> **Source:** https://permissionless.fi/en/26-regulation
> From *Permissionless Finance* (Permissionless Finance: From Perpetual Futures to the On-Chain Global Market) by Eric Cheung. Licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).

# Chapter 26: The Economics of Regulation Between Innovation and Stability

In the first quarter of 2024, the average weekday trading volume of Bitcoin perpetual futures (measured as a 30-day rolling average) reached $57.7 billion [1]. That figure reflects perpetual futures' roughly 90% share of the crypto-derivatives market by open interest [2], and it has made them a central concern for financial regulators worldwide. Faced with this large-scale market—one that runs around the clock, spans national borders, and has no central clearinghouse—regulators confront a severe classification dilemma. Perpetual futures represent no ownership claim over any entity and therefore fail to satisfy the core "investment contract" element of the Howey test [3], which makes them difficult to classify simply as securities. At the same time, they have no expiration date and no physical-delivery mechanism, which places them outside the definitional framework of traditional commodity futures [4] and likewise challenges the jurisdiction of the Commodity Futures Trading Commission (CFTC).

The difficulty of classification is merely a surface symptom; the deeper predicament lies in the failure of traditional regulatory tools. Historical experience has shown that a simple, blanket ban cannot eliminate market demand and only invites regulatory arbitrage. Indeed, capital flight was among the regulatory motives well before any ban: Chainalysis estimates that from mid-2019 to mid-2020, more than $50 billion in crypto-assets (of which roughly $18 billion was USDT) moved from East Asian addresses to destinations outside the region, forming an important part of the backdrop to China's comprehensive 2021 ban [5]. After the ban took effect, trading activity migrated rapidly to offshore exchanges, while domestic traders continued to participate through technical workarounds. This outcome indicates that the only substantive consequence of prohibition was to strip regulators of all visibility into the market and any capacity to intervene in it, all without reducing systemic risk. Yet the complete absence of regulation carries equally serious consequences. The November 2022 collapse of the FTX exchange exposed a shortfall of roughly $8 billion in customer funds [6], and millions of users suffered substantial asset losses. This episode demonstrates just how severe information asymmetry and agency moral hazard can become in a "free market" that lacks mandatory asset segregation and external audit.

Regulators therefore can neither force perpetual futures into an ill-fitting traditional framework, nor ignore their existence, nor retreat to a posture of laissez-faire. This predicament raises the central question of the chapter: in the specific context of the perpetual futures market, how should regulation intervene so as to repair the market's defensive deficiencies without destroying its innovative advantages in price discovery and accessibility? Answering this question requires moving beyond a moral or political stance on whether regulation is "good" or "bad" and adopting instead the cost-benefit analytical framework of economics. Regulation is, in essence, a tool for intervening in market failure, and every specific regulatory policy—whether capping leverage, mandating disclosure, or requiring capital segregation—inevitably carries both benefits and costs.

To assess the net effect of these policy tools systematically, this chapter proposes and applies three interrelated analytical frameworks. The five-dimensional regulatory impact matrix evaluates, one by one, the specific effect of each regulatory tool on five dimensions—transaction costs, price discovery, market resilience, fairness, and accessibility—providing a microfoundation for policy comparison. Building on this, the regulatory "impossible trinity" reveals that under a globalized and decentralized technical architecture, no regulatory regime can simultaneously maximize global consistency, innovation-friendliness, and consumer protection, thereby explaining the structural roots of today's fragmented global regulation. That fragmentation, in turn, motivates a paradigm contrast between functional and entity-based regulation, which argues why traditional institution-type regulation is markedly constrained in the face of cross-boundary innovation and prone to regulatory vacuums, and why regulation organized around function and risk characteristics is the more adaptive alternative.

Building on these frameworks, the chapter proceeds to a detailed analysis of the economics of regulation. It first defines four categories of market failure in the perpetual futures market—externalities, information asymmetry, and others—to delineate the legitimate boundaries of regulatory intervention, and it constructs a net-benefit evaluation model that incorporates compliance burdens and innovation suppression. It then sets out an inventory of regulatory targets for perpetual futures, prioritizing systemic risk, market manipulation, consumer protection, and market integrity according to the severity of each risk and the market's capacity for self-repair. On this basis, it dissects the five-dimensional impact of specific regulatory tools such as leverage limits and market-maker obligations, and it examines the economic consequences of the global contest over jurisdiction. Finally, the chapter extends to the regulatory boundaries of decentralized exchanges, exploring the possibility and the technical limits of compliance-by-code. After reading this chapter, readers will be able to step outside the black-and-white debate over regulation, use structured economic tools to assess the true cost of any regulatory proposal, and clearly delineate which market deficiencies can be repaired through legal rules and which must be left to the decentralized engineering discussed in later chapters.

## 26.1 The legitimacy of regulation

The legitimacy of regulatory intervention rests on market failure: when the market mechanism cannot on its own reach a Pareto-optimal allocation, external intervention may improve aggregate social welfare. In the context of the crypto-derivatives market, not every market deficiency constitutes a failure that warrants regulatory intervention. Some deficiencies can repair themselves through competition among protocols or through underlying technological innovation, whereas excessive regulatory intervention may not only impose high compliance costs but also trigger innovation suppression and regulatory arbitrage. Assessing the soundness of a regulatory policy is therefore, in essence, a complex cost-benefit analysis: intervention is legitimate in the economic sense only when the marginal benefit of repairing a market failure exceeds the sum of the regulatory costs.

### 26.1.1 Four categories of market failure

In traditional financial theory, market failure is usually grouped into four basic forms: externalities, information asymmetry, undersupply of public goods, and market power [7]. Within the distinctive microstructure of perpetual futures, these four failures display characteristics quite different from those of traditional assets.

Externalities are the most damaging form of failure in the perpetual futures market, typically manifested as the systemic risk arising from liquidation cascades. When a single trader's over-leveraged position is forcibly liquidated, the liquidation engine's dumping of assets onto the market depresses the price, which in turn triggers the liquidation of additional highly leveraged positions [8]. This positive-feedback loop harms not only the liquidated trader but also imposes the negative externality of evaporating liquidity on all market participants. As illustrated by the October 2025 liquidation cascade detailed in Section 26.2.1, this endogenous fragility constitutes the core rationale for regulatory intervention [9].

Information asymmetry is especially pronounced between centralized exchanges and retail traders. Exchanges hold complete data on order flow, liquidation parameters, and asset reserves, whereas ordinary traders are often unable to assess counterparty risk accurately. The collapse of FTX laid bare the extreme consequences of this asymmetry: management's misappropriation of customer assets went undetected by the market for a long period, ultimately producing billions of dollars in customer losses [10]. This collapse of trust, driven by informational opacity, not only destroyed a single platform but also triggered cross-market financial contagion [11].

The undersupply of public goods manifests in the perpetual futures market as a tragedy of the commons in liquidity under extreme conditions. Liquidity is, in essence, a public resource with positive externalities. In calm markets, market makers earn the bid-ask spread by supplying liquidity; but in periods of high volatility or crisis, market makers, out of their own risk-management considerations, often choose to withdraw their quotes. This individually rational risk-averse behavior produces, at the aggregate level, a collectively irrational and sharp decline in liquidity, further exacerbating price volatility and liquidation risk [12].

Market power arises from the monopolistic position of the leading exchanges. In a market where liquidity exhibits strong network effects, trading volume tends to concentrate on a few large platforms. This market concentration allows the leading exchanges to exercise unilateral pricing power when setting market-maker agreements, fee schedules, and listing standards. Moreover, some exchanges combine the dual roles of matching venue and proprietary market maker, a conflict of interest that, absent external oversight, can readily evolve into an implicit shifting of costs onto ordinary traders.

### 26.1.2 The boundary of self-repair

Identifying a market failure does not mean that regulation must intervene immediately. In crypto markets, many phenomena regarded as defects are in fact improving on their own through market mechanisms. The central criterion for judging whether regulation is necessary is whether the defect has the potential to correct itself naturally through competition or technological evolution.

Competition constitutes a highly effective self-correcting mechanism. Consider transaction costs: as decentralized derivatives protocols have proliferated and competition among centralized exchanges has intensified, the all-in trading cost of perpetual futures—including explicit fees and implicit slippage—has trended steadily downward. This competition-driven efficiency gain sharply reduces the need for direct price controls on fee rates or market-maker spreads. When the market can maximize welfare on its own through competition, forcible regulatory intervention may instead distort price signals.

Technological innovation likewise performs a regulation-substituting function. Early liquidation mechanisms often used a crude, whole-position approach that readily produced severe price shocks. To attract and retain users, however, many exchanges voluntarily introduced gradual liquidation algorithms and more refined risk engines. This technologically driven improvement in resilience demonstrates that, in certain domains, code and protocol rules can constrain high-risk behavior more effectively than traditional administrative directives. In addition, the maturation of cross-market arbitrage has caused many early pricing anomalies to fade, as arbitrageurs, in pursuing profit maximization, in effect perform the function of correcting price deviations.

Regulatory resources should therefore concentrate on the structural failures that the market cannot resolve on its own. The enforcement of asset segregation and the verification of reserve transparency, for example, cannot be achieved through exchanges' self-disciplinary pledges alone; they require external audit and mandatory legal constraints [13]. Conversely, for the micro-frictions that are naturally easing as competition intensifies or technology iterates, regulatory restraint is often the superior strategy.

### 26.1.3 The costs of regulation

Every form of regulatory intervention carries non-negligible costs, and in the crypto-derivatives market these costs are exceedingly complex.

Direct compliance costs are the most visible price of regulation. To satisfy the anti-money laundering (AML), know-your-customer (KYC), and periodic audit requirements of different jurisdictions, exchanges must maintain large legal and compliance teams. Research indicates that the average annual federal regulatory compliance cost per employee across all U.S. industries is approximately $12,800, rising to roughly $14,700 for small firms with fewer than 50 employees [14]. In crypto markets, these high operating costs are ultimately passed on to traders through higher fees or wider bid-ask spreads, directly eroding market accessibility and operational efficiency.

Innovation-suppression costs are a hidden but far-reaching negative effect of regulation. Financial innovation is often born in the gray areas of existing regulatory frameworks. Perpetual futures were themselves invented to circumvent the liquidity fragmentation caused by traditional futures delivery. Had this product been brought under a strict traditional-derivatives regime in its infancy, its distinctive funding-rate mechanism might never have been validated and developed. Surveys of regulation-intensive industries such as finance and utilities find that compliance costs can exceed 2.5% of a firm's total payroll, while the aggregate cost of incremental social regulation is estimated at roughly 5% of U.S. GDP [15]. An excessive compliance and regulatory burden can crowd out the resources firms devote to experimentation and R&D, although the net effect of regulation on innovation remains contested in the literature.

Regulatory-arbitrage costs are especially salient in a globalized, decentralized network environment. When a given country or region imposes stringent leverage limits or entry standards, capital and trading activity migrate rapidly to more lightly regulated offshore platforms. When Japan cut the leverage cap on crypto-asset derivatives sharply from 25x to 2x in 2020, for example, it nominally protected domestic investors but in practice drove large trading volumes to overseas exchanges beyond its jurisdiction (Section 26.7.1 documents this trade-off with policy data). Such regulatory arbitrage not only fails to reduce global systemic risk at its root but also strips the strictly regulating jurisdiction of any real pricing power over, or supervisory capacity within, the market.

Moreover, transplanting rules designed for the traditional financial system directly onto crypto architecture generates enormous friction costs. The non-custodial nature of decentralized exchanges and the logic of automatic smart-contract execution conflict fundamentally with the traditional intermediary-based regulatory paradigm. Forcing decentralized protocols to discharge the obligations of a traditional broker is not only technically difficult but may also fundamentally undermine the permissionless nature of decentralized finance.

### 26.1.4 The net-benefit analysis framework

Building on the preceding analysis, regulatory policy must be formulated on a rigorous cost-benefit framework [16]. The net benefit of a regulatory measure can be formalized as the increase in social welfare from repairing a market failure, minus direct compliance costs, innovation-suppression costs, and the efficiency losses induced by regulatory arbitrage.

Figure 26-1 characterizes the nonlinear relationship between net benefit and regulatory intensity along two dimensions, benefit and cost: the intersection of the two curves marks the critical threshold at which net benefit turns from positive to negative, while the point of maximum vertical distance between them corresponds to the optimal regulatory intensity that maximizes net social welfare.

![Figure 26-1](./images/fig-26-1-en.png)

**Figure 26-1.** The net-benefit analysis framework for regulation

The shapes of the two curves follow from basic regulatory economics. The benefit of repairing market failure rises with regulatory intensity but exhibits pronounced diminishing marginal returns: basic early-stage regulation—such as mandatory disclosure and asset segregation—can sharply reduce systemic risk at relatively low cost. Once regulatory intensity crosses the critical point, however, further intervention such as extreme leverage limits or product bans yields negligible marginal safety benefits, even as compliance and innovation-suppression costs accelerate markedly.

Regulatory-arbitrage costs must be understood along two dimensions. Along the single-jurisdiction regulatory intensity depicted on the horizontal axis of Figure 26-1, arbitrage costs rise monotonically with intensity: the more stringently one jurisdiction regulates, and the larger the rule gap relative to other jurisdictions, the stronger the incentive for capital flight and risk transfer; hence this component is increasing in the figure. Along the dimension of global regulatory coordination, by contrast, arbitrage costs follow an inverted-U shape: under the extreme assumptions of a complete absence of regulation or a perfectly uniform global regime, there is no exploitable rule differential across jurisdictions and thus no room for arbitrage; but in the realistic state where jurisdictions each impose moderate, heterogeneous regulation, the rule differentials across jurisdictions maximize the arbitrage incentive, driving capital flight and risk transfer. This inverted-U shape is a theoretical inference: its peak depends on the degree of rule differential across jurisdictions, and it currently lacks direct empirical calibration.

Regulatory intervention is justified only when the total-benefit curve lies above the total-cost curve—that is, when net benefit is positive. The optimum in the figure indicates the regulatory intensity that maximizes net social welfare. This framework rules out two extreme policy positions: it rejects the complete laissez-faire that ignores the risks of liquidation cascades and asset misappropriation, and it equally rejects the over-regulation that ignores the value of innovation and the native characteristics of crypto. In the regulatory practice of perpetual futures, finding this optimal equilibrium requires policymakers to understand the underlying technical mechanisms thoroughly and to weigh investor protection against the maintenance of market vitality with care.

