When people talk about @Injective , they usually focus on execution: fast blocks, on-chain order books, multiple VMs, derivatives everywhere. That is the exciting part. But as soon as you start running real, multi-leg strategies across several venues on the same chain, a much less glamorous question appears: how do you standardize margin and PnL so that everything adds up in one coherent picture? Without that, even the best trading stack quickly becomes a maze of incompatible sub-accounts, custom funding formulas and ad-hoc spreadsheets.
On a single #injective address today you can imagine holding spot positions, perps, maybe RWAs, plus exposures created via smart contracts in different VMs. From a chain perspective it is “one portfolio”; from the perspective of each venue, it is a fragmented set of siloed ledgers. One market might use isolated margin, another cross margin, a third some hybrid credit approach. Each may have its own definition of realized vs unrealized PnL, its own way of streaming fees and funding. For simple users that is annoying; for institutions and complex strategies it is a real barrier to sizing risk rationally.
The first thing a standardized framework would do is flip the mental model: positions live at the account level, not at the venue level. In other words, the canonical source of truth about margin and PnL is a chain-native “portfolio account” that all venues read from and write to. Spot modules, perp markets, options engines, structured-product contracts – they still run their own logic, but any time they change a user’s exposure, they also emit a standardized update into this shared accounting layer. The portfolio account becomes the spine; venues become producers of events.
To support that, $INJ L1 would need a common schema for positions. Think in terms of a minimal, chain-level object: instrument ID, side, size, entry price(s), mark price, realized PnL, unrealized PnL, and a risk weight. Each venue can add extra fields for its own needs, but the core schema stays consistent. That schema is what portfolio margin engines and risk dashboards consume. A perp leg and an RWA swap leg may have very different details, yet they present the same basic interface to the portfolio: “here is how much this adds or subtracts from your equity and risk.”
Margin standardization builds on that. Instead of every venue inventing its own notion of “available balance,” the L1 can define a canonical set of balances per account: raw collateral, haircut collateral, maintenance margin requirement, initial margin requirement, and excess. Venues then express their needs in those terms: “this new order will increase your maintenance requirement by X and your initial requirement by Y.” The portfolio engine checks whether the global account can afford it. You still can have isolated sub-accounts for certain strategies, but they are explicit sub-trees of the same tree, not entirely separate worlds.
For complex strategies, sub-accounts and “strategy tags” become essential. A single trader might run market-making, directional swing trades and structured notes from the same wallet. In a standardized framework, each position update can carry a strategy tag or sub-account ID. Margin is still managed at the parent-portfolio level, but PnL can be sliced by tag for reporting, risk and performance. That means you can ask very natural questions on-chain: “how much did my delta-neutral basis strategy make this month, net of fees across all venues?”, and actually get a consistent answer.
PnL itself needs a shared language. Different venues might choose different pricing sources – last trade, bid/ask mid, oracle – but the type of PnL event should be standardized. Mark-to-market change, realized close-out, funding payment, fee, rebate, revaluation due to parameter change: each gets its own code. Whenever a venue changes your equity, it must emit one of these codified PnL events into the portfolio module. That allows both humans and automated systems to reconstruct why an account moved over time without reverse-engineering a dozen idiosyncratic logs.
Funding and carry are particularly important in a chain whose identity is “built for derivatives.” Here, standardization means agreeing on a few core things: the time granularity of funding (block-based, per-interval), how notional is computed, and how funding interacts with margin and realized PnL. Once those rules are encoded at L1, any venue implementing funding does so through the same hooks. A trader can then safely aggregate funding flows from different markets, confident they all follow the same calculus, even if the actual funding rates differ.
Cross-venue liquidation is where unified accounting really proves its worth. In a fragmented world, each market decides independently when an account is unsafe and pulls the plug on its own positions. In a unified model, the portfolio engine keeps a global view: if total equity falls below maintenance, it can orchestrate a sequence of actions – reduce risk where it is cheapest to do so, close hedges in a coordinated way, and only then touch core positions. That is impossible unless every venue reports its positions and margin demands into the same standardized engine.
From an institutional perspective, standardized PnL and margin is the difference between “interesting playground” and “allocatable venue.” Funds need to produce reports, audit trails and risk snapshots that auditors and regulators can understand. If Injective L1 offers a canonical API – directly from the chain – to export account-level PnL by day, by strategy, by venue tag, with clear classifications of cashflows, it removes a huge amount of bespoke reconciliation work. At that point, integrating Injective into existing middle-office systems becomes almost as straightforward as plugging in another prime broker.
This is also about developer experience. Builders today who want to launch a new derivatives dApp on Injective face a choice: either build their own margin and accounting layer (and accept that users must mentally reconcile yet another set of balances), or try to bolt onto existing venue logic. A standardized L1 portfolio module gives them a third option: focus on pricing, matching and UX, and plug into shared margin/PnL semantics for everything else. That lowers the barrier to experimentation while keeping user risk surfaces coherent.
Of course, there are trade-offs. The more logic you centralize in a core module, the larger the trust and complexity surface becomes. Some venues will need features the standard does not support yet; others will want exotic PnL semantics. The answer is not to freeze the kernel, but to version it and to allow a “fallback mode” where truly exotic products maintain their own internal ledger while still feeding minimal risk and PnL signals into the common layer. That way the standard covers 80–90% of needs, while the tail of innovation doesn’t get blocked.
Governance will have to play a role in evolving the standard. Defining risk weights, margin formulas and PnL codes is not just a technical exercise; it encodes a philosophy of how aggressive or conservative the whole ecosystem should be. Over time, the community can iterate on these constants and schemas, just as traditional clearing houses adjust their models. The key is that changes happen out in the open, at the protocol level, instead of every venue quietly redefining risk and PnL in its own corner.
If #injective leans into this vision, “standardizing cross venue margin and PnL accounting” becomes more than a backend refactor. It turns the chain into something closer to a universal clearing layer for its own ecosystem: one account, many venues, one coherent view of risk and performance. For users, that means less time reconciling numbers and more time thinking about actual strategy. For builders, it means they can innovate on edges of the product space without dragging around a full back-office in their contracts. And for institutions, it means looking at Injective not just as a fast execution environment, but as a place where complex, multi-venue strategies can be run with the same level of clarity and discipline they expect from traditional finance – perhaps even better.
