Preparing NFT Treasuries for Tail Risk: Lessons from Bitcoin Options’ Negative-Gamma Setups

Bitcoin’s spot chart can look calm right up until it doesn’t. That is the core lesson NFT treasurers, DAO operators, and marketplace risk teams should take from the current options backdrop: when dealers are short downside convexity, small drops can trigger forced hedging, and forced hedging can accelerate the drop. Recent reporting on Bitcoin options shows traders paying up for protection while market makers sit in a negative gamma environment below key levels, a structure that can convert ordinary selling into a self-reinforcing feedback loop. For NFT platforms managing mint proceeds, protocol reserves, creator royalties, or treasury war chests, the practical implication is simple: you need treasury sizing, cloud-native control systems, and defensive hedges that assume a sharp drawdown will arrive when liquidity is thinnest, not when everyone is prepared.

In this guide, we will translate Bitcoin options behavior into a concrete risk framework for NFT organizations. We will cover how to size reserves, how to design a liquidation buffer, when to use derivatives hedges, and how to automate triggers so the treasury can defend itself without relying on human reaction time. Along the way, we’ll connect treasury design to operational resilience, compliance, and identity controls, borrowing useful lessons from secure identity solutions, EU regulatory planning, and even the discipline of stress testing budgets in volatile environments.

1. Why Negative-Gamma Matters to NFT Treasuries

Negative gamma is a volatility amplifier, not just a trader term

Gamma describes how quickly an option hedge must be adjusted as the underlying asset moves. When market makers are short gamma, they tend to buy as prices rise and sell as prices fall, which can smooth markets when they manage to stay balanced and destabilize them when the move starts running away. In practice, that means a level that looks like simple support on a chart can become a trapdoor if dealer positioning forces additional selling into the decline. Bitcoin’s recent options setup, with implied volatility elevated relative to realized volatility, suggests participants are paying for insurance even while spot looks subdued. That tells treasury teams to stop reading calm price action as safety.

For NFT treasuries, the analogy is not abstract. If your reserve policy assumes assets can always be liquidated in a stable market, you are effectively pricing risk as if the order book were deep and patient every day. In a selloff, that assumption breaks first. NFTs themselves are even more fragile than BTC in many cases because liquidity is thinner, bid depth is more fragmented, and floor prices can gap suddenly when confidence slips. That is why treasury planning should incorporate tail risk, not just average case volatility.

Dealer hedging can turn a selloff into a cascade

The reason negative gamma matters operationally is that it creates reflexivity. If Bitcoin falls through a heavily watched strike, market makers who sold downside protection may have to sell more BTC to keep risk neutral, which adds pressure and can force another round of hedging. This is the “self-reinforcing feedback loop” now being discussed in the options market. For NFT platforms holding treasuries in volatile assets, the same pattern can happen when treasury sells are done mechanically into a falling market without buffer rules or staged execution. A treasury that must meet payroll, grants, or redemption obligations cannot wait for the market to recover if it is already being pulled lower by its own liquidation activity.

That is why the right mental model is not “Can we survive a 20% move?” but “What happens if a 20% move triggers forced sales from us and from everyone else at the same time?” This is the essence of price volatility in any thin market: the first move is often smaller than the second. NFT organizations should treat treasury liquidity as a system property, not a balance sheet footnote.

Tail risk is a governance issue, not only a trading issue

Tail risk becomes a governance problem once treasury decisions affect salaries, vendor payments, ecosystem incentives, and the credibility of the platform itself. A DAO that cannot fund grants because it sold liquid reserves at the wrong time may experience a governance crisis long after the market stabilizes. Similarly, a marketplace that cannot honor operational obligations during drawdown may be forced to cut services or delay settlements. This is why treasury policy needs board-level or DAO-level approval, with clear risk thresholds and documented contingency actions. If the policy is vague, humans will improvise under stress, and improvisation during a crash is where losses compound.

Pro Tip: Size your treasury as if two things happen at once: asset prices fall and your access to liquidity worsens. In crypto, those events are usually correlated, not independent.

