# How Does Span'S Use of Risk Arrays Differ from Tims's Scenario Grid? ▴ Question

**Published:** 2025-08-03
**Categories:** Question

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## Concept

An institutional portfolio’s risk profile is a complex, multi-dimensional surface. The critical task for any clearinghouse or risk manager is to project this high-dimensional reality onto a single, actionable number ▴ the [margin requirement](https://prime.greeks.live/area/margin-requirement/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). The architectural choice of how to perform this projection defines the operational reality for every market participant.

Two dominant design philosophies have shaped the landscape of derivatives margining, embodied by the Chicago Mercantile Exchange’s (CME) Standard Portfolio Analysis of Risk (SPAN) and the Options Clearing Corporation’s (OCC) [Theoretical Intermarket Margin System](https://prime.greeks.live/area/theoretical-intermarket-margin-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (TIMS). Understanding their divergence begins with recognizing the fundamental problem they both solve ▴ quantifying potential loss for portfolios containing non-linear instruments like options and futures.

SPAN’s architecture is built upon a principle of standardized, pre-calculated risk components. At its core is the **[Risk Array](https://prime.greeks.live/area/risk-array/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite)**, a set of numeric values generated by the exchange that represents the gain or loss for a single, specific contract under a predefined set of market shocks. Think of it as a lookup table. For each product it clears, the CME simulates a series of price and volatility movements and publishes the resulting profit or loss values in a data file.

A clearing firm’s system ingests this file, applies the P/L values from the array to its portfolio of positions, and identifies the scenario that produces the maximum loss. This loss, aggregated across the portfolio and adjusted for various [spread credits](https://prime.greeks.live/question/how-does-an-rfq-provide-a-competitive-spread/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and additional charges, becomes the margin. The risk array is a discrete, product-level component that forms the building block of a portfolio-level calculation.

TIMS, conversely, operates on a principle of holistic, portfolio-level revaluation. Its foundational element is the **[Scenario Grid](https://prime.greeks.live/area/scenario-grid/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite)**. This grid defines a matrix of hypothetical market states, primarily focused on a range of potential prices for the underlying asset and shifts in the overall volatility surface. The TIMS process takes a member’s [entire portfolio](https://prime.greeks.live/question/how-can-a-single-inaccurate-trade-report-jeopardize-the-entire-financial-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) of positions and subjects it to a full re-pricing under each and every scenario in this grid.

It uses a theoretical options pricing model to calculate the portfolio’s value at each grid point. The margin requirement is determined by finding the single point on this grid that results in the greatest calculated loss for the portfolio as a whole. The scenario grid is a framework for dynamic valuation, where the risk of the portfolio is assessed as a single, integrated unit from the outset.

> The core distinction lies in the unit of analysis ▴ SPAN builds a portfolio’s risk from pre-calculated, single-contract risk arrays, while TIMS evaluates the entire portfolio’s value across a grid of market scenarios.

This structural difference has profound implications. SPAN’s methodology, with its published risk parameter files, creates a highly predictable and replicable system. Any market participant with the SPAN software and the correct parameter file can calculate the exact same margin requirement as the exchange.

It is a system designed for immense scale and standardization, which is why it has been adopted by dozens of exchanges globally for a wide array of derivatives. TIMS’s approach is more computationally intensive but offers a potentially more nuanced view of risk for complex, inter-related equity option portfolios, as the simultaneous revaluation of all positions inherently captures the offsetting effects and non-linear correlations between them without the need for explicit “spread credit” rules.

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## Strategy

The strategic imperatives behind SPAN and TIMS reflect the markets they were designed to secure. The choice between a risk array architecture and a scenario grid architecture is a choice about the trade-offs between standardization, computational efficiency, and the granularity of risk modeling. These are not merely technical details; they are strategic decisions that shape [capital efficiency](https://prime.greeks.live/area/capital-efficiency/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), operational workflows, and the very nature of [risk management](https://prime.greeks.live/area/risk-management/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) for clearing members.

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## Architectural Philosophy and Strategic Intent

The strategic intent of [CME SPAN](https://prime.greeks.live/area/cme-span/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is to provide a robust, transparent, and globally consistent framework for margining futures and options on futures. Its adoption by over 50 exchanges and clearing organizations is a testament to this strategy. The system is engineered for efficiency and predictability. By publishing a standardized Risk Array file each day, the [CME Group](https://prime.greeks.live/area/cme-group/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) provides all market participants with the exact building blocks needed to compute margin requirements.

