps. For large investors, the frictional cost of entering and exiting positions fell by an order of magnitude.
Effect Three: Open Interest Rose Dramatically in Absolute Terms. Aggregate open interest in BTC perpetual futures increased from approximately $2 billion at the end of 2019 to around $9 billion at the end of 2020, before surpassing $28 billion at its peak in late 2021. In just two years, OI increased by an order of magnitude.
Portfolio Margin: The Final Step Toward Wall Street Standards, and How Bybit Pulled Ahead
The extent to which institutional capital was willing to enter the market depended largely on capital efficiency. Early isolated margin systems physically separated the funds allocated to each position, resulting in extremely low capital efficiency. Cross margin pooled funds across an account, but still calculated the risks of different positions by simply adding them together. For hedged portfolios such as cash-and-carry arbitrage, the system could not “understand” that the long and short positions formed a delta-neutral portfolio, and therefore continued to require margin for both positions.
Three Generations of Margin Systems: The Leap in Capital Efficiency
Portfolio Margin, or PM, is the ultimate solution to this problem. It introduces a comprehensive risk assessment methodology similar to SPAN, or Standard Portfolio Analysis of Risk, used by traditional exchanges such as CME, or VaR, or Value at Risk. Instead of simply adding together the margin requirements of individual positions, the system constructs a multidimensional scenario matrix, including price movements of +/-5%, +/-10%, and +/-15%, volatility changes of +/-25%, and other scenarios. It then calculates the entire portfolio’s net loss under each scenario and uses the worst-case outcome to determine the margin requirement.
Consider a cash-and-carry arbitrage position that holds 1 million BTC in the spot market while shorting an equivalent 1 million BTC through perpetual futures:
Cross Margin: Long-side margin + short-side margin = double the capital cost
Portfolio Margin: The system recognizes the portfolio as a delta-neutral hedge with net risk exposure of approximately zero, reducing the margin requirement to nearly zero
The difference can range from several times to tens of times.
At this point, it is necessary to tell a story of leapfrogging the competition: PM was a crucial factor in Bybit’s rise from a second-tier exchange into the industry’s top tier.
How Bybit Pulled Ahead: A Timeline (2022–2026)
On June 15, 2022, Bybit launched its Portfolio Margin mode, although FTX had previously developed the concept into its most comprehensive form. The initial rollout covered USDC-settled perpetual futures and options. Two months later, in August, Bybit launched its Unified Trading Account, or UTA. This combined previously separate spot, stablecoin-margined, coin-margined, and options accounts into a single capital pool, with the margin requirements of all positions calculated under one global risk matrix.
This came during the deep bear market that followed the collapse of LUNA, when institutional market makers and quantitative funds had become more sensitive to capital efficiency than ever before. An exchange capable of reducing the margin requirement for cash-and-carry arbitrage to nearly zero allowed traders to run strategies at several times the scale possible on competing platforms. By combining PM with UTA, Bybit rose from the “second tier” behind OKX in just one year and attracted substantial institutional market-making liquidity that had previously belonged to other platforms. Current Coinglass data show that Bybit’s OI-to-trading-volume ratio of 0.71 is significantly higher than Binance’s 0.47 and OKX’s 0.28. This structural difference is an extension of Bybit’s early-mover advantage in PM: the platform accumulated more professional arbitrage positions rather than relying solely on retail turnover.
Binance and OKX subsequently introduced their own versions of portfolio margin and unified accounts, but Bybit had already established itself in the minds of institutional users during that window of opportunity. By 2023, portfolio margin had been fully implemented across major centralized exchanges and had become a standard feature for VIP and institutional users.
This meant that the margin efficiency of crypto centralized exchanges had officially caught up with, and in some respects even surpassed, that of traditional Wall Street prime brokers. It was the final piece of infrastructure needed for institutional capital to enter the market at scale. Bybit captured the largest share of the benefits generated by that development.
The Birth of a Two-Tier Market
Interestingly, institutional dominance did not drive retail traders out of the market. Instead, it divided the market into distinct tiers.
After 2023, a stable two-tier market structure emerged:
Upper Tier: Major Assets Such as BTC and ETH. Liquidity is dominated by institutional basis arbitrage and quantitative market making. Algorithms keep funding rates firmly confined within a normal range. Retail traders making directional bets have little chance of generating consistent long-term profits because they cannot compete with the bots operating in this market. According to an industry report by Wintermute, institutional investors concentrate 67% of their positions in BTC and ETH perpetual futures.