## 26.2 Regulatory targets and prioritization

The scarcity of regulatory resources demands that intervention be selective. Not every deficiency in the perpetual futures market requires regulatory intervention; the core task is to identify the areas where the marginal benefit of intervention is highest and to prioritize among them. In evaluating each market failure, the market's own capacity for repair must be taken into account, because competitive mechanisms and technological evolution can often resolve some problems endogenously. Regulatory intervention is fully justified in the economic sense only when the market mechanism has entirely failed and the negative externality or information asymmetry causes a significant loss of social welfare. This section systematically reviews four potential regulatory targets in the perpetual futures market—systemic risk, market manipulation, consumer protection, and market integrity—and, based on the severity of the market failure, the market's capacity for self-repair, and the net benefit of intervention in each area, provides an operational framework for prioritization.

### 26.2.1 Systemic risk

Systemic risk is the most prominent source of negative externalities in the perpetual futures market, and its core mechanism is precisely the positive-feedback loop between the forced liquidation of highly leveraged positions and the evaporation of liquidity described in Section 26.1.1. This self-reinforcing liquidation cascade harms not only over-leveraged users but, through liquidity evaporation and price contagion, strikes every participant in the ecosystem—including spot holders who never used leverage. The liquidation cascade of October 10–11, 2025 is an instructive case: within 36 hours, roughly $19 billion of open interest was forcibly liquidated. The event was triggered mainly by a macro-policy shock, but the structural accumulation of high leverage was the fundamental reason this shock escalated into a systemic event [9]. According to Ali's (2025) GARCH-based estimates, cross-asset contagion during the episode was roughly 20% stronger than the spillovers during the 2018 trade war, and the volatility-persistence coefficient ($\alpha+\beta$) approached 0.90, indicating that the effect of the systemic shock was highly persistent [9].

Individual exchanges lack the economic incentive to unilaterally limit systemic risk—a classic prisoner's dilemma. In a highly competitive environment, exchanges tend to offer very high leverage to attract traders seeking high-risk returns. If one platform unilaterally lowers its leverage cap or tightens margin requirements, its market share will quickly flow to more lightly regulated competitors, whether centralized exchanges in other jurisdictions or permissionless decentralized protocols. This leverage arms race causes systemic risk to accumulate across the entire market, while no individual platform bears the full cost of the systemwide damage caused by a liquidation cascade: the negative externality of excessive leverage is externalized to the whole market, whereas its private benefits (trading fees and funding-rate revenue) are internalized by the exchange. This mismatch between costs and benefits is a clear manifestation of market failure and the fundamental reason regulatory intervention is justified.

Regulatory intervention against systemic risk carries a fairly high marginal benefit, but the challenges of implementation are not to be underestimated. By imposing a market-wide uniform leverage cap, dynamic margin requirements, and standardized liquidation mechanisms, regulation can effectively interrupt the transmission path of the positive-feedback loop and markedly improve the market's overall resilience. Such intervention, however, also faces complex trade-offs. Strict leverage limits inevitably reduce capital efficiency, raise traders' implicit costs, and may drive high-leverage demand to unregulated offshore markets or decentralized platforms, producing a regulatory-arbitrage effect. The setting of regulatory parameters must therefore strike a delicate balance between reducing systemic risk and maintaining market liquidity, and the effectiveness of regulatory action by a single jurisdiction will be greatly diminished without international coordination.

### 26.2.2 Market manipulation

Market manipulation systematically undermines market fairness by distorting the price-discovery mechanism and inflating the appearance of liquidity. In the perpetual futures market, manipulation takes more varied forms than in traditional financial markets, and because of the regulatory vacuum, its execution cost is extremely low. One typical pattern is cross-market spot-perpetual manipulation: the manipulator buys the spot asset heavily during periods of concentrated liquidity, pushing up the index price on which the mark price depends and thereby triggering the forced liquidation of a large number of short positions in the contract market; the manipulator then rapidly sells in the opposite direction once the liquidations are complete, profiting from the artificially induced price swing. Empirical research shows that this manipulation pattern leaves identifiable statistical traces in data from major exchanges such as Binance: the price crashes that follow manipulative spikes produce significantly lower subsequent returns, and the position changes of top traders are highly correlated with price movements [17]. This strategy is especially frequent in the less liquid altcoin perpetual futures market, because a thin order book means the manipulator can generate a significant price deviation with relatively little capital.

Wash trading is another pervasive and far-reaching form of manipulation, designed to manufacture a false appearance of market activity through self-trading or offsetting trades between affiliated accounts. A systematic empirical analysis of 29 cryptocurrency exchanges found that wash trading accounts, on average, for more than 70% of the reported volume on unregulated exchanges, with such fictitious volume reaching trillions of dollars annually [18]. Exchanges have strong economic incentives to engage in or tolerate wash trading: inflated volume raises their ranking on third-party data platforms, attracts genuine liquidity providers and institutional clients, and provides stronger bargaining leverage in listing negotiations. The harm of wash trading lies not only in the direct price distortion but, more importantly, in its systematic pollution of the market's information environment. When investors cannot distinguish genuine liquidity from fictitious liquidity, their judgments about market depth and liquidity risk become systematically biased, leading them to make suboptimal investment decisions. Wash trading also provides cover for implicit collusion between market makers and exchanges, making conflicts of interest difficult for outside observers to detect.

Regulators play a critical role in combating market manipulation, but the effectiveness of enforcement depends heavily on their ability to obtain trading data. Although the market's endogenous arbitrage mechanism can dampen price manipulation to some degree, it is often powerless against complex cross-market manipulation and systematic wash trading, because the arbitrageurs themselves may become the injured party of a manipulation strategy. By mandating strict trade surveillance, suspicious-activity reporting regimes, and clear definitions and severe penalties for manipulative conduct, regulation can significantly raise the cost of violations and thereby reduce the frequency of manipulation at the margin. Yet the cross-border nature of crypto markets means that enforcement by a single jurisdiction often runs into the limits of its jurisdictional boundary, which is an important reason the net benefit of regulating market manipulation is partly diluted.

### 26.2.3 Consumer protection

Consumer protection is fundamentally about correcting the information asymmetry among market participants, and in particular about shielding inexperienced retail traders from the disproportionate harm of complex financial derivatives. The mechanism design of perpetual futures contains several elements that are highly opaque to retail participants: the dynamic adjustment of the funding rate, the calculation of the mark price from a multi-exchange index price, the nonlinear liquidation function, and the operating logic of the insurance fund. Most retail traders do not fully grasp the destructive power of these mechanisms under extreme conditions, especially how the multiplier effect of high leverage and volatility can drive initial margin to zero in a short time. The European Securities and Markets Authority's (ESMA) analysis of the contracts-for-differences (CFDs) market shows that 74% to 89% of retail investor accounts lose money in leveraged trading, with average per-investor losses ranging from €1,600 to €29,000 [19]. Although CFDs and perpetual futures differ structurally—in particular, the B-book market-making structure of CFDs differs from the order-book matching model of perpetual futures, so this figure can be treated as an upper-bound estimate of the retail loss rate—the two are highly similar in their leverage effect and their pattern of retail losses, and this figure provides an important reference benchmark for assessing the consumer-protection needs of the perpetual futures market.

In the regulatory design of consumer protection, there is a fundamental clash of values between libertarianism and paternalism, and this divergence has no objective solution at the economic level. The libertarian view holds that adult investors have the right to bear risk on the basis of their own judgment, including the right to sustain financial losses, and that the regulator's responsibility is limited to ensuring adequate disclosure rather than substituting for the investor's decisions. The economic rationale for this position is that mandatory protective measures generate a paternalism cost: they deprive investors of tools for reasonable risk management with derivatives and may push retail participants toward more lightly regulated offshore platforms, thereby reducing, in substance, the protection they receive. The paternalist view argues that, given retail participants' inherent limitations in cognitive capacity, risk tolerance, and access to information, market outcomes do not truly reflect their preferences, and that mandatory measures must therefore restrict their participation in high-risk trading even at the cost of their formal freedom to invest. This chapter takes no position, but it notes that this divergence directly shapes the choice of regulatory tools—from mere risk warnings to strict accredited-investor entry standards and tiered leverage regimes.

The behavioral-economics framework of the "nudge" offers a third path beyond this binary opposition [20]. The core idea of a nudge is to guide decision-makers toward better outcomes by altering the choice architecture without prohibiting any option. Applied to the perpetual futures market, regulators can design a set of non-coercive interventions. For example, they can set the default leverage on the trading interface to a low level (such as 5x); users can still raise it manually, but the default effect significantly lowers a novice trader's initial risk exposure. As another example, before a user submits a high-leverage order, they can be required to complete a visual simulation of liquidation risk, so that they intuitively understand the probability distribution of having margin wiped out under extreme conditions. As a further example, a pre-trade cooling-off period can be introduced, imposing a brief delay on newly opened high-leverage positions during periods of extreme volatility to curb emotionally driven impulsive trades. These measures respect the trader's right to autonomous choice while using behavioral intervention to reduce the systematic losses caused by cognitive biases, thereby opening a pragmatic middle ground between libertarianism and paternalism.

The economic trade-offs of implementing consumer protection are especially pronounced, which is the main reason it ranks last in the prioritization. Strengthening disclosure is the lowest-cost intervention and can effectively reduce information asymmetry without directly interfering in market operation, but its actual effect is severely limited by retail participants' attention and comprehension. More aggressive measures—such as sharply limiting retail leverage or outright banning retail participation in certain products—can directly reduce retail financial losses, but they also sharply reduce market accessibility and may drive demand toward regulatory vacuums. Consumer-protection regulation therefore needs to be carefully calibrated between preventing exploitation and preserving market openness, and its net benefit depends to a large extent on the regulator's value preferences rather than on pure economic calculation.

### 26.2.4 Market integrity

Market integrity is the foundation on which any financial system exists, and its core requirement is the safety of customer assets and the transparency of intermediary operations. If an exchange can arbitrarily misappropriate customer assets without oversight, then any rule design at the trading level and any optimization of market microstructure become meaningless, because users' fundamental interests have already been violated at the most basic level. The collapse of FTX is the definitive cautionary case for the cryptocurrency market. The CFTC's complaint states that the platform entirely failed to implement basic corporate controls, failed to segregate customer assets from its own funds and from the funds of affiliated entities, and failed to keep proper records of intercompany fund flows [21]. The CFTC's 2022 complaint found customer deposit losses at FTX exceeding $8 billion; in August 2024, the Commission further obtained a court-approved monetary-relief judgment of approximately $12.7 billion (about $8.7 billion in restitution to customers and victims and about $4 billion in disgorgement and penalties) [21]. This episode reveals a structural loophole: in the absence of mandatory asset-segregation requirements, the moral hazard of centralized exchanges is systemic rather than incidental.

The proof-of-reserves mechanism that the industry has explored on its own attempts to prove an exchange's asset solvency through cryptographic means, but it has fundamental limitations as a safeguard of market integrity. Proof-of-reserves systems focus mainly on verifying the existence of on-chain assets, yet they often cannot reveal, fully or in real time, an exchange's hidden liabilities and complex off-balance-sheet leverage [22]. Specifically, proof of reserves can show that an exchange controls certain wallet addresses, but it cannot prove that those assets have not been secretly pledged to third-party lenders, nor that the exchange holds no hidden short positions established through derivatives. This incomplete transparency not only fails to prevent the covert misappropriation of assets but may even mislead investors by providing a false sense of security, causing them to form overly optimistic judgments about the exchange's actual solvency. Relying solely on technical means and industry self-discipline therefore cannot fully resolve the moral hazard of centralized intermediaries; it must be supplemented by legally binding external oversight.

Mandatory asset segregation and external audit are the core means of safeguarding market integrity. Regulators must require perpetual futures exchanges to maintain minimum capital to absorb operating losses, to enforce strict physical and legal segregation between customer assets and proprietary assets, and to undergo regular, comprehensive audits by independent third parties, with the audit scope extending to off-chain liabilities and related-party transactions. The compliance cost of this kind of regulatory intervention is relatively manageable—consisting mainly of audit fees and the cost of tied-up capital—but its benefit in averting a multibillion-dollar disaster is enormous. More importantly, safeguarding market integrity has significant positive externalities: when investors have full confidence in an exchange's solvency, the liquidity and participation of the entire market improve.

### 26.2.5 Prioritization

Based on the net-benefit analysis framework, we can construct a systematic prioritization of the four regulatory areas above. This ranking depends not only on the severity of the market failure but must also weigh the market's capacity for self-repair and the expected net benefit of regulatory intervention. By structuring these dimensions, we can clearly identify the optimal allocation of regulatory resources and provide a theoretical basis for regulators' decisions under resource constraints.

Table 26-1 provides a systematic prioritization of the four regulatory areas along three dimensions: the severity of the market failure, the market's capacity for self-repair, and the net benefit of regulation. Market integrity is placed in the first priority. Its extremely high failure severity has already been demonstrated by the FTX episode discussed above (Section 26.2.4), and the market is entirely unable to guarantee the safe segregation of assets on its own in the absence of external compulsion. Because the compliance cost is relatively low and the intervention effectively prevents catastrophic outcomes, its net regulatory benefit is extremely high. Moreover, safeguarding market integrity has a foundational status: the other regulatory objectives are meaningful only once the safety of customer assets is assured.

Systemic risk follows in the second priority. Although its severity is slightly lower than that of a market-integrity failure, the market lacks any mechanism to reduce risk on its own because of the prisoner's dilemma created by the leverage arms race. Intervention against systemic risk can significantly improve market resilience and prevent the negative externality of a liquidation cascade from harming innocent participants, so its net benefit is likewise considerable. However, the effectiveness of systemic-risk regulation depends heavily on international coordination, and unilateral action may produce a regulatory-arbitrage effect, which to some extent dilutes its net benefit.