2. What Bitcoin Options Are Signaling Right Now

Implied volatility is telling you protection is expensive

According to the report grounding this analysis, Bitcoin implied volatility has been holding in the 48% to 55% range while realized price swings remain much quieter. That spread means the options market is pricing meaningful risk ahead, even though spot has not yet confirmed it. In practical terms, market participants are willing to pay for insurance because they see the possibility of a move that current price action does not reveal. NFT treasury managers should read that as a warning that “nothing is happening” can be the most dangerous phase of the cycle. The market is often calmest just before a regime change.

For treasuries, this suggests that buying protection late is expensive, but waiting for confirmation is often worse. If your organization relies on liquid reserves to cover 6 to 12 months of operating needs, the cost of hedging a portion of those reserves is often much lower than the cost of forced liquidation in a crash. The decision is less about maximizing upside and more about preserving operational continuity. That makes the case for systematic hedging programs rather than ad hoc emergency responses.

Weak demand and thin participation make downside more fragile

The cited market report also points to weakening spot demand and reduced participation, leaving Bitcoin in what it calls a fragile equilibrium. That matters because a market with fewer committed buyers can move much faster when a large seller arrives. NFT ecosystems often face the same condition during quiet periods: fewer active traders, lower collection turnover, and a concentrated set of holders with very different time horizons. In those environments, a single distressed sale can distort the floor, especially if market makers or liquidity providers step back at the same time. The fact pattern is familiar to anyone who has seen marketplaces fail to prove depth before capital is deployed.

For this reason, treasury policy should not assume a constant liquidation discount. If you need to liquidate NFTs, governance tokens, or protocol-owned assets during stress, expected slippage should be modeled under thin-book conditions. A conservative treasury team should calculate outcomes using stressed bids, not last-traded prices. That is the difference between a reserve and a false comfort number.

Support levels matter because they attract reflexive positioning

Bitcoin’s reported downside zone below $68,000 is important not because a number on a chart is magical, but because widely watched levels can become triggers for hedging and liquidation. In crypto, support is often as much about positioning as it is about valuation. When a market breaks a visible level, discretionary traders, quant funds, and market makers can all react at once, magnifying the move. NFT treasuries should think the same way about their own buffers. If your stablecoin reserve floor is too close to the minimum operating requirement, a modest drawdown can leave no room to respond.

That is why treasury teams should define “action levels” above actual danger levels. For instance, if a platform needs $2 million in six-month operating liquidity, it should not set its emergency action trigger at $2 million. It should create a preemptive trigger at perhaps $2.6 million or $3 million, depending on volatility and obligations, so defensive measures begin before the treasury enters the danger zone. This margin of safety is the treasury equivalent of a liquidation buffer.

3. Building an NFT Treasury That Can Survive a 40% Drawdown

Separate operating cash from risk capital

The first treasury design principle is separation. Operating cash should be held in assets that are highly liquid, highly stable, and immediately accessible, while risk capital can be allocated to assets with more volatility or upside potential. For NFT platforms and DAOs, that usually means keeping a core reserve in stablecoins or short-duration cash equivalents, then allocating a smaller sleeve to ecosystem assets, collector funds, or long-duration strategic positions. This is not a pessimistic framework; it is a survivability framework. If you blur the line between runway and investment capital, you create a hidden liquidity mismatch.

A practical example: a marketplace with monthly burn of $400,000 and a 12-month policy target should not hold all $4.8 million in speculative assets simply because those assets performed well in a bull market. Instead, the treasury might keep 9 to 12 months of operating runway in stablecoin reserves, with a separate strategic sleeve for acquisitions, partner incentives, or yield generation. When risk rises, the operational reserve should stay untouched. If you need background on structuring multi-stage response systems, the logic resembles multi-layered recipient strategies: the critical layer must remain insulated from the experimental layer.

Use scenario-based sizing, not point estimates

Treasure sizing should be tested under multiple market paths: shallow drawdown, deep drawdown, and drawdown plus liquidity freeze. A shallow drawdown might be 15% to 20%, a deep drawdown 35% to 50%, and the worst case should include delayed access to exchanges, wider spreads, and temporary stablecoin dislocations. If a DAO’s obligations remain fixed while assets fall sharply, the reserve must absorb both mark-to-market losses and execution friction. That is why a simplistic “we hold six months of expenses” policy can fail in practice. It ignores the second-order effects that emerge during stress.