Lower Tier: Altcoins, Meme Coins, and Highly Speculative Tokens. This is the primary battleground for retail traders. Institutional arbitrage capital is reluctant to participate because liquidity is too thin, oracle systems are too fragile, and the risk-reward profile is unattractive. As a result, this market has become a direct contest between market manipulators and retail traders. Extreme funding rates, violent volatility, and frequent liquidations are concentrated in this tier.
This tiered structure has persisted to the present day and continues to deepen.
4.The Era of Funding Rate Weaponization (2023–2025)
TRB: A Textbook Short Squeeze
In late 2023, TRB, the token of the oracle project Tellor Tributes, became the subject of a short squeeze in Binance’s perpetual futures market that was dramatic enough to enter the textbooks.
The sequence unfolded as follows:
Step One: Gain Control of the Spot Supply. A whale quietly accumulated TRB in the spot market until it gained effective control over the token’s circulating supply. Nothing appeared unusual in the public market because each purchase was dispersed and executed gradually.
Step Two: Create a Deep Discount in the Perpetual Market. The whale began using a relatively small amount of capital to push up TRB’s spot price rapidly. Because retail traders in the perpetual market remained skeptical of TRB’s fundamentals, as the project had no obvious positive catalyst at the time, they rushed to short the contract in an attempt to “catch the top.” As a result, the perpetual price lagged significantly behind the spot price, creating a deep discount and triggering extremely negative funding rates.
Step Three: Extract Funding Payments. Under the rules in place at the time, short sellers had to make substantial payments to long traders every eight hours. The whale itself held the dominant long position. While pushing up the spot price and generating unrealized gains, it also collected funding payments directly from short sellers every eight hours.
Step Four: Trigger the Short-Squeeze Spiral. As the price continued to rise, short sellers eventually exhausted their margin. Market buy orders from the liquidation engine flooded the order book, pushing the price even higher and triggering another round of short liquidations. This created a classic positive feedback loop. On New Year’s Eve, TRB surged to an all-time high of approximately $600 before collapsing almost instantly. Total liquidations across the market exceeded $70 million that day.
The central problem exposed by the TRB incident was that, in a market with highly concentrated supply and thin liquidity, the funding rate mechanism could be transformed from a “price convergence tool” into a “targeted extraction channel.” It was designed to penalize the side that deviated from market equilibrium. But under an “artificial equilibrium” created by a market manipulator, it instead penalized the traders whose assessment of the project’s fundamentals was correct.
Binance responded by changing its rules. It shortened funding settlement intervals for long-tail assets from eight hours to four hours or even one hour, while expanding the cap for each funding payment from +/-0.75% to +/-2% or even +/-3%. The intention was to increase the cost of maintaining a position sharply enough to force extreme price deviations to converge more quickly.
This response effectively limited the scale of similar strategies in subsequent cases, but it also became a double-edged sword.
ALPACA: When the Rules Themselves Were Weaponized
In April 2025, Binance announced that it would delist ALPACA Finance’s spot and perpetual trading pairs. Conventional logic suggested that delisting would drain liquidity, marginalize the project, and cause its price to collapse. Based on this “consensus,” large numbers of traders aggressively shorted ALPACA perpetual futures. (https://x.com/agintender/status/1954160744678699396?s=20)
Instead, the price surged more than tenfold.
This is how it happened:
Layer One: The “Illusion of Certainty” Created by the Delisting Announcement. When everyone believed the price was “certain to fall,” short positions became extremely crowded in the perpetual market, creating a severe imbalance between longs and shorts. The deep discount pushed funding rates to extremely negative levels.
Layer Two: The Fatal Evaporation of Circulating Liquidity. After the delisting announcement, rational long-term holders and market makers began to withdraw, causing spot liquidity to contract sharply. At that point, only a small amount of capital was needed to push the spot index price substantially higher. Coordinated capital took advantage of this liquidity vacuum with precision.