Market manipulation ranks third. Although price distortion and wash trading severely undermine fairness, the presence of arbitrage mechanisms can constrain the space for manipulation to some degree, and as the market matures, the profit margin of some manipulative behavior is narrowing naturally. Regulatory intervention in this area is necessary, but its net benefit is diluted by high enforcement costs owing to the complexity of cross-market and cross-jurisdictional enforcement. Consumer protection is placed fourth. Although retail participants face systematic losses in leveraged trading, the information-asymmetry problem has some room for self-improvement as market education spreads and information transparency increases. More importantly, consumer-protection measures often stand in direct negative trade-off with market accessibility, and their net benefit depends to a large extent on the regulator's value preferences rather than on pure economic calculation.

| Regulatory area | Market-failure severity | Capacity for self-repair | Net regulatory benefit | Priority |
| :--- | :--- | :--- | :--- | :--- |
| Market integrity (asset segregation) | Very high (FTX: ~$8 billion in customer losses) | Very low (moral hazard cannot self-eliminate) | Very high | First |
| Systemic risk (leverage / liquidation) | High (cascade losses can reach tens of billions of dollars) | Low (arms race creates a prisoner's dilemma) | High (subject to international coordination) | Second |
| Market manipulation (wash trading / cross-market) | Medium to high (wash trading exceeds 70%) | Medium (arbitrage partly corrects; market is maturing) | Medium (enforcement costs are high) | Third |
| Consumer protection (information asymmetry) | Medium (74–89% of retail accounts lose money; based on ESMA CFD data, an upper-bound estimate for perpetuals) | Medium (information transparency is improving) | Medium (largest trade-off; value-dependent) | Fourth |

**Table 26-1.** Prioritization matrix for regulating the perpetual futures market (Data source: constructed by the author)

This prioritization points to an important economic insight: in regulating the perpetual futures market, basic, innovation-neutral institution-building—such as asset segregation and financial audit—often yields the highest net benefit. Such regulatory measures require neither complex technical knowledge nor fine calibration of market microstructure, and their core logic is entirely consistent with the basic principles of traditional financial regulation. Conversely, the interventions that intuitively attract the most public attention—such as directly limiting retail leverage or banning specific products—have more complex economic consequences, accompanied by the largest unintended side effects and value controversies. A rational regulatory framework should therefore first shore up the foundation of market integrity and then extend gradually to the regulation of systemic risk and market conduct. This inside-out, foundation-to-complexity regulatory path is consistent both with the economic principle of net-benefit maximization and with the historical experience of the evolution of traditional financial regulation.

## 26.3 The regulatory toolbox

Having identified the failure areas in the perpetual futures market that require regulation and their priorities, the core challenge facing regulators is how to choose the appropriate policy tools. Every regulatory intervention not only generates direct compliance costs but also systematically alters the market's microstructure, thereby profoundly affecting market quality. This section provides an economic evaluation of four categories of core policy in the regulatory toolbox, using the five-dimensional market-quality model introduced in Chapter 25 (transaction costs, price discovery, resilience, fairness, and accessibility) to analyze systematically which dimensions these tools improve and on which dimensions they produce unavoidable side effects.

### 26.3.1 Leverage limits

Capping the maximum leverage on perpetual futures is the most intuitive response of regulators facing systemic risk. Absent external intervention, the crypto-derivatives market—whether centralized exchanges or decentralized protocols—generally offers extremely high leverage (often as high as 100x to 125x) to attract retail traders seeking high-risk returns [23]. This high-leverage environment, however, greatly increases the probability of liquidation cascades, allowing a single trader's insolvency to spread rapidly to the entire market through the automatic-liquidation mechanism and trigger liquidity evaporation and a price collapse. Regulators therefore generally favor cutting the leverage cap sharply, for example limiting it to the range of 20x to 50x.

Leverage limits have their most pronounced positive effect on market resilience. When the maximum leverage is forcibly reduced, traders must post a higher proportion of initial margin, which directly increases the thickness of a position's buffer. When the market faces sharp volatility, a thicker margin buffer can effectively delay the triggering of liquidation, thereby breaking the vicious circle within the liquidation-price-liquidity positive-feedback loop in which falling prices trigger liquidations and liquidations in turn push prices lower still. This intervention, in essence, provides a public good for the entire market—systemic resilience against extreme shocks—by weakening individuals' capacity to take on excessive risk. At the same time, leverage limits improve market fairness to some degree, because they protect the retail traders who lack risk-management experience and are prone to the temptation of extreme leverage from severe losses [24].

This improvement in resilience, however, comes at the cost of market accessibility. When leverage is strictly limited, traders with smaller capital must commit more funds to establish a position of the same size, which in effect raises the barrier to market entry and excludes some participants. In addition, transaction costs are affected negatively. Although the explicit fee rate does not change, the reduction in capital efficiency means traders must leave more funds idle as margin, and this opportunity cost constitutes an implicit trading friction. Price discovery, meanwhile, remains relatively neutral in this process, because leverage limits mainly affect position size and do not directly impede the incorporation of new information into prices.

Figure 26-2 uses the leverage cap (2x to 125x) as its parameter axis, with the left and right panels tracking the improvement in market resilience and the loss of accessibility, respectively: when leverage is lowered from 125x to 50x, the resilience gain is substantial while the accessibility loss is limited; compressing it further below 10x flattens the marginal resilience gain but sharply accelerates the deterioration in accessibility, and the sweet spot marked jointly by the two panels (50x) is the core zone of the policy trade-off.

![Figure 26-2](./images/fig-26-2-en.png)

**Figure 26-2.** Parameter-sensitivity analysis of leverage limits

More complicated still, leverage limits face a serious risk of regulatory arbitrage in implementation. If a strict leverage cap is imposed within a single jurisdiction alone, traders demanding high leverage will quickly move to offshore exchanges or decentralized platforms. Japan's 2020 policy of cutting the leverage cap from 25x to 2x shows that overly stringent limits lead to a large-scale outflow of trading volume, so that the regulator instead loses its capacity to monitor the market (Section 26.7.1 documents this trade-off with policy data from Japan's Financial Services Agency (FSA)) [25]. The net effect of leverage limits therefore depends heavily on how the parameter is set: too loose (such as 100x) fails to guard effectively against liquidation cascades, whereas too strict (such as 2x) triggers destructive regulatory arbitrage, and a moderate limit of around 50x may be the better compromise between resilience and accessibility.

### 26.3.2 Disclosure and transparency

Unlike leverage limits, which directly intervene in market trading behavior, disclosure and transparency requirements are a non-intrusive regulatory tool. This kind of policy does not prohibit any particular business model or product structure but instead mandates that exchanges publicly disclose key information about their internal operations, including the state of asset reserves, the summary terms of market-maker agreements, liquidation parameters and mark-price algorithms, and any conflicts of interest arising from proprietary market-making. The core of this regulatory philosophy is that, by eliminating information asymmetry, market participants can price risk on the basis of full information, so that the market mechanism itself spontaneously penalizes platforms that take excessive risk or act in bad faith.

Judged against the same five dimensions, the most direct and significant contribution of disclosure requirements is to improve market fairness. As described in Section 26.1.1, the information gap between exchanges and retail participants leaves ordinary users in a state of blind trust regarding core data such as order flow, liquidation logic, and market-maker privileges [26]. Mandatory disclosure of market-maker agreements and proprietary-trading positions can effectively curb platforms' use of their informational advantage for insider trading or market manipulation, ensuring that all participants stand on an equal footing at the level of the rules. In addition, greater transparency in the liquidation mechanism also helps improve the efficiency of price discovery, because market participants can more accurately anticipate the system's response under extreme conditions and thus make more rational pricing decisions.

The direct impact of disclosure policy on the dimensions of resilience, transaction costs, and accessibility is relatively neutral. It does not directly change the economic cost of trading, nor does it raise the barrier to market entry. In the long run, however, greater transparency can strengthen public trust in the market and reduce participants' concerns about credit risk, and this decline in the trust premium may translate indirectly into lower implicit transaction costs. At the same time, under market stress, a transparent picture of asset reserves can effectively prevent an irrational, panic-driven bank run, providing psychological support for market resilience.

Although disclosure is regarded as the lowest-cost regulatory tool with the smallest side effects, its effectiveness faces one key limitation: the disclosure itself must be truthful and verifiable. The limitations of proof of reserves (see Section 26.2.4—it can prove on-chain assets but cannot reveal off-chain liabilities and off-balance-sheet leverage [22]) are a case in point. Before its collapse, FTX also presented seemingly healthy financial statements to investors and venture-capital firms, but this independently unverified information ultimately proved to be gravely inaccurate. Disclosure therefore translates into effective market transparency only when it is combined with strict external audit and legal liability; otherwise it may merely produce a false sense of security.

### 26.3.3 Market-maker obligations

Liquidity is the foundation on which the perpetual futures market keeps running, and market makers are the core force supplying it. In an unregulated crypto market, most market makers operate on a voluntary liquidity-provision model that is highly flexible but leads them, when the market suffers an extreme shock, to withdraw en masse out of rational individual risk-management considerations—producing the tragedy of the commons in liquidity described in Section 26.1.1, in which individually rational risk-averse behavior causes liquidity to evaporate instantly at the aggregate level, aggravating one-sided crashes and liquidation cascades [12]. To address this undersupply of a public good, regulators typically introduce a designated-market-maker regime.

The core logic of the designated-market-maker regime is the "parity of rights and obligations." The exchange grants specific market makers privileges such as fee rebates, dedicated API channels, or lower latency; in exchange, these market makers must bear explicit liquidity-provision obligations. These obligations typically include maintaining minimum order depth within a specified price band, adhering to a maximum bid-ask spread, and meeting minimum uptime requirements. More critically, regulation requires that these obligations remain in force even under "abnormal market conditions" and cannot be waived at will simply because volatility has intensified [27].

Market-maker obligations, by contrast, are aimed mainly at improving market resilience. By requiring core liquidity providers to maintain quotes in times of crisis, the market can retain a minimal capacity to absorb selling pressure under extreme conditions, avoiding a disorderly price collapse. At the same time, this regime improves market fairness, because it makes public and standardizes the private incentive agreements that were originally hidden between exchanges and market makers, eliminating opaque interest arrangements.

The introduction of market-maker obligations, however, inevitably has a negative impact on transaction costs. When market makers are compelled to provide liquidity under extreme conditions, they face significant adverse-selection risk and inventory-devaluation risk. To compensate for this potential extreme loss, market makers must widen their bid-ask spreads under normal conditions, passing the cost of bearing the obligation on to ordinary traders. Moreover, the design of this regime faces a difficult balancing challenge: how to define "abnormal market conditions." If the definition is too broad, market makers can easily trigger the exemption clause, rendering the obligation a dead letter; if it is too strict, market makers may, in a genuine systemic crisis, suffer losses beyond their capital capacity and ultimately go bankrupt. Once a core market maker fails, it not only cannot provide liquidity but, as a large defaulting counterparty, further aggravates the market's systemic risk.

### 26.3.4 Capital requirements and asset segregation

If leverage limits and market-maker obligations address risks at the trading level, then capital requirements and asset segregation strike directly at the core of an exchange's governance structure. The misappropriation of FTX customer assets described in Section 26.2.4 shows that when an exchange's internal governance fails completely, any discussion of liquidation-engine efficiency or order-book depth loses its meaning [28]. In the post-FTX era, therefore, establishing strict capital-adequacy standards and a customer-asset-segregation regime has become the top-priority agenda for regulators worldwide.

Capital-requirement policy stipulates that an exchange must hold a certain proportion of its own funds as a buffer to absorb operating losses, technical failures, or cyberattacks. This is analogous to the Basel Accords framework in traditional banking, which aims to ensure that financial institutions have sufficient solvency when facing unexpected shocks. Asset-segregation requirements are more direct still: they mandate that an exchange strictly separate customers' deposited funds from the platform's own operating funds at the legal and physical levels, and they prohibit the exchange from using customer assets for proprietary trading, staking and lending, or as collateral [29].

Capital requirements and asset segregation deliver their largest gains on the resilience and fairness dimensions. Asset segregation fundamentally cuts off the exchange's path to misappropriating customer funds, eliminating the possibility of a systemic collapse triggered by internal moral hazard on the platform. This not only protects the absolute safety of customer assets but also restores participants' basic trust in centralized trading infrastructure, greatly strengthening the market's resilience against endogenous risk. At the same time, higher capital requirements ensure that an exchange has sufficient own funds to meet its payout obligations under extreme market stress, preserving the fairness of trade settlement.

The distinctive feature of this regulatory intervention is that its enormous benefits come with relatively limited negative side effects, concentrated mainly on accessibility. It does not interfere with traders' leverage choices or change the microstructure of the order book, so it has no direct effect on price discovery or transaction costs. The only dimension that may be slightly affected is market accessibility. Strict capital-adequacy standards and regular external-audit requirements substantially raise the fixed cost of opening and operating a cryptocurrency exchange, which may squeeze some smaller, less well-capitalized platforms out of the market and increase industry concentration. From the perspective of protecting investors, however, eliminating the marginal platforms that cannot provide basic safety guarantees is itself the intended outcome of regulatory selection, and this reduction in accessibility is an acceptable cost in the overall welfare analysis.

### 26.3.5 The five-dimensional impact matrix

Through the analysis of the four categories of core regulatory tools above, we can clearly see that no single policy can resolve all market failures at once. Every intervention aimed at repairing a specific market failure triggers a chain reaction in the complex market ecosystem, improving certain quality dimensions while inevitably causing friction or loss on others. Table 26-2 compresses these complex trade-offs into a five-dimensional impact matrix of regulatory tools, to facilitate comparison of the net effects of different policies.

Table 26-2 evaluates, one by one, the direction and intensity of the impact of seven categories of regulatory tools along five dimensions: transaction costs, price discovery, resilience, fairness, and accessibility. In the table, an upward arrow (↑) denotes improvement on that dimension, a downward arrow (↓) denotes deterioration, and a rightward arrow (→) denotes roughly no change, with the number of arrows representing the magnitude of the impact. This standardized scoring framework makes horizontal comparison across policies immediately clear and also reveals the unavoidable trade-offs each intervention entails across the dimensions. Of these, the two tools of mandatory KYC/AML and an outright trading ban are not treated separately in the preceding subsections; their five-dimensional scores are based on their typical effects in the discussions of jurisdiction and anti-money laundering (see Sections 26.4.2 and 26.6.2): the former trades accessibility for gains in legitimacy and fairness, while the latter, by driving trading underground, produces negative effects on most dimensions.

| Regulatory tool | Transaction costs | Price discovery | Resilience | Fairness | Accessibility | Net assessment |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| Leverage limit (to 20x) | ↑ | → | ↑↑↑ | ↑ | ↓↓ | Very large trade-off; highly prone to regulatory arbitrage |
| Leverage limit (to 50x) | → | → | ↑↑ | ↑ | ↓ | A better compromise; balances resilience and accessibility |
| Disclosure and external audit | → | ↑ | → | ↑↑ | → | Positive net benefit; very low cost; strongly recommended |
| Market-maker obligations | ↑ | → | ↑ | ↑ | → | Moderate net benefit; highly dependent on the design of exemption clauses |
| Capital requirements and asset segregation | → | → | ↑↑ | ↑↑ | ↓ | Very high net benefit; a core tool against severe systemic risk |
| Mandatory KYC/AML | ↑ | → | → | ↑ | ↓↓ | Large trade-off; touches on the decentralization values of crypto markets |
| Outright trading ban | N/A | N/A | N/A | N/A | ↓↓↓ | Negative net benefit; drives the market underground; counterproductive |

**Table 26-2.** Five-dimensional market-quality impact matrix of the regulatory toolbox (Data source: constructed by the author)

This matrix distills a core insight of regulatory economics: excellent regulatory design does not seek perfect improvement on every dimension but instead, on the basis of a deep understanding of a policy's side effects, chooses the tool combination that "maximizes net benefit" or "keeps side effects most manageable." For example, although capital requirements and asset segregation slightly reduce accessibility, their enormous benefit in preventing an FTX-style disaster makes them a primary policy. Conversely, although an extreme leverage limit (such as 2x) can significantly improve resilience in theory, its severe damage to accessibility and the regulatory arbitrage it triggers often make it a failed policy in practice. The core of regulatory design lies in finding, on this multidimensional trade-off frontier, the equilibrium point best suited to the market's current stage of development.

