# Arbitrage Economics: Edge vs Cost {% hint style="info" %} Operator and jurisdiction: BASIS is operated by BASIS DIGITAL INFRASTRUCTURE LTD, a Seychelles IBC (LEI: [254900IX2F2KCWNSSS64](https://lei.bloomberg.com/leis/view/254900IX2F2KCWNSSS64)). Research Partner: Base58 Labs contributes execution research, systems modeling, and risk design. {% endhint %} Most spread-trading summaries stop at "buy low, sell high." Real execution begins after that. The relevant question is whether an observed gap has positive expected value after fees, slippage, latency drag, settlement cost, and residual tail risk. This page defines the economics model BASIS uses to approve or reject a structural alpha capture slice. {% hint style="success" %} ⚙️ Execution environment BASIS runs BHLE with sub-50μs decision latency, 100K+ OPS throughput, and proprietary routing infrastructure. Faster routing reduces execution decay, but no trade bypasses the expected value gate. {% endhint %} ## 1) Formal expected value model For any opportunity, BASIS gates execution on expected value: $$ EV = E\[\text{Edge}] - \sum C\_{\text{trade}} - R\_{\text{premium}} $$ | Variable | Meaning | | ------------------------ | ---------------------------------------------------------------------------- | | $E\[\text{Edge}]$ | Expected gross profit from an observed spread, basis, or funding dislocation | | $\sum C\_{\text{trade}}$ | Total direct and indirect execution costs | | $R\_{\text{premium}}$ | Additional premium for unhedgeable or tail risk | {% hint style="info" %} Rule: BASIS initiates a trade only when $EV > 0$ under conservative parameters. {% endhint %} ``` Decision rule if expected_edge - total_trade_costs - risk_premium > 0 and venue_limits_pass and inventory_limits_pass and state_machine_checks_pass: route_order() else: reject_slice() ``` ## 2) Cost and risk decomposition {% tabs %} {% tab title="Cost stack" %} | Component | Description | BASIS treatment | | -------------------- | --------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | | $C\_{\text{fees}}$ | Explicit venue charges such as maker, taker, funding transfer, or withdrawal cost | Direct deduction from expected edge | | $C\_{\text{slip}}$ | Price impact from consuming liquidity | Function of trade size, venue depth, queue position, and volatility | | $R\_{\text{lat}}$ | Risk that the edge compresses before hedge completion | Penalty that rises with observed latency and market velocity | | $R\_{\text{settle}}$ | Cost and risk of moving inventory across venues or chains | Includes gas, delay, operational friction, and settlement failure probability | | $R\_{\text{cpty}}$ | Venue or protocol failure risk | Managed through venue scoring, exposure caps, and concentration limits | | {% endtab %} | | | {% tab title="Execution controls" %} BASIS applies math-constrained routing before any order is released: * deterministic execution paths * state machine risk controls * venue exposure ceilings * inventory bounds * route quality scoring * minimum executable size checks * throttle and pause logic during volatility spikes These controls prevent displayed edge from being mistaken for executable edge. {% endtab %} {% endtabs %} ## 3) Slippage inversion: when not trading is correct A common execution failure is slippage inversion: $$ \sum C\_{\text{trade}} \geq E\[\text{Edge}] $$ At that point, the trade is loss-making by construction, even if the displayed spread still looks attractive. BASIS refuses these slices. The risk engine can pause, throttle, or reduce order size when liquidity deteriorates or volatility rises and the slippage estimate expands. {% hint style="warning" %} Skipping a trade is often the correct outcome. Deterministic rejection is a feature of execution precision, not a missed opportunity. {% endhint %} ## 4) Inventory and capital cost The model also prices inventory risk. * In derivatives strategies, inventory cost often appears through funding. * In spot strategies, inventory cost appears as opportunity cost and temporary directional exposure. * More volatile inventory requires a larger premium, which reduces the set of acceptable slices. This follows the same intuition developed in optimal market-making literature: inventory is not neutral, and holding it even briefly should be priced into the decision. ## 5) How BASIS evaluates a slice {% stepper %} {% step %} Observe the raw spread, basis, or funding dislocation. {% endstep %} {% step %} Estimate executable size using live depth, queue state, and route quality. {% endstep %} {% step %} Subtract direct costs, including fees and expected slippage. {% endstep %} {% step %} Apply latency, settlement, counterparty, and inventory premiums. {% endstep %} {% step %} Run deterministic state machine checks for exposure, concentration, and route safety. {% endstep %} {% step %} Route only if the resulting $EV$ remains positive. {% endstep %} {% endstepper %} ## 6) Why this framework improves trust A formal EV gate converts spread capture into something that can be reasoned about and audited. It makes three points explicit: * Not every displayed spread is a real opportunity * Risk has a quantifiable price * Forced execution is usually worse than selective execution Within BASIS, this framework sits inside the execution and risk stack that supports structural alpha capture. The combination of BHLE routing, deterministic execution, and state machine risk controls is designed to preserve edge quality under real market conditions. *** ## References \[1] Kyle, A. S. (1985). "Continuous Auctions and Insider Trading." Econometrica, 53(6), 1315-1335. \[2] Avellaneda, M., and Stoikov, S. (2008). "High-frequency trading in a limit order book." Quantitative Finance, 8(3), 217-224. \[3] Alexander, A. (2025). "Latency Arbitrage in Cryptocurrency Markets: Analyzing Execution Speeds & Liquidity Dynamics." SSRN Working Paper 5143158. Available at: \[4] Grossman, S. J., and Stiglitz, J. E. (1980). "On the Impossibility of Informationally Efficient Markets." 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