Layer Three: The Increased-Frequency Mechanism Provided “Assistance in Reverse.” In response to the abnormal volatility, Binance activated its dynamic funding frequency mechanism under the rules introduced after the TRB incident. Funding payments of several percent per hour were originally intended to force extreme deviations to converge rapidly. In ALPACA’s case, however, they became fuel that accelerated the depletion of short sellers’ capital. Short sellers faced pressure from two directions: unrealized losses caused by the rising price and the continuous drain of more frequent funding payments.
Layer Four: The Short-Squeeze Spiral Was Triggered. Once short sellers exhausted their margin, liquidations began. Buy orders from the liquidation engine pushed the price even higher, repeating the same pattern seen with TRB.
The broader significance of the ALPACA incident was that it exposed a previously overlooked mechanical paradox: an exchange’s own risk management rules could become an attack vector. The increased-frequency mechanism assumed that “market participants would respond rationally to higher costs by exiting their positions.” But in the face of the overwhelming consensus created by the delisting announcement, short sellers did not believe there was any reason to exit. They treated the delisting as a pricing assumption that guaranteed a decline, while the rules’ “punishment” only pushed them deeper into their positions.
After the incident, the industry introduced more refined management of delisting transition periods. Following a delisting announcement, exchanges would first reduce the maximum leverage substantially, for example, from 20x to 5x, and then lower position limits in stages. They would also disable accelerated funding settlements and restore the standard eight-hour interval before forcibly closing the remaining positions at the mark price ahead of the final delisting. The core principle behind this combination of measures was to tighten every risk parameter as liquidity gradually disappeared, leaving neither side room to speculate in the final liquidity vacuum.
MYX, COAI, and AIA: Structural Vulnerabilities in the Highly Speculative Token Ecosystem
TRB and ALPACA were sensational, isolated incidents. But the risks that became persistent during 2024–2025 came from a group of micro-cap tokens with market capitalizations ranging from only a few million to tens of millions of dollars, including MYX, COAI, and AIA. The characteristics shared by these highly speculative tokens formed a textbook collection of structural vulnerabilities.
Extreme Liquidity Asymmetry. Daily spot trading volume might amount to only a few hundred thousand dollars, while leverage could push the notional open interest in perpetual futures to several or even more than ten times the token’s spot market capitalization. The tail of the derivatives market began wagging the dog of the spot market. A moderately sized liquidation event in the perpetual market could be enough to move the spot price by several percentage points.
Fragile Index Prices. Spot trading in these tokens might be concentrated on only one or two exchanges. This rendered the protection provided by a multi-source weighted index ineffective. A manipulator needed to deploy only a small amount of capital across one or two spot order books to move the index price directly.
Extreme Funding Rate Swings. Because institutional arbitrage capital was unwilling to trade these illiquid, high-risk assets, funding rates lost their natural “ceiling.” They could surge to dozens of times their normal levels within a short period.
The typical script for these highly speculative tokens was almost always the same:
The manipulator quietly accumulates tokens in the spot market and gains control of the circulating supply -> launches a surprise spot rally during the least liquid hours, such as early morning in Asia or on weekends -> retail traders rush to short the perpetual contract -> the price continues rising and triggers short liquidations -> liquidation buy orders push the price higher and create a short-squeeze spiral -> the price surges by 300%-500% within hours -> once the shorts have been wiped out, the manipulator reverses course, dumps its holdings, and exits -> the price falls by half or collapses to zero within minutes -> both long and short traders are left amid the wreckage of mass liquidations.
The Standard Playbook for Highly Speculative Tokens, as Seen in MYX, COAI, AIA, and Similar Assets:
Exchanges have responded by continuously tightening risk parameters for long-tail assets, including lowering maximum leverage, increasing maintenance margin rates, and introducing position limits. But as long as the liquidity gap between spot and derivatives markets persists, these highly speculative token rallies will not disappear. They are a structural “tax” on the crypto derivatives market. As long as perpetual futures are offered for long-tail assets, such events will continue to recur periodically.
The Latest Form: “Data Plays” — Systematic Manipulation of High-FDV, Low-Float Tokens
If TRB was an isolated outbreak and MYX, COAI, and AIA represented opportunistic campaigns involving highly speculative tokens, the recently emerging phenomenon of “data plays” marks a structural evolution of this manipulation model. Its origins lie not in the product design of any particular exchange, but in the economic structure of the latest generation of newly listed tokens: high fully diluted valuations, low circulating supply, and extremely concentrated ownership.