## 26.4 The jurisdiction problem

The global, decentralized character of perpetual futures raises a question thornier than how to regulate them: who regulates. Regulatory jurisdiction in traditional financial markets rests on the principle of territoriality and on entity registration, and a regulator holds exclusive jurisdiction over financial activity within its sovereign borders. The servers of a perpetual futures trading platform, however, may be deployed across multiple jurisdictions, the core development team may be distributed around the world, and liquidity providers and traders connect from everywhere via the internet. This borderless technical architecture conflicts fundamentally with a legal framework based on sovereign borders. The fragmentation of global regulation is not the incidental result of regulators' lack of willingness to cooperate but reflects a structural contradiction: global consistency, innovation-friendliness, and consumer protection cannot all be achieved at once.

### 26.4.1 The impossible trinity

The formulation of international financial-regulatory policy is subject to a structural trade-off framework that can be formalized as the regulatory "impossible trinity." This concept derives from the classic macroeconomic theory that a fixed exchange rate, free capital mobility, and independent monetary policy cannot all be achieved simultaneously [30]. This framework is not a strict mathematical impossibility theorem but an analytical tool that reveals the structural tension among policy objectives. In the context of regulating crypto-asset derivatives, the three vertices of the triangle are global consistency, innovation-friendliness, and consumer protection. Global consistency means that countries implement uniform regulatory standards to eliminate cross-border arbitrage space; innovation-friendliness means reserving sufficient room for experimentation for emerging technologies and business models; and consumer protection means reducing retail investors' risk exposure through entry standards, disclosure, and leverage limits. The mutual exclusivity among the three arises from resource constraints and incentive incompatibility: when the international community pursues global consistency and consumer protection at once, it must formulate and enforce strict uniform standards, which inevitably compresses the room for each country to experiment with locally tailored innovation. When global consistency and innovation-friendliness are prioritized together, by contrast, countries can agree only on a low standard, and the strength of consumer protection is necessarily sacrificed.

Figure 26-3 shows the inherent conflict among these three policy objectives: pursuing global consistency and consumer protection simultaneously requires the enforcement of strict uniform standards, which suppresses early-stage technological innovation in lightly regulated jurisdictions—Europe's mature financial infrastructure can still bear the strict compliance costs, but fintech firms in emerging-market countries may be forced to abandon innovation projects as a result; whereas pursuing global consistency and innovation-friendliness simultaneously can only reach consensus on a loose minimum standard, which cannot provide effective consumer protection and may allow systemic risk and market manipulation to spread.

![Figure 26-3](./images/fig-26-3-en.png)

**Figure 26-3.** The regulatory "impossible trinity"

Faced with this impossible trinity, national regulators can only choose to compromise among the three objectives. The choice in reality is usually to give up global consistency and instead seek a balance between innovation-friendliness and consumer protection according to a country's own economic-development strategy and financial-stability concerns. This policy choice, grounded in sovereign autonomy, directly produces the inconsistency of global rules. The current regulatory fragmentation is therefore an inevitable product of structural constraints, and each country's or region's different position in the triangle reflects its different pricing of the benefits and risks of financial innovation.

From an economic perspective, this trade-off reflects different countries' different valuations of the benefits and risks of innovation. Developed economies generally have stronger financial-regulatory capacity and investor-protection mechanisms and can therefore bear higher innovation risk. By contrast, some developing countries may face more severe financial-stability challenges and therefore tend to adopt a more conservative stance. In addition, each country's industrial policy also influences its regulatory choice. Countries that hope to attract fintech talent and firms may choose a more relaxed regulatory environment, whereas those that rely mainly on traditional financial institutions may take a more cautious attitude toward emerging technologies.

### 26.4.2 The global regulatory map

Based on their different trade-offs within the impossible trinity, the world's major economies have taken sharply different policy stances on regulating perpetual futures. This divergence of stances is not a simple binary opposition but forms a continuous spectrum from outright prohibition to active embrace. On this spectrum, the policy choices of different jurisdictions determine not only their share of the global crypto-derivatives market but also significantly affect the geographic distribution of trading activity.

Figure 26-4 depicts the current spectral distribution of global regulation. At the far left of the spectrum are the jurisdictions that adopt outright prohibition. China imposed a strict ban on cryptocurrency trading in 2021, aiming to sever completely the link between crypto-assets and the fiat-currency system in order to guard against capital flight and financial risk. Empirical research shows, however, that the enforcement effect of this extreme policy is limited: trading activity did not disappear but shifted to offshore platforms through intermediaries such as stablecoins, and Chinese investors continue to exert significant influence on Bitcoin price formation [31]. This finding carries an important policy implication: even the strictest regulatory measures cannot fully halt trading activity and may instead cause regulators to lose visibility into and control over that activity.

To the right of the prohibition end are the jurisdictions that impose strict regulation. Japan's FSA strictly limits the leverage cap on crypto-derivatives to 2x, and this extremely conservative consumer-protection measure forces traders seeking high leverage toward unrestricted overseas platforms, thereby weakening the domestic regulator's influence and the competitiveness of Japan's fintech industry (Section 26.7.1 documents this trade-off with FSA policy data).

![Figure 26-4](./images/fig-26-4-en.png)

**Figure 26-4.** The global regulatory map and policy spectrum

The middle of the spectrum comprises the regions that attempt to build comprehensive frameworks. Through the Markets in Crypto-Assets (MiCA) regulation, the European Union established the world's first cross-national comprehensive regulatory framework; although the regulation targets mainly spot markets and stablecoins, it provides a foundational classification and entry standard for derivatives regulation. The core feature of the MiCA framework is that it establishes uniform EU market-access rules, allowing a crypto-asset service provider licensed in one member state to provide services in other member states. This "single passport" mechanism substantially lowers cross-border compliance costs but also requires all participants to comply with relatively strict consumer-protection standards. The United States, by contrast, is in a state of functional-regulatory divergence: the U.S. Securities and Exchange Commission (SEC) and the CFTC have a long-standing dispute over jurisdiction of crypto-derivatives, and this enforcement-based rather than legislation-based regulatory model brings extremely high uncertainty, which has in effect entrenched the market dominance of offshore exchanges. The U.S. divergence reflects a deeper problem: different regulators may have different classificatory understandings of the same category of financial product, creating opportunities for regulatory arbitrage.

At the right end of the spectrum are the jurisdictions inclined toward innovation-friendliness. The Monetary Authority of Singapore (MAS) combines a regulatory sandbox with a licensing regime, attempting to strike a balance between attracting fintech innovation and guarding against money-laundering risk. The MAS framework allows qualified firms to test new products and services in a restricted environment while maintaining basic consumer protection. The advantage of this approach is that it can provide space for innovation without entirely abandoning regulation. Dubai's Virtual Assets Regulatory Authority (VARA) offers a more light-touch regulatory framework, attracting a large number of crypto firms through clear and flexible rules. VARA's success lies in providing clear legal status and relatively low compliance costs, which has led many global crypto firms to establish regional headquarters in Dubai. At the far right of the spectrum, certain offshore jurisdictions impose almost no substantive regulation on crypto-derivatives; they offer the highest degree of freedom to innovate and the lowest compliance costs but also entirely abandon consumer protection.

### 26.4.3 The economic consequences of fragmentation

The significant differences in global regulatory policy directly give rise to regulatory arbitrage. Regulatory arbitrage refers to market participants exploiting the inconsistency of rules across jurisdictions to shift business or trading activity to the regions with the lowest compliance costs and the fewest restrictions. In the perpetual futures market, this arbitrage takes three main forms: arbitrage of exchange domicile, circumvention of users' geographic location, and liquidity fragmentation. Arbitrage of exchange domicile means that an exchange chooses to register in the most lightly regulated region and then provides services to users worldwide via the internet. Circumvention of users' geographic location means that users employ technical means such as VPNs to bypass geographic restrictions and access trading platforms banned in their home country. Liquidity fragmentation means that, because of regulatory restrictions, trading liquidity is dispersed across multiple platforms, resulting in insufficient liquidity in the global market.

When a country imposes strict regulation, the direct consequence is often not the elimination of high-risk trading but the loss of jurisdiction over it. The migration of trading volume to offshore platforms after China's 2021 ban, described in Section 26.4.2, is a paradigmatic case of regulatory arbitrage causing a country to lose its regulatory capacity [31]: the effectiveness of regulation depends not only on the strictness of the rules but, more importantly, on their enforceability. This substantive regulatory failure instead increases systemic risk, because regulators cannot obtain trading data or conduct risk monitoring.

A deeper problem triggered by regulatory arbitrage is the loss of global market efficiency. The Financial Stability Board's (FSB) assessment report notes that significant gaps and inconsistencies in the implementation of crypto-asset regulation are undermining the interconnectedness of the global financial system [32]. At the level of micro-market structure, this fragmentation manifests as a pricing-island effect. Because of compliance requirements, fiat on- and off-ramp restrictions, and region-specific trading bans, the funds and positions of cross-market arbitrageurs cannot flow freely between exchanges in different jurisdictions. The blocking of arbitrage paths allows cross-market price differences—which should converge instantly—to persist, reducing the overall efficiency of price discovery in the global market. For example, if the perpetual futures price on a European exchange differs significantly from that on an Asian exchange, traditional arbitrageurs should eliminate the difference by buying in the low-price market and selling in the high-price market. But if the European exchange is prohibited from serving Asian users, or the Asian exchange is prohibited from serving European users, this arbitrage mechanism breaks down and the price difference may persist for a long time.

Moreover, regulatory fragmentation may trigger a race to the bottom. To attract the tax revenue, employment, and technology spillovers that crypto firms bring, some jurisdictions may face political pressure to lower their regulatory thresholds. If this competition evolves into a scramble to relax standards, the level of consumer protection worldwide will decline overall. When large numbers of retail investors conduct high-leverage trading on offshore platforms that lack asset-segregation and disclosure requirements, systemic risk is not reduced by some countries' strict regulation but instead becomes harder to monitor and guard against, because risk concentrates in opaque regions. This phenomenon has precedents in traditional finance as well: in certain historical periods, some countries competed to loosen regulatory standards in order to attract financial institutions, which is thought to have aggravated the subsequent fragility of the financial system.

### 26.4.4 The path to coordination

Faced with the economic costs of regulatory fragmentation, establishing some form of international coordination mechanism becomes an inevitable choice. Because of the structural constraint of the impossible trinity, however, pursuing a fully unified global regulatory framework is unrealistic in the short term. A more feasible path is to seek a compromise between core consensus and regional differences through bilateral mutual recognition and the setting of minimum standards.

Bilateral mutual-recognition agreements are an effective mechanism for lowering cross-border compliance costs. When the regulatory objectives and rule intensity of two jurisdictions are sufficiently close, they can mutually recognize each other's regulatory licenses. This means that a perpetual futures exchange licensed in one country can legally operate in another without reapplying. This mechanism can locally alleviate liquidity fragmentation without requiring global uniformity. The precondition for implementing bilateral mutual recognition, however, is that both sides must be highly consistent on core issues such as asset segregation, anti-money laundering, and the prevention of market manipulation. Successful examples of such agreements include the financial-services passport regime within the European Union, which allows a financial institution licensed in one member state to provide services in other member states, substantially lowering the cost of cross-border financial services.

At the multilateral level, setting international minimum standards is key to preventing a race to the bottom. In 2023, the International Organization of Securities Commissions (IOSCO) issued policy recommendations for crypto and digital-asset markets, providing benchmark regulatory guidance for its member countries [33]. This minimum-standard model is analogous to the role of the Basel Accords in traditional banking: it requires all participating countries to meet basic requirements on customer-asset protection and conflict-of-interest management but allows each country to add stricter rules on top (such as different leverage caps) according to its national circumstances. The advantage of this approach is that it can maintain a minimum protection standard while allowing each country to innovate according to its own situation.

IOSCO's recommendations cover core areas such as anti-money laundering, know-your-customer, the prevention of market manipulation, and customer-asset protection. Through these minimum standards, the international community can prevent regulatory competition from evolving into a total collapse of consumer protection. At the same time, countries can still maintain differences in leverage limits, product classification, and entry standards to suit their stage of economic development and risk appetite. This approach has already achieved some success in other financial domains; for example, the recommendations of the Financial Action Task Force (FATF) on anti-money laundering have been adopted by most countries.

Although international organizations are actively promoting coordination, the surrender of sovereignty in reality still faces complex political-economy constraints. Global regulatory unification involves not only the alignment of technical standards but also touches on each country's financial sovereignty, tax interests, and industrial policy. Over the next 5 to 10 years, therefore, the most likely regulatory configuration for the perpetual futures market combines a global consensus on bottom-line issues such as anti-money laundering and asset custody with persistent regional differences on dimensions such as leverage limits, product access, and derivatives classification. This hybrid model of core consensus plus regional difference is the most realistic response to the regulatory impossible trinity.

## 26.5 Functional regulation versus entity-based regulation

The traditional financial-regulatory framework rests mainly on the logic of entity-based regulation. This paradigm assumes that financial activity is tightly bound to specific types of institution, so regulators achieve their objectives by licensing and imposing overall constraints on specific entities such as banks, securities exchanges, or commodity-futures commissions. The emergence of perpetual futures, however, poses a fundamental challenge to this paradigm. As a derivative that occupies a dominant position in the crypto-asset market, perpetual futures operate in a way that crosses the clear boundaries of traditional financial products, so a regulatory method based on entity classification faces significant limitations when confronting this kind of innovative instrument. This predicament has driven an evolution of the regulatory paradigm, prompting academics and policymakers to reexamine the theoretical value and practical potential of functional regulation.