One useful approach is to define a survival ratio: liquid stable reserves divided by stressed monthly obligations. For many crypto-native organizations, a ratio below 6x in volatile periods is dangerously thin. Better yet, build a tiered policy where reserves above 12x expenses can be deployed opportunistically, but reserves below 9x automatically trigger de-risking. This turns treasury policy into an operating system rather than a quarterly discussion.

Model correlation, not just volatility

Crypto treasury losses often happen because assets that appear diversified are actually highly correlated when it matters most. Governance tokens, NFT floor prices, ETH-denominated revenues, and even treasury yield strategies can all decline together during a broad risk-off event. If your NFT platform uses ETH for fees but pays expenses in stablecoins, a BTC-led drawdown may still reduce user activity, royalties, mint demand, and token liquidity all at once. That is correlation risk, and it is why tail-risk planning must include cash-flow analysis, not only asset-price analysis.

In practice, this means mapping every treasury asset and liability by sensitivity to BTC, ETH, stablecoin depegs, and exchange liquidity. If your liabilities are fiat-linked while your assets are crypto-linked, your treasury has a hidden short-volatility posture. That posture becomes dangerous exactly when implied volatility is already expensive, which is why many teams end up buying protection after the market has started moving. A better process is to budget for insurance continuously, much like cloud platforms budget for peak load rather than average load.

4. Designing a Liquidation Buffer That Prevents Forced Sales

The liquidation buffer is your first line of defense

A liquidation buffer is the distance between your normal operating reserve and the point at which you must sell risk assets under pressure. The wider the buffer, the more options you have when markets break. For NFT treasuries, the buffer should be large enough to cover not just scheduled expenses, but also emergency payouts, delayed settlements, or a revenue drought caused by a market panic. If the treasury is forced to sell collectibles or governance tokens at the same time users are rushing to exit, prices can deteriorate much faster than basic models predict. That is how a treasury problem becomes a brand problem.

To design the buffer, start by classifying obligations into three buckets: mission-critical, deferrable, and optional. Mission-critical items include payroll, security vendors, audit fees, and legal obligations. Deferrable items include grants, ecosystem incentives, and discretionary partnerships. Optional items include buybacks, campaign spend, and speculative investments. The liquidation buffer should be sized to cover mission-critical obligations under a severe but plausible stress scenario, with deferrable items paused automatically.

Predefine what gets sold, in what order, and under what conditions

A treasury should not decide in a panic which assets to sell first. Instead, establish a ranked liquidation ladder ahead of time. The ladder might begin with idle stablecoin yield positions, then short-duration liquid assets, then strategic assets, and only then illiquid NFTs or governance tokens. This ordering reduces the chance that you sell the wrong asset at the worst time. It also improves governance because stakeholders know the playbook before the crisis begins. For additional thinking on operational vetting, the discipline resembles vetting a marketplace before capital is committed in an uncertain environment.

The ladder should also define lot size and execution method. Large one-shot sales often move the market against you, especially when market makers are already de-risking. Smaller sliced executions, time-weighted selling, and OTC workflows can reduce slippage. If the treasury needs to exit quickly, an OTC desk or structured venue may preserve more value than a public sell into thin order books. The goal is not just to liquidate; it is to liquidate with as little market impact as possible.

Build a drawdown trigger matrix

Trigger matrices make the buffer operational. For example, at 15% portfolio drawdown, the treasury may pause discretionary spend and increase monitoring frequency. At 25%, it may reduce risk exposure and extend stablecoin coverage. At 35%, it may suspend grants and initiate predefined hedges. At 45% or more, it may activate a full defensive plan, including asset liquidation and counterparty review. These thresholds should be based on the organization’s cash-flow profile and not copied from a generic template.

Because NFT platforms often have non-linear revenue, the trigger matrix should incorporate volume decline, user activity decline, and settlement risk as well as asset prices. Revenue can fall faster than TVL or market cap. A treasury can look healthy on paper while the business beneath it is already deteriorating. That is why drawdown triggers must include both financial and operating metrics.

5. Derivatives Hedges for NFT Platforms: What Works and What Does Not

Use hedges to protect survival, not to chase returns

Derivatives hedges should be treated as insurance, not as a profit center. The purpose is to reduce the probability that a sudden drawdown forces destructive behavior. Common tools include put options, put spreads, collars, futures shorts, and cross-asset hedges. The best choice depends on the treasury’s exposure, budget, and governance constraints. If your organization needs downside protection but cannot tolerate unlimited mark-to-market swings, a defined-risk structure is usually better than naked futures exposure.