Together, these three characteristics create a token model that appears “built for manipulation”:
High FDV Means an Inflated Valuation on Paper. Project teams and market makers can use a very small amount of circulating supply to support paper valuations of several billion dollars, directly raising the psychological anchor around the market narrative. You might not short a project valued at $1 million, but you might short one valued at $19 billion.
Low Circulating Supply Means Thin Real Liquidity. Tokens that are freely tradable in the market may account for only 5%-15% of the total supply, while the remainder is locked in allocations to teams and investors or subject to future unlock schedules. In any market without sufficient liquidity, only a small amount of capital is needed to move such a limited circulating supply.
Highly Concentrated Ownership Makes Market Control Easy. This can be verified directly through on-chain data. The top 20 addresses, including those associated with project teams, early investors, sniper bots, and affiliated market makers, may collectively hold more than 60% of the circulating supply. These addresses also frequently transfer funds among themselves, suggesting that they effectively belong to the same coordinated group.
When these three characteristics are combined in a token that also has a perpetual futures trading pair on a centralized exchange, the path to manipulation becomes mechanical:
The core of this strategy, itself a product of high FDV and low float, is that every risk management mechanism in perpetual futures, including the mark price, funding rate, and liquidation engine, ultimately begins with the index price. The index price, in turn, is derived from transaction prices in the spot market. When a token’s economic structure makes its spot market inherently vulnerable to manipulation with only a small amount of capital, all the sophisticated engineering on the derivatives side becomes an amplifier. Instead of suppressing manipulation, it magnifies its effects across every participant in the derivatives market.
This form of manipulation is more “structured” than it was during the TRB era in three respects:
First, it is systematic. TRB was a one-off incident, and exchanges changed their rules afterward. But as long as newly issued tokens continue to follow the dominant model of “high FDV, low float, and concentrated ownership,” eligible targets will continue to appear in large numbers, with each one providing a potential venue for manipulation. An exchange may introduce one patch, but the next wave of tokens with the same structure will quickly find another attack path.
Second, it operates across exchanges. Manipulators are no longer confined to the perpetual futures order book of a single exchange. They need to control the spot supply only across the small number of exchanges where a token is traded. The resulting corruption of the index price simultaneously affects every CEX offering perpetual futures on that token, including Binance, OKX, Bybit, Bitget, and Gate. A single spot market manipulation can extract profits across multiple derivatives markets. This cross-exchange effect produces a much higher return per unit of manipulation than strategies targeting only one exchange in the past.
Third, it is more difficult to detect. Manipulators can maintain a relatively low profile in the derivatives market. Unlike in the TRB case, they do not need to hold conspicuously large long positions in the perpetual order book. All the “dirty work” takes place in the on-chain spot market, where the legal boundaries surrounding spot market manipulation remain highly ambiguous under current regulatory frameworks. Such activity can be presented as “organic trading,” “market-making activity,” or “community promotion.” Liquidations in the derivatives market then appear to be the result of “natural market volatility,” with no obvious counterparty and little scope for tracing the activity.
A common misunderstanding needs to be clarified here: this phenomenon is not caused by the product design of any CEX’s “Alpha Zone,” “Innovation Zone,” or “Monitoring Zone.” These products are indeed among the venues where such tokens are concentrated, but shutting down an Alpha Zone would simply cause tokens with the same structure to appear through other listing channels. As long as “high FDV, low float, and concentrated ownership” remains the industry’s dominant issuance model, and as long as centralized exchanges are willing to offer perpetual futures on these tokens, the manipulation will simply move to another venue. The real problem lies not in the exchange’s product format, but in the token’s issuance structure.
For centralized exchanges, this presents an unprecedented challenge. Traditional risk management tools, including price limits, dynamic funding frequency adjustments, funding rate caps, leverage limits, and position limits, all operate on the derivatives side. But the attack vector for this new form of manipulation lies not in the derivatives market, but at the input layer of the index price. No matter how sophisticated the derivatives risk controls may be, they will still become distorted when faced with a systematically corrupted index price.
Binance’s September 2025 adjustment to its mark price algorithm partially addressed this difficult problem. But if the “multiple sources” underlying a multi-source weighted index collapse into only a few sources, or even a single source, for these tokens, the vulnerability at the index level has no clear solution. This exposes a deeper structural contradiction within the CEX perpetual futures system: its sophisticated mechanisms depend on the assumption that the spot market itself is sound and dominated by a sufficiently large number of independent participants. The issuance model behind the current generation of high-FDV, low-float tokens directly violates that assumption.