### 26.5.1 The limits of entity-based regulation

Entity-based regulation works effectively only on the premise that the regulated object can be accurately assigned to a predefined legal and economic category. In the U.S. financial-regulatory system, this classification process usually determines whether a product falls under the jurisdiction of the SEC or the CFTC. For digital assets and their derivatives, this either-or classification framework has produced long-standing jurisdictional disputes and regulatory vacuums.

The legal nature of perpetual futures first faces the challenge of the definition of a security. The Howey test, established by the U.S. Supreme Court in 1946, is the core standard for judging whether a transaction constitutes an investment contract and therefore a security [34], and the SEC adopted this standard in its analytical framework for digital assets [3]. The test requires an investment of money, in a common enterprise, with a reasonable expectation of profits, where the profits derive entirely or predominantly from the efforts of others. As a derivative, perpetual futures anchor their value to the price of an underlying crypto-asset, and traders profit from price movements by going long or short. This mechanism represents no ownership of any issuing entity, and traders' expectation of profit derives from changes in the market price rather than from the operating efforts of a specific management team. Classifying perpetual futures directly as a security under the Howey test framework therefore faces significant legal obstacles.

Having ruled out classification as a security, bringing perpetual futures under the commodity-futures regulatory framework seems the more reasonable path, but this too faces a conflict of technical definition. A traditional futures contract is defined as a standardized agreement to buy or sell a specific quantity of a commodity at a predetermined price on a specific future date. The core innovation of perpetual futures is precisely that they eliminate the expiration date, using the funding-rate mechanism to make the contract price track the spot price closely [13]. This design without a delivery deadline places them, in legal definition, outside the category of traditional futures, so the CFTC faces a challenge of legal interpretation in establishing its jurisdiction. Although the CFTC has recently signaled that it may permit perpetual futures trading in the United States, this process remains subject to a reinterpretation of the definition of derivatives [35].

This classificatory ambiguity directly leads to the formation of a regulatory vacuum. When a systemically important financial innovation cannot be accommodated by the existing regulatory framework, market participants often exploit the ambiguity for regulatory arbitrage. Capital and trading activity tend to flow to the jurisdictions with the most lenient regulatory requirements or where clear rules have not yet been established. This phenomenon is especially evident in the perpetual futures market, where large trading volumes concentrate on offshore exchanges, leaving the regulators of major economies without effective tools to intervene when facing potential systemic risk and market manipulation. This regulatory failure stems not from regulators' inaction but from the structural limitation of the entity-based regulatory paradigm in the face of cross-boundary financial innovation.

### 26.5.2 The principle of functional regulation

Faced with the limitations of entity-based regulation, functional regulation offers a more adaptive alternative paradigm. The theoretical basis of functional regulation can be traced to the financial-system design framework of Merton and Bodie [36]. That framework proposes that financial functions are more stable than financial institutions; the form of an institution evolves with changes in technological, political, and cultural norms, but the basic functions that a financial system must perform are enduring. The design and regulation of a financial system should therefore anchor on function rather than on institution.

Applying this theory to regulatory practice, the core logic of functional regulation can be summarized as "same function, same risk, same regulation." In discussing financial-regulatory frameworks, the Bank for International Settlements notes that activity-based or functional regulation is more justified when financial instability originates from a specific activity rather than a specific entity [37]. Under this paradigm, the focus of regulation shifts from "what type of institution is this" to "what economic function is this institution performing." If a decentralized protocol and a centralized exchange both perform the functions of order matching and price discovery, then, for that specific function, they should be subject to the same rules aimed at preventing market manipulation and ensuring transparency, regardless of their legal organizational form.

The economic advantage of functional regulation lies in its ability to effectively eliminate the incentive for regulatory arbitrage. Under entity-based regulation, innovators have a strong incentive to circumvent strict regulatory requirements by changing their organizational form or product name. Functional regulation, by seeing through the appearance of organizational form and imposing constraints directly on the substance of the economic activity, renders such formal circumvention ineffective. Moreover, this paradigm is more friendly to technological innovation. It does not need to create a new legal category for every newly emerging financial instrument or institutional form but instead decomposes the new thing into a combination of known financial functions and applies the corresponding existing rules.

Figure 26-5 contrasts the structural difference between the two regulatory paradigms: entity-based regulation attempts to force perpetual futures into ill-fitting institutional categories, whereas functional regulation achieves precise rule-matching by decomposing the specific functions they perform.

![Figure 26-5](./images/fig-26-5-en.png)

**Figure 26-5.** Structural comparison of entity-based and functional regulation

### 26.5.3 The functional decomposition of perpetual futures

Applying the functional-regulation paradigm to the perpetual futures market requires a deep functional decomposition of the platforms that offer perpetual futures trading. Whether a centralized exchange or a decentralized protocol, its operation can be deconstructed into four core financial functions: clearing, custody, market-making, and disclosure. By mapping these functions to their corresponding regulatory objectives, one can build a systematic and highly adaptive regulatory framework.

The clearing function is the primary source of systemic risk in the perpetual futures market. Because of the high leverage inherent in perpetual futures, the design of the liquidation mechanism directly bears on market resilience. Under a functional-regulation framework, any entity or protocol that performs the clearing function must be subject to rules analogous to those of a traditional clearinghouse. These include establishing a robust risk-management framework, setting reasonable initial and maintenance margin requirements, and maintaining an insurance fund sufficient to absorb the bad-debt losses of underwater positions under extreme market conditions. For decentralized exchanges, this means that the liquidation logic in their smart contracts must meet minimum risk-control standards to prevent a liquidation cascade from triggering a broad market collapse.

The custody function concerns the holding and safekeeping of customer assets. The lesson of the FTX episode is that when a trading platform performs both trade-matching and asset-custody functions, the risk of misappropriating customer assets is extremely high. Functional regulation requires strict asset-segregation rules for entities that perform the custody function. This means that customers' margin must be completely separated from the exchange's operating funds at the physical or cryptographic level and must undergo regular external audit or provide verifiable transparency through cryptographic means such as proof of reserves.

The market-making function directly affects the supply of liquidity in the perpetual futures market but is also prone to conflicts of interest and market manipulation. When the exchange itself or an affiliated entity acts as a major market maker on the platform, the fairness problem comes to the fore. Functional regulation requires imposing explicit market-maker obligations on participants that perform the market-making function, such as maintaining minimum liquidity and limiting spreads under abnormal market conditions. At the same time, a strict firewall must be established to prevent the exchange performing the matching function from using non-public order-flow information to gain an improper advantage for its proprietary market-making business.

The disclosure function is the foundation for mitigating information asymmetry among market participants. Functional regulation requires that platforms offering perpetual futures trading, whatever their architecture, provide the market with sufficient transparency. This includes publishing trading data, disclosing the key terms of market-maker agreements, clarifying the calculation methods of liquidation parameters and the mark price, and providing regular trade-surveillance reports to deter manipulation.

Figure 26-6 systematizes the decomposition of the four functions above into a regulatory mapping, enabling regulators to identify precisely the functional nodes that require intervention rather than imposing homogeneous compliance obligations on an entire platform indiscriminately. For a centralized exchange that bears multiple functions at once, this framework requires the establishment of internal firewalls between the functions; for a decentralized architecture in which the functions are dispersed across different protocols, the compliance obligations can be assigned to the actual performer of each function.

![Figure 26-6](./images/fig-26-6-en.png)

**Figure 26-6.** Functional decomposition of a perpetual futures exchange and the corresponding regulatory mapping

### 26.5.4 Implementation challenges

Although functional regulation offers an elegant solution in theory, its actual implementation in the perpetual futures market still faces major challenges. These challenges stem mainly from the special features of crypto-market microstructure and the inherent properties of decentralized technology.

The first is the problem of blurred functional boundaries. In traditional finance, clearing, custody, and trade-matching are usually performed separately by different specialized institutions. In the crypto-asset market, however—especially within centralized exchanges—these functions are highly concentrated in a single entity. This cross-functional coupling makes it exceedingly difficult to apply segregated regulation to a single function. For example, when an exchange controls both the liquidation engine and the market-making funds, requiring it to build an absolute internal firewall often lacks a credible verification mechanism. It is very difficult for regulators to force the separation of these deeply coupled functions without disrupting the exchange's existing business model and efficiency advantages.

The second is the challenge of enforcement difficulty—namely, "who determines that a certain function has been performed" and "against whom is accountability pursued." In the context of decentralized exchanges, this problem is especially acute. A decentralized protocol is, in essence, a set of automatically running smart-contract code that lacks a traditional legal-person entity as a regulatory object. When an automated market maker protocol performs the functions of price discovery and liquidity provision, it is difficult for regulators to determine whether the protocol's original developers, the holders of governance tokens, or the operators of the front-end interface that provides liquidity should bear compliance responsibility. This absence of a responsible subject greatly weakens the deterrent power and enforceability of functional regulation when it confronts a purely on-chain application.

Moreover, the scope of applicability of functional regulation has inherent limits. Although it can effectively handle activities highly similar to traditional financial functions, for mechanisms unique to crypto markets—such as algorithm-based automated liquidation and flash loans—the functional-regulation framework may lack ready-made rules to draw on. This means that regulators must not only decompose functions but also create entirely new regulatory standards for these new functions, which undoubtedly increases the complexity and time cost of regulatory design. Functional regulation is therefore not without limits; it requires continual adjustment and refinement in defining functional boundaries, adapting to cross-boundary coupling, and innovating enforcement means.

## 26.6 Regulating DeFi perpetual futures

The preceding analysis has systematically evaluated the various regulatory tools aimed at centralized exchanges. Assessing the actual effectiveness of these tools, however, requires considering one key variable: as the principal escape valve for regulatory arbitrage, decentralized exchanges' accessibility directly determines the net effect of regulating the centralized market. If traders can migrate almost frictionlessly to permissionless decentralized protocols, the actual binding force of the leverage limits or compliance requirements imposed on centralized exchanges is greatly diminished. Understanding the regulatory boundaries of DeFi perpetual futures is therefore a prerequisite for accurately assessing the effectiveness of the entire regulatory toolbox.

Decentralized exchanges pose a fundamental challenge to the traditional regulatory paradigm. When an exchange is no longer an entity operated by a specific company but a set of smart contracts deployed on a blockchain and jointly maintained by nodes worldwide, the traditional "regulate the entity" approach faces the risk of complete failure. This failure stems not from a lack of regulatory will but from the physical limits of the technical architecture: code has no nationality, a smart contract has no legal personality, and a decentralized network has no chief executive who can be subpoenaed. This does not mean, however, that decentralized finance is unregulable; only that the entry point of regulation must shift. This section analyzes how a decentralized architecture dismantles traditional compliance tools and explores how, in an environment without a centralized controller, a new type of regulatory framework can be built through code audits, front-end restrictions, and liquidity-provider obligations.

### 26.6.1 The spectrum of decentralization

Decentralization is not a black-and-white binary state but a continuous spectrum. In the perpetual futures market, a protocol's degree of decentralization directly determines the difficulty of regulatory intervention. Depending on how many core components run on-chain, existing decentralized perpetual futures exchanges fall into three categories: nominal decentralization, hybrid architecture, and fully on-chain architecture [38].

The nominally decentralized architecture is typified by dYdX v3 (its form before migrating to the v4 standalone chain in 2023). The protocol deploys its smart contracts on an Ethereum layer-2 network, achieving decentralization of asset custody and settlement, but its order book and matching engine still run on centralized servers operated by dYdX Trading [39]. This design guarantees users' control over their assets while providing a trading experience close to that of a centralized exchange. From a regulatory standpoint, this architecture retains a clear operating entity and centralized infrastructure, and regulators can enforce compliance requirements by requiring the operating company to implement geo-blocking or identity verification.

The hybrid architecture is typified by GMX, whose core feature is that it abandons the order-book model in favor of a global liquidity-pool design [40]. In this architecture, users' trades are matched directly against the liquidity pool as counterparty, prices are supplied by a decentralized oracle network, and the liquidation logic is executed entirely and automatically by smart contracts [41]. This design markedly raises the degree of decentralization, with no centralized matching engine and no single controlling entity. The hybrid architecture, however, still depends on an external oracle network to feed in price data, which provides a potential intervention node for regulation.

The fully on-chain architecture represents the current endpoint of decentralized evolution, typified by Hyperliquid and dYdX v4. Such protocols are usually built on a dedicated layer-1 blockchain optimized for trading, integrating the order book, matching engine, oracle, and liquidation mechanism entirely into the consensus layer [39] [42]. In Hyperliquid's design, the validator network is responsible not only for producing blocks but also for maintaining the global order book directly in memory, with all state transitions confirmed through Byzantine fault-tolerant consensus [42]. This architecture greatly reduces reliance on centralized components and approaches end-to-end decentralization. It eliminates a certain class of systemic risk arising from single points of failure but at the same time introduces new risks at the consensus and oracle layers, leaving traditional regulatory tools almost nothing to grip onto.

Figure 26-7 places the three architectures above on a continuous spectrum of decentralization from low to high: the higher the degree of decentralization, the lower the regulatory accessibility, which means that the design of regulatory tools must adjust dynamically to the regulated object's position on the spectrum.

![Figure 26-7](./images/fig-26-7-en.png)

**Figure 26-7.** The decentralization spectrum of DeFi perpetual futures

### 26.6.2 The failure of traditional tools

Traditional financial regulation is built on the foundational assumption of "intermediary institutions," achieving its policy objectives by licensing entities such as banks, brokers, and exchanges and imposing obligations on them. When a decentralized exchange eliminates the intermediary through smart contracts, this regulatory toolbox encounters a structural failure.

Licensing requirements are the first line of defense in traditional regulation, but in a fully decentralized protocol this requirement loses its object. A smart contract deployed on a blockchain cannot apply for a business license, and there is no legal-person entity to bear the legal consequences of operating without one [43]. Even if regulators attempt to hold the protocol's developers accountable, the nature of open-source software allows the writing and deployment of code to be carried out completely anonymously. More importantly, once a smart contract is set to be non-upgradeable, even its original developers cannot modify or halt its operation, which makes traditional enforcement means such as "revoking the license" or "forcing a shutdown" physically impossible [44].

AML/KYC rules are another pillar of traditional regulation, but they likewise face an enforcement predicament in a permissionless blockchain network. The essential feature of a decentralized exchange is that it allows any user holding a crypto wallet to interact directly with the protocol, and this interaction occurs in the underlying blockchain network without passing through any centralized gateway that could perform identity verification [45]. Requiring a smart contract to verify a user's real-world identity before executing a trade is not only technically difficult but also runs counter to the core spirit of blockchain pseudonymity. This architectural feature gives decentralized exchanges a natural capacity to evade traditional identity checks, thereby weakening the global anti-money-laundering system in practice [46].