For NFT platforms, direct hedging of individual NFT floors is often impractical because liquidity is poor and markets are fragmented. In many cases, it is more effective to hedge the underlying crypto exposure that drives the broader ecosystem, such as ETH or BTC, while separately increasing stablecoin reserves. That does not eliminate collection-specific risk, but it reduces the probability of a market-wide liquidity event feeding back into your treasury. To understand the operational side of building controls around this kind of risk, it is useful to study secure sharing of sensitive logs: the hedge program needs access, auditability, and clear permissions.

Match hedge tenor to cash needs

A hedge only helps if it is alive when you need it. Many teams buy protection with the wrong tenor, then find that the hedge expires before the stress event actually develops. In a regime where negative gamma can accelerate a move, the crucial risk window may be short, but the broader drawdown can last weeks. Treasuries should ladder hedges across maturities to protect near-term obligations and allow flexibility if volatility persists. One month may protect against an imminent flush, while three to six months can cover a longer de-risking cycle.

Tenor selection should also account for volatility term structure. If near-term implied volatility is elevated, longer-dated protection may be comparatively efficient. Conversely, if the market is already pricing a sudden event, a staggered program can avoid concentrating premium spend at one point on the curve. This kind of discipline mirrors how teams manage rapid platform shifts and changing user behavior in other sectors, such as responsive content strategy during major events.

Avoid hedges that create liquidity traps

Some hedges solve one problem by creating another. For example, futures shorts can protect value but require margin management, and if the market rebounds sharply or funding dynamics move against you, the hedge can become an operational burden. Similarly, complex structured products may look efficient on paper but hide counterparty, settlement, or accounting risk. NFT treasuries should prefer hedges that are understandable, auditable, and compatible with existing governance processes. In a compliance-heavy setting, the most elegant derivative is often not the safest one.

That is especially true for organizations that operate across jurisdictions. If treasury controls must satisfy auditors, tokenholders, and legal counsel, you need a hedge program with clear policy language and repeatable approvals. For a broader view of how rules shape technical design, compare the challenge to emerging governance rules in regulated markets. The lesson is that good risk management is as much about process design as it is about instruments.

6. Automating Defensive Hedges and Treasury Controls

Automation reduces reaction time and emotional decision-making

In a negative-gamma selloff, time matters. Prices can move faster than committees can meet. That is why treasury defense should be partially automated through policy engines, alerts, and preapproved execution paths. When a threshold is crossed, the system should notify the right people, calculate the required actions, and, where permitted, initiate hedges or liquidity conversions. Automation does not replace governance; it enforces governance when humans are under stress.

The best automation stacks include data feeds from spot markets, options volatility, stablecoin health, treasury balances, and on-chain transaction monitoring. They also include role-based approval workflows so execution is fast but not reckless. Think of it as a cloud control plane for risk management. If you want a model for scalable system design, the logic is similar to streamlining cloud operations with strong tab or context management: the operator should see what matters now and what must happen next.

Set alerts on volatility, not just price

Price alone is a lagging signal. A more advanced setup watches for rising implied volatility, widening bid-ask spreads, falling open interest quality, and abnormal funding or skew changes. If implied volatility rises while realized volatility remains muted, that can be an early clue that protection is being accumulated and tails are being repriced. For NFT treasuries, that’s the moment to inspect exposure, not after the market has broken support. Monitoring should also include market maker behavior, because dealer positioning often tells you more about future liquidity than headline price moves do.

In practical terms, a treasury risk dashboard should surface three state variables: liquidity, convexity, and runway. Liquidity tells you what you can move immediately. Convexity tells you whether your exposures will help or hurt as volatility rises. Runway tells you how long the organization can function without a capital raise or a recovery in revenue. If any of the three deteriorate simultaneously, defensive action should be automatic.

Keep compliance, audit, and permissions baked in

Automating defenses without controls creates a new risk surface. Every hedge, sale, and policy override should be logged, reviewable, and tied to clear authorization rules. That matters for DAOs with multi-signature governance as well as for centralized teams with board oversight. It also matters for tax and accounting treatment, since derivative gains, losses, and liquidation events must be documented precisely. Good control design can be inspired by privacy-first pipeline design: move only what is necessary, retain what is required, and protect sensitive data end to end.