“Data plays” are the latest scar in the ten-year evolution of perpetual futures. The ultimate solution will not come from minor adjustments to derivatives risk controls. It must come from one of three places: a change in token issuance models, including fairer initial distributions, higher genuine circulating supply, and stricter unlock requirements; a fundamental tightening of listing standards, including refusing to offer perpetual futures on structurally vulnerable tokens; or the migration of derivatives shorting mechanisms on-chain, allowing short positions to act directly against real spot liquidity pools rather than depending on oracles and centralized indexes.
None of these solutions has achieved broad consensus. But one point is already clear: when a token is itself a carefully designed manipulation machine, even the most sophisticated derivatives infrastructure becomes its accomplice rather than its constraint.
Binance’s September 2025 Overhaul of the Underlying Formulas
The “increased frequency plus expanded caps” introduced after TRB represented a patchwork improvement. The ALPACA and MYX incidents demonstrated that patching was no longer sufficient. The formulas themselves had to be reconsidered.
On September 16, 2025, Binance published an announcement titled “Important Updates on Funding Rate Formula and Mark Price Calculation of Futures Contracts,” with the changes taking effect on September 18, 2025. This was the first time since Binance launched perpetual futures that it simultaneously modified both the funding rate formula and the mark price algorithm at the level of their underlying formulas.
Three Generations of Funding Rate Mechanisms:
Unlike previous adjustments, which changed thresholds, caps, or settlement frequencies, this reform altered the calculation logic itself. Its central motivation was a systematic reassessment of the limitations of the first two generations of funding rate mechanisms:
The First Generation, with fixed eight-hour settlements and a +/-0.75% cap, created an arbitrage window for traders to target positions immediately before settlement, while also leaving manipulation windows open for extended periods.
The Second Generation, with dynamic settlement frequency and expanded caps, effectively shortened the duration of extreme deviations but was itself weaponized as a “punitive mechanism.” In TRB’s case, the manipulator actively weaponized the funding rate. In ALPACA’s case, the manipulator used the increased-frequency rules themselves as an additional source of pressure.
The root of the problem was not the severity of the penalty, but the behavior of the funding rate formula itself under extreme market structures. This was the question that the third generation of reforms attempted to address.
As the world’s largest centralized exchange by trading volume, Binance’s formula-level changes effectively carry the power to set industry standards. Previous mechanism reforms led by Binance, including the widespread adoption of stablecoin-margined contracts, the expansion of partial liquidation, and the standardization of dynamic funding frequency adjustments, were each adopted by competitors within months. This dual revision of the underlying formulas is similarly expected to trigger a chain reaction across the industry.
5.Perpetuals for Everything and the Reconstruction of the Pricing Paradigm (2024–2026)
Category Expansion: From BTC Alone to Global Assets
The evolution of assets listed in perpetual futures markets is itself a chronicle of the crypto industry’s changing narratives.
The Ten-Year Expansion of Perpetual Futures Categories:
2016–2019: The BTC and ETH Duopoly. The total number of perpetual futures markets across the industry remained below ten. Exchanges were extremely cautious about offering derivatives on long-tail assets because contracts based on assets with insufficient spot market depth were highly vulnerable to manipulation.
2020–2021: The DeFi-Driven Explosion. As USDT issuance expanded substantially and stablecoin-margined contracts became widespread, standardized USD-based pricing significantly lowered the barriers to trading across different assets. DeFi governance tokens such as AAVE, UNI, and SUSHI, along with tokens from emerging blockchains such as SOL, AVAX, and MATIC, were rapidly listed in perpetual futures markets. The total number of markets across the industry surpassed 500.
2022–2023: Product Expansion During the Bear Market. Although the market was undergoing a deleveraging cycle, intense competition among exchanges caused the pace of new listings to accelerate. Layer 2 tokens such as ARB and OP, various AI-related tokens, and large numbers of meme coins were listed in quick succession. Individual major exchanges began offering 300–400 perpetual futures markets.