Asset-segregation requirements are used in traditional regulation to prevent intermediaries from misappropriating customer funds, and this is the core mechanism for guarding against an FTX-like collapse. In a decentralized exchange, however, this problem is largely mitigated by technical means. Users' assets are locked in publicly transparent smart contracts, and their transfer and liquidation follow predetermined mathematical logic, making it difficult for any individual or organization to bypass the code rules and use those funds [47]. On the specific dimension of custodial misappropriation, the determinism of code substitutes to some degree for human trust in an intermediary, but this does not eliminate other, new risks—such as oracle manipulation and the inadequate absorption of liquidated positions (see Section 26.6.4).

Regulatory arbitrage is the inevitable result of the failure of traditional tools. Because blockchain networks transcend geographic borders, the strict regulation imposed by one country can often only drive trading activity to offshore hubs or decentralized networks rather than truly eliminate the risk [48]. When compliance costs make centralized exchanges uncompetitive, users seeking high leverage and permissionless trading migrate naturally to decentralized alternatives. This migration not only causes regulators to lose visibility into the market but may also expose users to informal markets that lack basic protection, producing consequences contrary to the original regulatory intent [45].

### 26.6.3 New regulatory tools

Faced with the failure of traditional tools, the regulatory paradigm must shift from "regulating the entity" to "regulating the code" and "regulating the access point." This shift has given rise to a set of new regulatory tools adapted to the decentralized architecture, which attempt to achieve public-policy objectives without disrupting the underlying technical logic.

Code-audit requirements are becoming a core pillar of decentralized-finance regulation. Since smart contracts substitute for the functions of traditional financial institutions, reviewing the security and logical correctness of the code is equivalent to reviewing the internal controls of a traditional financial institution. Regulators can require that all smart contracts offering financial services to the public undergo a comprehensive security audit by a certified third-party auditor before deployment [49]. Such an audit must cover not only the security vulnerabilities that guard against hacking but also economic stress tests of the liquidation logic, oracle dependencies, and governance permissions. By establishing a standardized audit framework and an entry regime for audit firms, regulation can significantly improve the market's overall resilience without directly interfering in the operation of the protocol [50].

Front-end regulation represents another pragmatic compromise strategy. Although regulators cannot prevent users from interacting directly with smart contracts on the blockchain, the vast majority of ordinary users still rely on a web-based graphical user interface (the front end) to access these protocols [51]. Regulation can therefore focus on the operators of these front-end interfaces, requiring them to implement geo-blocking based on users' IP addresses or to integrate compliance-screening tools at the front-end level [52]. This "regulate the access point" strategy has already been widely adopted in practice; for example, the front ends of mainstream protocols such as Uniswap actively block access from sanctioned regions. Although advanced users can bypass these restrictions by calling contracts directly or using alternative front ends, front-end regulation effectively raises the barrier to non-compliant participation and brings the vast majority of non-professional users within the scope of protection.

Liquidity-provider obligations are an innovative regulatory idea designed for the features of the decentralized architecture. In protocols that adopt an automated market maker or liquidity-pool model, although traders may be transient and anonymous, the participants who supply large-scale liquidity are often long-lived entities with large amounts of capital [38]. Regulators can shift their approach: rather than attempting to identify every trader, they can impose compliance obligations on liquidity providers above a certain capital scale [53]. For example, they can require institutional-grade liquidity providers to conduct anti-money-laundering screening of the sources of their funds or to follow specific risk-management standards when providing liquidity. Because the on-chain behavior of liquidity providers is continuous and traceable, this strategy of focusing on large participants is far more feasible to enforce than comprehensive surveillance of all users.

### 26.6.4 Case study: Hyperliquid

Fully on-chain protocols, in responding to extreme market events, have displayed a complex interplay between decentralized governance and the logic of traditional regulation. The JELLY-token manipulation incident on Hyperliquid in March 2025 offers a highly valuable natural experiment for understanding this tension [54].

JELLY is a low-market-cap perpetual futures asset listed for trading on Hyperliquid. Exploiting the asset's scarce spot liquidity, the attacker established a large short position on Hyperliquid and then maliciously ramped up the price in the spot market, attempting to drain the protocol's liquidation fund pool [54]. Because JELLY's price was manipulated upward by more than 400% in a short time, and the order book lacked sufficient liquidity to absorb the forcibly liquidated short position, the position was transferred to the protocol's liquidity-provider vault, driving the vault's unrealized loss to about $13.5 million at one point (about $12 million when the validators intervened) [54][55]. In this moment of crisis, the protocol's built-in auto-deleveraging (ADL) mechanism failed to activate in time because of a flaw in the parameter setting of its trigger condition, and the solvency of the entire protocol faced a severe test [54].

Faced with systemic risk, Hyperliquid did not rely on the intervention of an external regulator but instead activated a decentralized-governance mechanism. The validator network quickly reached consensus and executed an emergency intervention through an on-chain vote: they overrode the manipulated oracle price, forcibly closed the relevant positions at the reasonable pre-manipulation price, and compensated the affected legitimate long traders from the protocol's reserves (excluding addresses associated with the attack) [54]. At the same time, the validators voted to permanently delist the JELLY contract from the trading platform [56].

This incident reveals the potential and the limits of decentralized autonomy as an endogenous regulatory mechanism. On the one hand, it demonstrated that even without a centralized entity, a decentralized network still has the capacity to act quickly in a crisis, protect the system from malicious attack, and compensate innocent users. This crisis-handling mechanism, driven by validator consensus, in effect partly achieved the market-integrity and majority-user-protection objectives that traditional regulation pursues [57]. On the other hand, this act of intervening in contract execution by modifying the oracle price essentially broke the absolute rigidity of "code is law" and introduced the subjectivity of human judgment.

From the perspective of regulatory economics, the Hyperliquid case shows that decentralized governance is not the opposite of traditional regulation but a complementary institutional arrangement. When a protocol's architecture technically rules out the possibility of external enforcement, cultivating a healthy, fast-responding decentralized-governance mechanism—one that can internalize and enforce the basic principles of maintaining market fairness and stability—will be the most pragmatic choice for regulators confronting the decentralization paradox. Future regulatory frameworks should not seek to destroy this capacity for autonomy but should instead work to set reasonable boundaries and transparency requirements for decentralized governance, so that it can resist risk without degenerating into a tool through which a few validators abuse their power.

## 26.7 Empirical evidence on regulation

The economic analysis of regulatory intervention cannot remain at the level of theoretical deduction alone. The distinctiveness of the crypto-asset market lies in its high degree of data transparency and the fragmentation of the global regulatory framework, which provide a rich array of natural-experiment scenarios for evaluating the market-quality effects of different regulatory tools. Empirical evidence shows that the impact of regulation on market quality is not a one-way cost or benefit but exhibits pronounced nonlinearity and dimensional differentiation. Every regulatory intervention, while improving certain market-quality dimensions, necessarily comes at the cost of others. This section quantitatively assesses the specific impact of regulatory intervention on the five market-quality dimensions—transaction costs, price discovery, resilience, fairness, and accessibility—by analyzing the leverage limits of Japan and the European Union, exchange compliance requirements, and the enforcement actions of the SEC.

### 26.7.1 Empirical evidence on leverage limits

Leverage limits are the intuitive tool with which regulators address systemic risk, and their core logic is to interrupt the transmission path of the liquidation cascade by reducing individual participants' risk exposure. The net effect of leverage limits on market quality, however, depends heavily on the parameter setting and the enforcement environment. Japan's FSA leverage-limit policy of 2020 provides a clear empirical sample of this trade-off. Before the limit was implemented, Japanese crypto-asset trading platforms generally offered leverage as high as 25x, and annual margin-trading volume once reached the scale of $500 billion [58]. In May 2020, the FSA forcibly reduced the maximum leverage on margin trading to 2x, and this policy shock directly reshaped the microstructure of the Japanese crypto market.

Figure 26-8 uses two panels to show the change in market quality before and after Japan's leverage-limit policy. On the accessibility and liquidity dimension, average monthly margin-trading volume collapsed from about $42 billion before the limit to about $5 billion per month by the end of 2020, and market depth shrank significantly; on the fairness and resilience dimension, the overall profitability rate of retained users rose from about 17% to 32%. Two points must be emphasized here. First, this profitability figure is cited by the author from [59], has not yet undergone independent public verification, and should be regarded as cited evidence rather than a verified empirical conclusion. Second, this increase stems mainly from a composition effect—the change in the makeup of market participants after high-risk retail traders exited—rather than from an improvement in the profitability of any individual trader. The essence of this trade-off is that regulation, at the cost of liquidity and retail accessibility, weeded out the most fragile market participants, thereby improving the system's overall resilience and traders' average survival rate.

![Figure 26-8](./images/fig-26-8-en.png)

**Figure 26-8.** Change in market quality before and after Japan's 2020 leverage limit

Similar trade-offs also appeared in the regulatory practice of Europe and South Korea. Through its product-intervention measures for CFDs, ESMA strictly limited retail leverage on crypto-derivatives to 2x, which placed European domestic perpetual futures providers at a significant disadvantage in competing with offshore platforms offering 10x to 100x leverage [60]. South Korea's regulatory path was more aggressive: in September 2025, its Financial Services Commission (FSC) issued guidelines on crypto-asset lending that prohibit leveraged borrowing in excess of collateral value [61]. At the same time, South Korea's long-standing controls on cross-border capital flows have impeded the free entry and exit of arbitrage capital, isolating the domestic market from the global liquidity pool and producing a structural pricing-island phenomenon, the so-called "kimchi premium" [62]. Together, these natural experiments demonstrate that, absent global coordination, unilateral leverage limits often lead to a geographic reconfiguration of liquidity rather than a fundamental elimination of systemic risk.

### 26.7.2 The market-quality effects of compliance requirements

An exchange's compliance status and choice of domicile directly determine the strength of the regulatory constraints it faces and, in turn, systematically affect its market-quality performance. In traditional financial-microstructure theory, stricter regulation is generally thought to improve market integrity and reduce adverse-selection costs. In the crypto-asset market, however, the relationship between compliance requirements and liquidity is more complex and dynamic. Jurisdictions that require exchanges to implement strict asset segregation, customer identity verification, and anti-money-laundering procedures often face pressure from the migration of trading volume to more lightly regulated regions.

Empirical research shows that exchanges registered in different jurisdictions exhibit significant divergence in market-quality indicators. Taking global platforms such as Binance and OKX as examples, their liquidity-provision patterns under different regulatory environments reflect the pass-through mechanism of compliance costs [63]. In markets with strict regulatory requirements, market makers face higher costs of tied-up capital and compliance-reporting burdens, and these costs are ultimately internalized as wider bid-ask spreads and thinner order-book depth. Conversely, in more lightly regulated offshore markets, lower entry barriers attract a large number of high-frequency traders and arbitrage capital, forming a highly competitive transaction-cost environment.

This liquidity stratification, driven by regulatory arbitrage, embodies the dual effect of compliance requirements. On the one hand, strict registration requirements and asset-segregation rules significantly improve market resilience and fairness and reduce the tail risk of an FTX-like collapse. On the other hand, high compliance costs constitute a substantive barrier to market entry, causing liquidity to concentrate among the few large compliant institutions that can bear these costs. This regulation-driven market concentration not only weakens competition but may also aggravate the fragility of liquidity supply under extreme market conditions. When compliant market makers retreat in unison during a crisis because of regulatory constraints or capital requirements, liquidity in the compliant market may even dry up faster than in the non-compliant market.

### 26.7.3 The cost of regulatory uncertainty

In assessing the economic consequences of regulation, one frequently overlooked dimension is the friction cost of regulatory uncertainty itself. When regulatory rules are ambiguous, classification standards unclear, or reliance placed on ex post enforcement rather than ex ante guidance, market participants must pay an additional premium for the potential compliance risk. The enforcement actions the SEC took against major crypto-asset exchanges in 2023 provide an ideal window for quantifying this cost of regulatory uncertainty.

In June 2023, the SEC sued Binance and Coinbase in quick succession, alleging that they offered securities-trading services without registration. The event study by Saggu et al. shows that this strategy of establishing regulatory boundaries through enforcement caused immediate and far-reaching damage to market liquidity [64]. The event study, based on a full sample of the SEC's series of enforcement actions, finds that in the first three days after the enforcement announcements, the prices of the affected crypto-assets fell by an average of about 5.2%, with the decline widening further to about 17.2% within 30 days. More critically, trading volume dropped sharply, indicating that this was not merely a repricing of prices but a structural withdrawal of liquidity.

The damage that regulatory uncertainty does to market microstructure operates mainly through the defensive retreat of market makers. Facing ambiguous asset-classification standards and potential legal sanctions, the rational choice for compliant market makers is to widen spreads or stop providing liquidity for the relevant assets outright. The research finds that assets with smaller market capitalization and poorer initial liquidity suffered more severely under this regulatory shock, with the widening multiple of their bid-ask spreads significantly higher than that of the leading assets [64]. This liquidity evaporation, triggered by regulatory uncertainty, leaves the market highly fragile when facing an external shock. The empirical results indicate that, for market quality, an unclear regulatory framework may cause greater harm than clear but strict regulatory rules. Under ambiguous rules, the risk aversion of investors and market makers is amplified, leading to the inefficient idling of capital and the stalling of the price-discovery mechanism.

### 26.7.4 A comprehensive assessment of five-dimensional market quality

Based on the evidence from the preceding empirical research and natural experiments, we can systematically assess the comprehensive impact of the various regulatory tools on crypto-asset market quality. Table 26-3 aggregates the existing empirical findings and maps them onto the five-dimensional market-quality assessment framework proposed in this chapter. This matrix is not only a summary of historical data but also provides an economic benchmark for future regulatory design.