From a trust perspective, automation should produce not just actions but evidence. If the treasury uses a hedge or triggers an emergency liquidation, stakeholders should be able to review why the action occurred, what policy threshold was crossed, and what the expected effect was. That transparency turns risk management into a defensible operating capability rather than a black box.

7. Market Maker Behavior, Liquidity, and the NFT Floor Price

Market makers do not stabilize markets for free

Market makers provide liquidity when they can earn spread and manage inventory risk, but in stress conditions they tend to reduce exposure, not add it. In a negative-gamma setup, they may even sell into weakness as they rebalance hedges. NFT treasuries often assume that market makers will always be there to smooth the exit. That assumption is dangerous. When volatility spikes, the same participants who support normal market function may step back or actively pressure price as they protect their books.

This means floor prices can gap, especially for collections with concentrated ownership or weak active bidding. It also means a treasury should never use an optimistic spot floor as the sole basis for reserve planning. A more robust plan uses stressed liquidity assumptions, discount factors for forced sale, and a separate valuation for strategic versus liquid assets. The difference between those values is your hidden risk. If you need a parallel from consumer markets, look at how buyers behave when markets catch their breath: shallow enthusiasm is not the same as real depth.

Liquidity evaporates fastest where narratives are strongest

One of the hardest lessons in crypto is that assets with the strongest community narratives can still have the weakest crisis liquidity. During good times, holders are committed and price is sticky. During drawdowns, those same holders may simultaneously seek the exits, and market support can disappear. NFT treasuries that hold their own ecosystem tokens or large collection inventories are particularly exposed because their asset value and business health can be tightly linked. That is a correlated tail risk that should be explicit in treasury policy.

To protect against this, teams should segment inventories and understand which holdings are core strategic assets versus monetizable reserve assets. Core assets may be illiquid but important to the brand. Reserve assets should be chosen for depth and saleability. If both categories are mixed together, a selloff can damage the community while still failing to produce enough cash. That is why risk management and brand management must be planned together, not in separate silos.

Plan for the probability that your own tokens become the weak bid

If your platform or DAO has a native token, its behavior in a drawdown may be more fragile than BTC because it has fewer natural buyers and more immediate reflexivity. Treasury teams should assume that native tokens may become the easiest source of liquidity and the worst asset to sell. That paradox matters: selling too much native token in a panic can weaken governance, depress incentives, and create a perception of distress. The result is often a deeper crisis than the original market move.

The solution is to predefine token-sale limits, time windows, and review requirements. If the token is a funding source, a staged plan should determine how much can be sold per week, under what volatility conditions, and with what disclosure. When possible, replace panic sales with programmed liquidity plans or hedges that monetize downside without immediately flooding the market. That makes the treasury more resilient and the ecosystem more credible.

8. A Practical Tail-Risk Playbook for NFT Platforms and DAOs

Step 1: Map exposures and obligations

Start with a full inventory of assets, liabilities, and contingent obligations. Include stablecoins, ETH, BTC, governance tokens, NFTs, vendor contracts, grants, payroll, tax obligations, and any commitments that could accelerate under stress. Then map each item to its liquidity profile and correlation to a market drawdown. The objective is to understand not just what the treasury owns, but what it owes and when. This is the foundation of any serious data-driven procurement or treasury process.

Once the map is complete, simulate the worst plausible month. Assume revenue drops, asset prices fall, stablecoin yields compress, and execution costs rise. If the treasury still has sufficient liquidity after those assumptions, the policy is probably resilient. If not, you have identified where to add reserves, cut spending, or hedge. The key is to make the scenario real enough that the response is operationally useful, not just theoretically elegant.

Step 2: Establish reserve and buffer thresholds

Define minimum stablecoin reserves, liquidation buffer targets, and emergency action levels. Many organizations should target at least 9 to 12 months of essential operating expenses in highly liquid reserves if they are exposed to volatile revenue or token-linked assets. If that is not feasible, the shortfall should be offset with stronger hedges, lower burn, or a preapproved credit or financing line. A stable reserve is the simplest defense against forced selling.

These thresholds should be reviewed quarterly and recalibrated when volatility regimes change. If options markets are pricing tail risk aggressively, you should raise the buffer. If revenues weaken or concentration increases, you should raise it further. Treasury policy should be dynamic, because the market is dynamic.