2024–2026: Indiscriminate Coverage. Binance expanded its perpetual futures lineup to more than 500 markets, while platforms such as Gate and Bybit moved even more aggressively, increasing their offerings to 800 or even more than 1,000. At the same time, the launch of stablecoin-quoted perpetual futures on gold, such as XAUUSDT, as well as silver and foreign exchange pairs, marked the point at which product expansion formally moved beyond the boundaries of crypto assets.
This cross-market expansion has far-reaching implications. By leveraging their uninterrupted 24/7 clearing capabilities, crypto centralized exchanges have begun to meet the demand for pricing global macro assets during weekends and public holidays. When US stock and foreign exchange markets are closed, any unexpected global macro event can first be reflected in the order books of crypto centralized exchanges. A tool once built for geeks to gamble has now become a critical mechanism for filling the time gaps in global macro asset liquidity.
The Exchange Landscape: Three Reshufflings and the Current Market Structure
Over the past decade, the competitive landscape of the perpetual futures market has undergone three complete reshufflings.
2016–2019: BitMEX Dominated. As the inventor of perpetual futures, BitMEX controlled more than 80% of the derivatives market during this period. Its XBTUSD contract once recorded more than $10 billion in daily trading volume.
2020–2022: Binance Rose as BitMEX Declined. The March 12 crash severely damaged confidence in BitMEX, while the US CFTC’s case against founder Arthur Hayes dealt another critical blow. Binance rapidly rose to the top through its early-mover advantage in stablecoin-margined contracts, lower fees, and stronger liquidity. OKX and Bybit formed the second tier. FTX briefly entered the top three, but its collapse in 2022 removed it from the market entirely.
2023–2026: A Multipolar Competitive Structure Took Shape. According to real-time Coinglass data from April 2026:
Binance remains firmly in first place with a substantial lead. However, the OI-to-trading-volume ratio is also worth examining because it reflects users’ typical holding periods and trading preferences. Binance and OKX have relatively low ratios, at 0.47 and 0.28, respectively, suggesting that their users favor high-frequency, short-term trading. Bybit and Gate have higher ratios, at 0.71 and 0.76, indicating a larger presence of medium- to long-term arbitrage traders and institutional positions. KuCoin’s ratio of 1.80, meanwhile, displays the classic characteristics of “low turnover and high position retention.” Even within the same perpetual futures market, different exchanges attract users with entirely different mindsets and trading styles. (Data: https://x.com/agintender/status/2040411675967553711?s=20)
Bitget’s Alternative Path: Carving Out a Market Through Copy Trading
While Bybit used portfolio margin to attract institutional traders, another exchange took the opposite approach by serving retail users who understood institutional trading strategies the least.
In 2020, Bitget became the first centralized exchange in crypto history to launch Copy Trading. The logic behind the product was remarkably simple: with the click of a button, a novice user could proportionally replicate every position opened, closed, or stopped out by a selected “Master Trader” in their own account. Master Traders received a share of their followers’ profits, followers gained the experience of “earning without the hassle,” and the platform collected trading fees from both sides.
This was not an innovation in risk management, but an innovation in user acquisition. It bypassed a central pain point of perpetual futures: ordinary retail traders did not understand the complex system of index prices, mark prices, funding rates, and partial liquidation, yet they still wanted access to this high-return market. Copy Trading repackaged a highly complex product as a consumer product offering “one-click investing.”
South Korea became the breakout market for this product. It is one of the world’s most retail-driven markets and one of the most receptive to copy-trading products. Historically, Korean stock investors have been enthusiastic about following the real-time trades of market “gurus,” making the culture a natural fit for Copy Trading. Bitget invested heavily in South Korea through localized operations, close partnerships with local KOLs, and carefully managed Korean-language copy-trading rankings. As a result, South Korea became a core market accounting for nearly 6% of Bitget’s global traffic. Public data from August 2025 showed that the number of new copy-trading users in the region had surpassed 100,000. This figure is highly unusual for a global exchange because a single country rarely accounts for such a large share of its users. In Bitget’s case, however, South Korea became that important.
Bitget’s path offers another model. While Binance, OKX, and Bybit dominated the top end of the market through infrastructure and institution-focused strategies, an exchange could carve out its own territory by “translating complex products for people who did not understand them.” From Copy Trading in 2020 to the launch of “CFD Copy Trading” across foreign exchange, gold, and commodities in 2025–2026, Bitget extended this product logic into a much broader range of asset classes.