Table 26-3 reveals a core policy dilemma: in the existing regulatory toolbox, no single intervention can produce a purely positive effect across all five market-quality dimensions. Leverage limits greatly strengthen the system's resilience and protect inexperienced retail participants but inevitably harm market accessibility and overall liquidity. Mandatory customer identity verification and anti-money-laundering compliance improve market fairness and legitimacy but likewise come at the cost of accessibility and higher transaction costs. Disclosure and asset-segregation requirements are among the few regulatory tools with a high net benefit: while significantly improving fairness and resilience, they have relatively small negative spillovers to the other dimensions.

| Type of regulatory intervention | Transaction costs | Price discovery | Resilience | Fairness | Accessibility | Empirical basis |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| Strict leverage limit (e.g., reduced to 2x) | Significant increase | Slight weakening | Significant improvement | Significant improvement | Significant decline | Japan FSA data [58][59] |
| Mandatory asset segregation and audit | Slight increase | Unchanged | Significant improvement | Significant improvement | Unchanged | Post-FTX comparative study [63] |
| Strict KYC/AML compliance | Significant increase | Unchanged | Unchanged | Significant improvement | Significant decline | Spread comparison between offshore and compliant platforms [63] |
| Regulatory uncertainty (enforcement actions) | Significant increase | Significant weakening | Significant decline | Unchanged | Slight decline | SEC litigation event study [64] |
| Isolationist policy (capital controls) | Significant increase | Significant weakening | Slight improvement | Unchanged | Significant decline | South Korea's "kimchi premium" phenomenon [62] |

**Table 26-3.** Summary of the empirical effects of regulatory intervention on five-dimensional market quality (Data source: compiled by the author based on [58][59][62][63][64])

The ultimate lesson of this empirical matrix is that optimal regulatory design does not seek the absolute maximization of any single dimension but instead makes wise trade-offs among the five dimensions that suit specific policy objectives. If the regulator's primary objective is to guard against a systemic collapse, then accepting lower liquidity and higher transaction costs is the price that must be paid. If regulation relies excessively on ex post enforcement or imposes technically incompatible requirements, however, the regulatory uncertainty and friction costs it generates will cause market quality to deteriorate simultaneously across all dimensions. Future regulatory frameworks must therefore move from moral judgment toward cost-benefit analysis grounded in empirical data, seeking room for marginal improvement while acknowledging technical constraints.

## 26.8 The political economy of regulation

The analytical frameworks of the preceding sections carry an important implicit assumption: that the regulator is a benevolent social planner aiming to maximize social welfare. In reality, however, regulatory rules are not formulated in a vacuum but are the political-economy equilibrium of a game among many interests. The systematic deviation between the theoretical optimum and actual policy is precisely the object of this section's analysis. Understanding the direction of crypto-market regulation cannot proceed from the theoretical model of market failure alone; it must examine who has an incentive to push for regulation, who has an incentive to block it, and who has the ability to exert substantive influence over the rule-making process. At the intersection of decentralized finance and traditional finance, the final form of regulation is often the product of mutual compromise among stakeholders rather than the theoretical optimum in the economic sense. This section applies the theory of regulatory capture to analyze the evolution of the crypto industry's political influence, maps the stakeholders, and explores how the mechanism of regulatory competition among jurisdictions determines the ultimate quality of regulation.

### 26.8.1 The theory of regulatory capture

The theory of regulatory capture was advanced in 1971 by the Nobel laureate in economics George Stigler; its core thesis is that a regulatory agency will ultimately be controlled by the industry it regulates, causing regulatory rulemaking to favor industry interests over the public interest [65]. Peltzman (1976) developed this theory further, proposing that regulators are not simply captured by a single interest group but instead seek an equilibrium that maximizes political support between producers and consumers—a perspective that provides a theoretical basis for understanding the multi-stakeholder game in Section 26.8.2 [66]. In the evolution of the crypto market, this theory has attracted a growing body of empirical observation consistent with its predictions. As industry capital has accumulated, crypto firms have shifted from initially evading regulation to actively shaping regulatory rules.

The crypto industry's influence over the political process is most directly reflected in the exponential growth of its lobbying spending. Before 2020, the industry's lobbying spending in Washington was almost negligible. As the market grew and compliance pressure mounted, however, industry resources began to tilt on a large scale toward the political arena. In 2022, the crypto industry's federal lobbying spending reached $21.6 million, 2.6 times that of 2021 and 8.6 times that of 2020 [67]. By 2023, despite multiple major industry crises, this figure still set a new record of nearly $25 million, with Coinbase and the Blockchain Association among the largest spenders [68].

Figure 26-9 tracks the exponential growth of the crypto industry's federal lobbying spending from 2018 to 2024. Even amid multiple major industry crises in 2022 (the Terra/Luna collapse and the FTX bankruptcy), lobbying spending rose rather than fell—a sign that in a crisis industry participants step up their investment in the regulatory agenda, competing for a voice while the rules are being rewritten.

![Figure 26-9](./images/fig-26-9-en.png)

**Figure 26-9.** Annual trend of the crypto industry's federal lobbying spending

FTX and its founder, Sam Bankman-Fried, offer a classic instance of regulatory capture in the crypto domain. Before the company's collapse, Bankman-Fried was one of the largest donors in U.S. politics and, through his team, established direct contact with financial regulators at the highest level, seeking to advance the Digital Commodities Consumer Protection Act, which would have favored his platform [69]. This influence rested on more than capital alone; it also ran through the subtler "revolving door" effect, whereby crypto firms hired former regulatory officials and government staff at high salaries to work for their new employers using the connections and rule knowledge they had accumulated within the system.

This deep political engagement has produced an endogenous bias in regulatory policy. When the regulated hold an informational and resource advantage, they can steer legislators' attention toward specific types of risk while obscuring other risks that might touch their core business model. The observed regulatory framework therefore often reflects the strategic intentions of the dominant firms within the industry rather than an objective outcome based on a systemic risk assessment.

### 26.8.2 Stakeholder analysis

The driving force behind the evolution of crypto regulation originates in the ongoing game among different interest groups. In this complex ecosystem, the motives and strategies of each party determine the resistance to, and the direction of, policy progress.

The forces pushing for strict regulation consist mainly of traditional financial institutions, consumer-protection advocates, and victim groups. Traditional financial institutions play a dual role in this game: on the one hand, they view unregulated crypto platforms as a threat of unfair competition and demand that regulators apply the principle of "same business, same risk, same rules" to eliminate the space for regulatory arbitrage; on the other hand, they also hope that a clear compliance framework will remove the compliance barriers to their own entry into this emerging market. Consumer-protection advocates and the retail groups that suffered losses in market collapses constitute the social pressure pushing for regulation, demanding strict asset segregation, leverage limits, and disclosure requirements to prevent a recurrence of an FTX-like episode.

The forces that block or seek to weaken regulation are led by crypto-native firms, industry lobbying groups, and advocates of technological innovation. The strategy of this camp is not to resist regulation outright but to advocate a "tailored," light-touch regulatory framework. They emphasize the special nature of decentralized technology, arguing that imposing traditional financial regulations designed for intermediaries on smart contracts would suppress innovation and force the industry to move overseas. Offshore jurisdictions, as this camp's implicit allies, attract capital and talent by offering a relaxed regulatory environment, which in effect raises the cost to major economies of imposing strict unilateral regulation.

Between these two opposing forces, institutional investors and large asset managers constitute a key middle force. This group manages vast amounts of capital and is eager to include crypto-assets in its portfolios but, constrained by its own compliance requirements, must operate in a regulated environment. It therefore neither wishes to see over-regulation that could shrink the market nor accepts complete laissez-faire that lacks basic property-rights protection. This demand for "moderate compliance" often becomes the decisive factor in bringing a pragmatic regulatory framework into being.

### 26.8.3 Regulatory competition

Because of crypto-assets' borderless nature and digital liquidity, regulatory jurisdiction faces a significant arbitrage challenge. Capital and business can cross borders easily, which puts countries and regions in direct competition over crypto-regulatory rules [70]. This competitive mechanism has a significant impact on the quality of global regulation.

In the initial stage of competition, the market widely feared a "race to the bottom." Under this pattern, in order to attract crypto firms and gain tax revenue and employment, some jurisdictions might competitively lower their compliance thresholds and relax their consumer-protection and anti-money-laundering requirements. This regulatory arbitrage not only weakens the overall safety of the global financial system but may also force countries that originally held to high standards to compromise under the pressure of capital outflow.

As the market matures and institutional investors enter, however, a "race to the top" has begun to emerge. After a series of trust crises at offshore platforms, high-quality crypto firms and large institutional investors increasingly prefer to operate in jurisdictions with a clear, rigorous, yet adaptive regulatory framework. This compliance premium has prompted financial centers such as Dubai, Singapore, and Hong Kong to compete in establishing comprehensive and clear virtual-asset regulatory regimes [71].

These emerging crypto hubs have not chosen to abandon regulation but instead compete by offering regulatory certainty. Hong Kong, for example, implemented a new licensing regime for virtual-asset trading platforms in 2023, setting extremely high requirements on asset segregation, conflict-of-interest management, and cybersecurity [72]. This competitive pattern shows that, in a crypto market with severe information asymmetry, high-quality regulation has itself become a competitive advantage: it provides reputational endorsement for the firms within a jurisdiction and lowers the friction costs of connecting with the traditional financial system.

### 26.8.4 Factors affecting regulatory quality

Having identified the political-economy drivers of regulation, the core question turns to how to assess and improve the actual effectiveness of regulatory intervention. The effectiveness of regulation is not simply equivalent to the strictness of the rules but depends on a series of determinants of institutional design and enforcement capacity.

The independence and technical capacity of the regulator are the foremost factors determining regulatory quality. In a domain as highly complex and rapidly iterating as crypto, if a regulator lacks sufficient resources and expertise to understand the underlying technical mechanisms, it can easily fall into the trap of "formal compliance"—in which firms superficially meet all reporting requirements but systemic risk is not, in fact, effectively controlled. At the same time, an agency's independence determines whether it can resist the regulatory-capture pressures described above and maintain an objective balance between industry interests and the public interest.

The paradigm choice in regulatory design directly affects the adaptability of the rules. Rules-based regulation often struggles to keep pace with the innovation of smart contracts and decentralized finance and readily leads to obsolete rules or new arbitrage space. By contrast, a principles-based regulatory framework, combined with the concept of functional regulation, can better see through the technological surface and strike at the essence of financial risk. This design allows regulators to remain flexible about the technical implementation path while holding to core bottom lines (such as customer-asset segregation).

In addition, the degree of international coordination determines the size of the space for regulatory arbitrage. Absent a globally unified standard, any unilateral high-quality regulation may see its effect significantly reduced by business migration. Effective regulation must not only balance the interests of all parties domestically but also build a minimum international consensus on guarding against core risks. Only when improving regulatory quality no longer comes at the cost of a jurisdiction's competitiveness can the crypto market truly escape the prisoner's dilemma of regulatory arbitrage and achieve a long-term equilibrium between innovation and stability.

## 26.9 Chapter summary

Through the analytical framework of regulatory economics, this chapter has systematically answered the core questions of why to regulate, what to regulate, how to regulate, and who should regulate, and it has proposed an optimal regulatory framework based on net-benefit maximization.

The legitimacy of regulatory intervention rests on market failure, not on the market itself. The externalities, information asymmetry, undersupply of public goods, and market power in the perpetual futures market constitute four main categories of failure, but failure alone does not automatically constitute a sufficient condition for intervention—competitive mechanisms and technological innovation can repair some defects on their own, and intervention is economically justified only when the expected benefits of regulation exceed costs such as the compliance burden, innovation suppression, and regulatory arbitrage [73]. Four conclusions can be drawn on this basis. First, asset segregation is the single tool with the highest net benefit: FTX's roughly $8 billion in customer-asset losses exposed the risk of misappropriation, and mandatory asset segregation combined with regular external audit can significantly improve resilience and fairness at relatively low compliance cost, which is why it ranks first in priority [10]. Second, functional regulation is superior to entity-based regulation: the cross-boundary nature of perpetual futures makes them hard to classify simply as a security or a commodity, whereas the functional principle of same activity, same risk, same regulation shifts the focus from institution type to specific economic function and better adapts to the rapid iteration of financial innovation [37]. Third, the cost of regulatory fragmentation may exceed that of regulation itself: the fundamental contradiction between a globalized market and fragmented sovereign jurisdiction produces, through the impossible trinity, a fragmented global regulatory map that pushes trading activity toward arbitrage space. Fourth, regulatory quality matters more than regulatory strength: disclosure and transparency requirements are the lowest-cost tools with the smallest side effects, and a well-designed framework should give priority to transparency mechanisms that promote market self-discipline.

At the practical level, an optimal regulatory framework should focus on guarding against tail risk and protecting market integrity, allocating regulatory resources first to areas such as asset segregation, reserve audit, and anti-manipulation. For centralized exchanges, compliance is no longer merely a passive cost of responding to external pressure but a strategic asset for building core competitiveness. For investors, understanding the boundaries of regulation's capability is a prerequisite for managing one's own risk, and investors need to develop the ability to assess counterparty risk independently.

Regulation plays a critical role in improving the defensive deficiencies of the perpetual futures market, but the boundary of its capability is equally clear. Legal and administrative means can mandate disclosure, set leverage caps, and regulate market-maker behavior, but they cannot change the physical mechanism of the liquidation cascade, nor can they eliminate the inherent trade-offs in a decentralized architecture. These domains that regulation cannot reach are precisely the space in which technical solutions come into play. Smart-contract audits, on-chain transparency mechanisms, and automated risk-control protocols are building an entirely new paradigm of embedded compliance [74], in which rules are hard-coded into the protocol's execution logic, thereby lowering the friction cost of compliance. Technology is not a substitute for regulation but its necessary complement. Having understood the economic logic of regulation and its limitations, the next chapter turns to a thought experiment, exploring the potential and the boundaries of perpetual futures as a universal pricing infrastructure.