Step 3: Automate triggers, reporting, and approvals

Set up policy triggers tied to drawdown, volatility, liquidity, and revenue metrics. When a trigger is hit, the system should generate a report, notify owners, and initiate the approved defensive workflow. This might mean pausing spending, converting risk assets into stablecoins, buying puts, or reducing exposure to correlated positions. The exact mix will depend on the organization, but the workflow should be pre-agreed. A well-designed workflow is the difference between controlled defense and disorderly liquidation.

Just as teams must adapt to changing platform realities in software update cycles, treasury controls must be resilient to changing market structure. Manual-only systems are too slow for a negative-gamma tape. If the organization cannot react within hours, it should design for automated partial defense and human confirmation for the rest.

Step 4: Review, audit, and test the plan

Finally, test the plan like a fire drill. Run tabletop exercises with finance, ops, legal, product, and governance stakeholders. Test what happens if the price falls 20% overnight, if the stablecoin reserve is temporarily inaccessible, or if a derivative venue experiences delays. Document the decisions and the timing. After the exercise, revise the policy based on what failed, not on what sounded good in the room.

This habit is what turns risk management into institutional memory. Without testing, every new market shock becomes a first-time event. With testing, the organization develops muscle memory that can survive the kind of feedback loop negative gamma creates.

9. Case Study: How a DAO Can Avoid a Forced Sale Spiral

The setup

Imagine a DAO with $8 million in assets: $3 million in stablecoins, $2 million in ETH, $2 million in governance tokens, and $1 million in illiquid NFTs. Monthly spend is $350,000, and the DAO funds grants every quarter. During a BTC-led selloff, ETH falls 18%, NFT floor prices drop 30%, and the governance token falls 35%. Trading volume also collapses, so selling pressure impacts price far more than expected. This is exactly the kind of environment where negative gamma in the broader market can amplify local treasury stress.

If the DAO had no liquidation buffer, it might try to meet expenses by selling governance tokens at the worst possible time. That sale depresses the token further, damaging voting confidence and ecosystem sentiment. Meanwhile, the market recognizes the forced sale and front-runs it. The result is a spiral that is financial, not just mechanical.

The better response

Now imagine the DAO had a policy requiring 10 months of essential expenses in stablecoin reserves, a 25% drawdown trigger for spending cuts, and a 35% trigger for hedging and reserve conversion. The DAO would pause grants, preserve stablecoins, and hedge the ETH sleeve using preapproved options. Because actions are staged, the DAO avoids panic sales and keeps its core governance token intact. The market may still fall, but the DAO does not become a forced seller into the decline.

This is the practical difference between surviving tail risk and being consumed by it. The market can always move against you. The question is whether your treasury moves with discipline or with desperation.

What NFT platforms can learn from it

Platforms with creator funds, operating reserves, or launchpad treasuries should adopt a similar sequence. Separate reserves, stage action thresholds, protect operating liquidity, and ensure every sale has a reason. If the organization operates a marketplace, it should also consider user trust impacts if it visibly sells assets into a falling market. Defensive hedging can protect not just balance sheet value but also credibility. That is crucial in markets where users can quickly compare your behavior against peers, much like teams compare product execution across unique platform launches.

10. Conclusion: Treat Treasury as a Risk Engine, Not a Vault

Bitcoin options are reminding the market that quiet price action can hide violent positioning underneath. Negative gamma means selling can beget more selling, and that dynamic is especially dangerous for NFT treasuries that depend on liquidity, confidence, and operational continuity. The answer is not to avoid risk altogether. The answer is to design a treasury that can absorb shocks without turning into a forced seller. That requires stablecoin reserves sized for the real burn rate, liquidation buffers large enough to absorb slippage, derivatives hedges that are simple and auditable, and automation that reacts faster than a committee can.

For NFT platforms, DAOs, and marketplaces, tail-risk readiness is now a competitive advantage. Teams that can survive deep drawdowns will have more room to build, more credibility with users, and fewer existential surprises when the market turns. If you want to go deeper on operational controls, liquidity vetting, and secure treasury workflows, review our guides on data privacy and legal risk, automation under complexity, and reliable tracking when platforms change. In crypto, the strongest treasury is not the one that wins the most in a bull market. It is the one that still functions when the tail arrives.

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