Competition in the perpetual futures market has never been solely about “whose liquidation engine is faster.” It is also about “who can explain this complex product to a new user.” Bitget bet on the latter and secured its own share of the market.
The Long Arc of OI: Four Orders of Magnitude in Ten Years
Open interest, or OI, is a core indicator of the amount of capital committed to the perpetual futures market. It represents the total notional value of all outstanding contracts and directly reflects how much real capital is “locked” in the market.
Tracing the ten-year trajectory of aggregate OI reveals a clear picture of how the crypto derivatives market has developed:
Aggregate Perpetual Futures Open Interest: A Ten-Year Trajectory (Illustrative Logarithmic Scale)
Four orders of magnitude of growth in ten years. This is more than a numerical change. Open interest of $120 billion means that the amount of capital committed to the perpetual futures market has become comparable to that of some core derivatives products in traditional finance.
The growth curve for daily trading volume has been even steeper. The crypto derivatives market currently records approximately $194 billion in 24-hour trading volume, with perpetual futures accounting for around 93% of the total. Daily liquidations amount to approximately $360 million, while the long-short ratio stands at 49.3%/50.7%. This near-perfect balance supports the existence of the “ceiling” created by institutional basis arbitrage in major assets: substantial amounts of hedging capital help keep long and short positioning relatively balanced across the leading markets.
The Structural Distribution of OI: A Two-Tier Market Under a Power-Law Distribution
Changes in the distribution of OI across different assets provide one of the most accurate barometers of market maturity.
The Ten-Year Shift in the Structural Distribution of OI (Estimated Shares):
This distribution follows a classic power-law pattern. A small number of leading assets account for most OI, while each of the hundreds of long-tail assets represents only a tiny share. Collectively, however, their contribution remains significant.
This structure corresponds perfectly with the “two-tier market.” Institutional capital is concentrated in leading assets such as BTC and ETH, where high liquidity supports basis and funding rate arbitrage. Retail capital is dispersed across long-tail assets for directional speculation. These two worlds operate on the same perpetual futures infrastructure, yet follow entirely different rules of engagement.
Conclusion: Behind Every Parameter Stands a Disaster
Looking back at the ten-year evolution of perpetual futures, a clear pattern emerges: every cog in this machine is a scar left on the market by a specific disaster.
Ten Years of Key Events and Mechanism Evolution: The Complete Picture
Multi-source weighting for index prices: Single-source indexes had previously been manipulated.
EMA smoothing for mark prices: Price wicks had previously been used to hunt innocent traders.
Partial liquidation: All-or-nothing account liquidations had previously caused cascading collapses.
ADL replacing Socialized Clawbacks: Huobi invented the mechanism before BitMEX, while the OKEx 50,000 BTC incident demonstrated the vulnerability of distributing losses indiscriminately among all profitable traders.
Stablecoin-margined contracts replacing coin-margined contracts: The death spiral during the March 12 crash nearly consumed the entire market.
Portfolio Margin: Simply adding together margin requirements wasted too much capital and prevented institutions from entering the market.
Position limits: One trader’s 50,000 BTC position nearly destroyed an exchange.
Dynamic increases in funding settlement frequency: TRB’s extraction of funding payments exposed the dangers of excessively long settlement windows.
The fundamental overhaul of the funding rate formula in September 2025: ALPACA demonstrated that the increased-frequency mechanism itself could be weaponized.
Refined management of delisting transition periods: Delisting announcements had previously become precise signals for launching attacks.
The latest form of “data plays” serves as another warning: no matter how sophisticated derivatives-side risk controls become, they cannot defend against a systematically corrupted spot index when the source of that corruption is the token issuance model itself.
Not one of these parameters is redundant, because behind every parameter stands a disaster that actually happened.
Over ten years, perpetual futures evolved from a toy for geeks into a global pricing machine processing nearly $200 billion in daily trading volume. Their users expanded from crypto punks to Wall Street quantitative funds, while the assets they covered grew from BTC to meme coins and from crypto-native assets to gold and foreign exchange. Every upgrade was accompanied by enormous liquidations and angry users, but every repair made after a crisis left behind another foundation stone.
This is an evolution of crypto financial engineering written with real money and the liquidation losses of countless traders.
It is not finished yet.
May we always approach the market with humility and respect.
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