## References

[1] Coinbase Institutional. (2024). *A Primer on Perpetual Futures*. Coinbase Market Intelligence, June 10, 2024 (Data source: CoinMetrics and Coinbase; 30-day rolling average, weekday basis). Reprinted via Richey May: https://richeymay.com/resource/articles/unlocking-the-power-of-perpetual-futures-cryptos-game-changing-trading-tool/

[2] Kavout. (2025). What Are Crypto Perpetual Futures and Why Do They Matter. https://www.kavout.com/market-lens/what-are-crypto-perpetual-futures-and-why-do-they-matter

[3] Securities and Exchange Commission. (2019). Framework for "Investment Contract" Analysis of Digital Assets. https://www.sec.gov/files/dlt-framework.pdf

[4] Ernst & Young. (2023). Crypto derivatives are becoming a major digital asset class. https://www.ey.com/content/dam/ey-unified-site/ey-com/en-us/insights/financial-services/documents/ey-crypto-derivatives-pov_final4.pdf

[5] Chainalysis. (2020). *East Asia: Pro Traders and Stablecoins Drive World's Biggest Cryptocurrency Market*. (Net outflow of over $50 billion in crypto-assets from East Asian addresses during 2019–2020, of which approximately $18 billion was USDT.) As recounted by the World Economic Forum (2022): https://www.weforum.org/stories/2022/01/what-s-behind-china-s-cryptocurrency-ban/

[6] BBC News. (2024). Customers of failed crypto firm FTX set for refunds. https://www.bbc.com/news/articles/c0qz3dg21vqo

[7] Stiglitz, J. E. (2024). *Government Failure vs. Market Failure*. Columbia University Academic Commons. https://ipdcolumbia.org/wp-content/uploads/2024/08/Govt_Failure_vs_Market_Failure_Stiglitz.pdf

[8] Auh, J. K., & Cho, W. (2023). Liquidation cascade and anticipatory trading: Evidence from the structured equity product market. *The Review of Asset Pricing Studies*, *13*(1), 53–94. https://doi.org/10.1093/rapstu/raac010

[9] Ali, Z. (2025). *Anatomy of the Oct 10–11, 2025 Crypto Liquidation Cascade: Macroeconomic Triggers, Market Microstructure, and Systemic Risk Lessons*. SSRN Electronic Journal. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5611392 https://doi.org/10.2139/ssrn.5611392

[10] DeKlotz, A. (2023). *FTX and Failed Custody Rules: The Collapse that Shocked the World*. SSRN Electronic Journal. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4544930 https://doi.org/10.2139/ssrn.4544930

[11] Jalan, A., & Matkovskyy, R. (2024). Systemic risks in the cryptocurrency market: Evidence from the FTX collapse. *Finance Research Letters*, *53*(C), 103632.

[12] Brunnermeier, M. K., & Pedersen, L. H. (2009). Market liquidity and funding liquidity. *The Review of Financial Studies*, *22*(6), 2201-2238. https://doi.org/10.1093/rfs/hhn098

[13] Dell'Erba, M., & Vianelli, A. (2025). Crypto-Derivatives Regulation(s). *Cornell International Law Journal*. SSRN Electronic Journal. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5895082 https://doi.org/10.2139/ssrn.5895082

[14] Crain, N. V., & Crain, W. M. (2023). *The Cost of Federal Regulation to the U.S. Economy, Manufacturing and Small Business*. National Association of Manufacturers. https://www.nam.org/wp-content/uploads/2023/11/NAM-3731-Crains-Study-R3-V2-FIN.pdf

[15] Bombardini, M., Trebbi, F., & Zhang, M. B. (2024). *Measuring the Costs and Benefits of Regulation* (NBER Working Paper No. 32955). National Bureau of Economic Research. https://www.nber.org/papers/w32955

[16] Coates, J. C. (2014). Cost-benefit analysis of financial regulation: Case studies and implications. *Yale Law Journal*, *124*, 882–1011.

[17] Wang, S., & Zhang, T. (2025). *Spot-futures manipulations in cryptocurrency markets* (SSRN Working Paper 5125326). https://ssrn.com/abstract=5125326

[18] Cong, L. W., Li, X., Tang, K., & Yang, Y. (2023). Crypto wash trading. *Management Science*, *69*(11), 6427–6454. https://doi.org/10.1287/mnsc.2021.02709

[19] European Securities and Markets Authority. (2018). *Additional information on the agreed product intervention measures relating to contracts for differences and binary options* (ESMA35-43-1000). https://www.esma.europa.eu/sites/default/files/library/esma35-43-1000_additional_information_on_the_agreed_product_intervention_measures_relating_to_contracts_for_differences_and_binary_options.pdf

[20] Thaler, R. H., & Sunstein, C. R. (2008). *Nudge: Improving Decisions about Health, Wealth, and Happiness*. Yale University Press.

[21] Commodity Futures Trading Commission. (2022). *Complaint: FTX Trading, Ltd., et al.* https://www.cftc.gov/media/8021/enfftxtradingcomplaint122122/download

[22] Lazirko, M., Appelbaum, D., & Vasarhelyi, M. (2025). Proof of reserves: A double-helix framework. *The British Accounting Review*, *57*(3), 101389.

[23] Aramonte, S., Huang, W., & Schrimpf, A. (2021). DeFi risks and the decentralisation illusion. *BIS Quarterly Review*, 21-36.

[24] Kahraman, B., & Tookes, H. E. (2017). Margin trading and leverage management. *Journal of Financial and Quantitative Analysis*, *52*(2), 481-512.

[25] Japan Cryptoasset Business Association. (2023). *Request for Revision of Leverage in Crypto Asset Margin Trading*. https://cryptocurrency-association.org/news/main-info/20231017-01/

[26] Auer, R., Cornelli, G., Doerr, S., Frost, J., & Gambacorta, L. (2023). Crypto trading and Bitcoin prices: evidence from a new database of retail adoption. *BIS Working Papers*, No 1049.

[27] Bessembinder, H., Hao, J., & Lemmon, M. (2015). Why designate market makers? Affirmative obligations and market quality. *Journal of Financial Economics*, *116*(3), 536-549. https://doi.org/10.2139/ssrn.1007274

[28] Arner, D. W., Zetzsche, D. A., & Buckley, R. P. (2023). The financialization of crypto: Lessons from FTX and the crypto winter of 2022-2023. *Available at SSRN 4372516*. https://doi.org/10.2139/ssrn.4372516

[29] Securities and Exchange Commission. (2025). *Statement on the Custody of Crypto Asset Securities by Broker-Dealers*. https://www.sec.gov/newsroom/speeches-statements/trading-markets-121725-statement-custody-crypto-asset-securities-broker-dealers

[30] Aizenman, J. (2010). The impossible trinity (aka the policy trilemma). *Encyclopedia of Financial Globalization*, 1-9.

[31] Chen, C., & Liu, L. (2022). How effective is China's cryptocurrency trading ban?. *Finance Research Letters*, *46*, 102429. https://doi.org/10.1016/j.frl.2021.102429

[32] Financial Stability Board. (2025). *Thematic Review on FSB Global Regulatory Framework for Crypto-asset Activities*. https://www.fsb.org/2025/10/thematic-review-on-fsb-global-regulatory-framework-for-crypto-asset-activities/

[33] International Organization of Securities Commissions. (2023). *Policy Recommendations for Crypto and Digital Asset Markets*. https://www.iosco.org/library/pubdocs/pdf/IOSCOPD747.pdf

[34] SEC v. W.J. Howey Co., 328 U.S. 293 (1946). United States Supreme Court.

[35] Selig, J. (2026). *The Next Phase of Project Crypto: Unleashing Innovation*. Commodity Futures Trading Commission. https://www.cftc.gov/PressRoom/SpeechesTestimony/opaselig1

[36] Merton, R. C., & Bodie, Z. (2004). *The Design of Financial Systems: Towards a Synthesis of Function and Structure* (Working Paper 10620). National Bureau of Economic Research. https://www.nber.org/papers/w10620

[37] Borio, C., Claessens, S., & Tarashev, N. (2022). *Entity-based vs activity-based regulation: a framework and applications to traditional financial firms and big techs* (FSI Occasional Paper No 19). Bank for International Settlements. https://www.bis.org/fsi/fsipapers19.pdf

[38] Heimbach, L., Wang, Y., & Wattenhofer, R. (2021). Behavior of liquidity providers in decentralized exchanges. *arXiv preprint arXiv:2105.13822*. https://doi.org/10.48550/arXiv.2105.13822

[39] dYdX Foundation. (2023). *v4 Technical Architecture Overview*. https://www.dydx.xyz/blog/v4-technical-architecture-overview

[40] GMX Contributors. (2023). *GMX: Decentralized Perpetual Exchange*. https://gmx.io/

[41] Capponi, A., & Jia, R. (2025). Liquidity provision on blockchain-based decentralized exchanges. *The Review of Financial Studies*, *38*(10), 3040-3080. https://doi.org/10.1093/rfs/hhaf046

[42] Hyperliquid Contributors. (2024). *Hyperliquid Docs: Order Book Architecture*. https://hyperliquid.gitbook.io/hyperliquid-docs/trading/order-book

[43] Ferreira, A. (2024). Decentralized finance (DeFi): the ultimate regulatory frontier? *Capital Markets Law Journal*, *19*(3), 242-260.

[44] Lorenz, G. (2024). Regulating decentralized financial technology: A qualitative study on the challenges of regulating DeFi with a focus on embedded supervision. *Stanford Journal of Blockchain Law & Policy*, *7*, 10-45.

[45] Financial Crimes Enforcement Network. (2023). *Illicit Finance Risk Assessment of Decentralized Finance*. US Department of the Treasury.

[46] Oye, E. (2025). *The Role of Decentralized Exchanges (DEXs) in Money Laundering Schemes* (working paper / preprint). ResearchGate.

[47] Bourveau, T., De George, E. T., & Macciocchi, D. (2024). Decentralized Finance (DeFi) assurance: early evidence. *Review of Accounting Studies*, 1-35. https://doi.org/10.1007/s11142-024-09834-8

[48] Priem, R. (2025). Regulatory Sandboxes for Security Tokens Trading: A Policy Instrument for Diverting Market Activity from Decentralised Exchanges (DEXs)? *SSRN Electronic Journal*.

[49] Landsman, W. R., Lyandres, E., Maydew, E. L., Rabetti, D., & Zhang, C. (2025). *Auditing Smart Contracts* (SSRN Working Paper No. 5198563). SSRN Electronic Journal.

[50] Rabetti, D. (2023). *Auditing Decentralized Finance (DeFi) Protocols* (SSRN Working Paper No. 4458298). SSRN Electronic Journal.

[51] Legal Nodes. (2024). *Legal Liability of Front-End Operators in Decentralized Finance*. https://legalnodes.com/article/front-end-operator-legal-liability

[52] Financial Action Task Force. (2021). *Updated Guidance for a Risk-Based Approach to Virtual Assets and Virtual Asset Service Providers*. FATF. https://www.fatf-gafi.org/content/dam/fatf/documents/recommendations/Updated-Guidance-VA-VASP.pdf

[53] Aquilina, M., Frost, J., & Schrimpf, A. (2024). Decentralised dealers? examining liquidity provision in DEXs. *Bank for International Settlements Working Papers*, No. 1227.

[54] OAK Research. (2025). *Hyperliquid and the JELLY attack: Context, vulnerability and team solution*. https://oakresearch.io/en/analyses/investigations/hyperliquid-jelly-attack-context-vulnerability-team-solution

[55] CoinDesk. (2025). *HyperLiquid Delists JELLY After Vault Squeezed in \$13M Tussle*. https://www.coindesk.com/markets/2025/03/26/hyperliquid-delists-jellyjelly-after-vault-squeezed-in-usd13m-tussle

[56] Halborn. (2025). *Explained: The Hyperliquid Hack (March 2025)*. https://www.halborn.com/blog/post/explained-the-hyperliquid-hack-march-2025

[57] Wright, A., & De Filippi, P. (2015). Decentralized blockchain technology and the rise of lex cryptographia. *SSRN Electronic Journal*. https://doi.org/10.2139/ssrn.2580664

[58] Presto Research. (2024). State of the Japanese Crypto Market. https://www.prestolabs.io/research/state-of-the-japanese-crypto-market

[59] Chainalysis. (2020). Japan's Cryptocurrency Regulation Updates: What You Need to Know. https://www.chainalysis.com/blog/japan-cryptocurrency-regulation-updates-2020/

[60] Finance Magnates. (2026). Has Europe Killed Crypto Perps Even before It Started? https://www.financemagnates.com/forex/10x-down-to-2x-has-europe-killed-crypto-perps-even-before-it-started/

[61] Financial Services Commission (Korea). (2025). *Guidelines on Virtual Asset Lending Services*. (Issued September 2025; prohibits leveraged borrowing in excess of collateral value, with a 20% cap on the lending rate.)

[62] Kaiko Research. (2024). Isolationary regulation, a double-edged sword. https://research.kaiko.com/insights/isolationary-regulation-a-double-edged-sword

[63] Feinstein, B. D., & Werbach, K. (2021). The Impact of Cryptocurrency Regulation on Trading Markets. *Journal of Financial Regulation*, *7*(1), 48–99. https://doi.org/10.1093/jfr/fjab003

[64] Saggu, A., Ante, L., & Kopiec, K. (2025). Uncertain Regulations, Definite Impacts: The U.S. SEC's Regulatory Interventions and Their Effects on Crypto Assets. *Oxford Business Law Blog*. https://blogs.law.ox.ac.uk/oblb/blog-post/2025/01/unintended-consequences-sec-crypto-enforcement-actions

[65] Stigler, G. J. (1971). The theory of economic regulation. *The Bell Journal of Economics and Management Science*, *2*(1), 3-21.

[66] Peltzman, S. (1976). Toward a more general theory of regulation. *Journal of Law and Economics*, *19*(2), 211-240. https://doi.org/10.3386/w0133

[67] Giorno, T., & Sayki, I. (2023). Cryptocurrency industry lobbying and political contributions skyrocketed in 2022. *OpenSecrets News*. https://www.opensecrets.org/news/2023/03/cryptocurrency-industry-lobbying-and-political-contributions-skyrocketed-in-2022

[68] Reklaitis, V. (2024). Crypto industry's lobbying hit a record in 2023 — and is off to a strong start in 2024. *MarketWatch*. https://www.marketwatch.com/story/crypto-industrys-lobbying-hit-a-record-in-2023-and-is-off-to-a-strong-start-in-2024-fa740b43

[69] Yaffe-Bellany, D., & Flitter, M. (2023). FTX Chief Once Met With Powell. Now D.C. Crypto Lobbyists Are Lying Low. *The New York Times*. https://www.nytimes.com/2023/09/27/business/economy/crypto-lobbying-washington-ftx.html

[70] Yablon, C. M. (2024). Crypto: The Prospect of Regulatory Competition. *Cardozo Law Review*, *45*(4), 1435-1489.

[71] Huang, R. H., Yang, D., & Loo, F. F. Y. (2020). The development and regulation of cryptoassets: Hong Kong experiences and a comparative analysis. *European Business Organization Law Review*, *21*(2), 319-347.

[72] Burgess, T., & Liu, J. (2025). A tale of two jurisdictions: Contrasting cryptocurrency regulations in Hong Kong and the United Kingdom. *Journal of Economic Criminology*, *10*, 100026. https://doi.org/10.1016/j.jeconc.2025.100150

[73] Posner, E., & Weyl, E. G. (2013). Benefit-cost analysis for financial regulation. *American Economic Review*, *103*(3), 393–397. https://doi.org/10.1257/aer.103.3.393

[74] Chainlink. (2026). *Payments compliance in the blockchain era*. https://chain.link/article/payments-compliance-blockchain