This decouples the complex task of scenario generation (performed by the exchange) from the task of [margin calculation](https://prime.greeks.live/area/margin-calculation/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (performed by the clearing firm). This strategy prioritizes a common language of risk, allowing for consistent application across diverse products and markets.

The strategy of OCC’s TIMS is rooted in the unique complexities of the U.S. listed equity options market. As the central clearer for this vast and intricate ecosystem, the OCC’s primary concern is the accurate modeling of large, complex portfolios of options with myriad strikes and expirations. The Scenario Grid strategy is designed to perform a holistic, top-down valuation.

It assesses the portfolio as an integrated entity, allowing the complex, non-linear interactions between different options positions to net out naturally within the valuation model itself. This approach is strategically tailored to capture the nuanced risk profile of sophisticated options strategies, such as multi-leg spreads and positions sensitive to shifts in the volatility skew, without relying on a system of pre-defined spread credits.

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## How Do the Methodologies Treat Key Risk Factors?

The strategic differences become tangible when examining how each system models financial risk. The table below juxtaposes their treatment of the primary risk vectors in a derivatives portfolio. This comparison reveals the architectural trade-offs inherent in each design.

| Risk Factor | CME SPAN (Risk Array Approach) | OCC TIMS (Scenario Grid Approach) |
| --- | --- | --- |
| Underlying Price Changes | Handled via a “Price Scan Range.” The Risk Array contains 16 scenarios that shock the price up and down by fractions of this range (e.g. +/- 33%, +/- 67%, +/- 100%). The range itself is a parameter set by the exchange. | Handled via a grid of explicit price points. The Scenario Grid defines a set of absolute or percentage-based price levels for the underlying asset. The portfolio is revalued at each of these points. |
| Volatility Changes | Handled via a “Volatility Scan Range.” The 16 scenarios in the Risk Array explicitly pair price moves with volatility moves (e.g. price up/vol up, price up/vol down). This is a discrete, predefined shock. | Handled as a dimension of the grid. The Scenario Grid can include various levels of implied volatility, allowing for the re-pricing of the portfolio under different volatility regimes. This can capture shifts in the entire volatility surface. |
| Time Decay (Theta) | Implicitly included in the Risk Array calculation. The gain or loss value for each scenario is calculated for a one-day time horizon, thus accounting for one day of time decay. | Implicitly included in the portfolio revaluation. The options pricing model used to value the portfolio at each grid point naturally accounts for a one-day decrease in time to expiration. |
| Portfolio Offsets | Handled through explicit, rule-based credits. SPAN has specific parameters for “Intra-Commodity” (calendar) spreads and “Inter-Commodity” (cross-product) spreads that reduce the total margin requirement. | Handled implicitly through portfolio-level revaluation. Because the entire portfolio is priced as one unit in each scenario, the natural offsets between long and short positions are inherently captured without needing separate credit rules. |

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## Strategic Implications for Market Participants

For a clearing firm or large trader, the choice of methodology has direct strategic consequences. A firm primarily trading highly correlated futures contracts across different exchanges might find the SPAN methodology highly advantageous. The explicit [inter-commodity spread](https://prime.greeks.live/area/inter-commodity-spread/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) credits provide a clear, quantifiable benefit that can be anticipated and incorporated into trading strategy costs. The predictability of the daily SPAN parameter file allows for precise, independent pre-trade margin calculations.

Conversely, an institution specializing in complex equity option overlays or volatility dispersion strategies might find the TIMS methodology to be a more accurate representation of its risk. The holistic revaluation approach can better capture the subtle correlations and volatility-skew effects that a rule-based spread credit system might miss. The strategic focus shifts from optimizing explicit spread credits to understanding how the entire portfolio’s valuation will behave under the various market states defined by the TIMS grid.

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## Execution

The execution of margin calculation under SPAN and TIMS translates their respective strategic philosophies into concrete operational workflows. For the institutional risk manager, understanding these procedural mechanics is essential for pre-trade analysis, capital management, and system integration. The difference is one of assembling pre-fabricated components versus commissioning a holistic analysis.

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## The Operational Playbook

The day-to-day process of calculating margin requirements follows a distinct path for each system, defined by the flow of data and the locus of computation.

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## CME SPAN Execution Workflow

The SPAN process is a distributed, multi-step procedure that relies on data provided by the exchange.

- **Parameter Generation** ▴ Each trading day, the CME analyzes market data and determines the core risk parameters for each product it clears. These include the Price Scan Range (the expected maximum one-day price move), the Volatility Scan Range, and various spread parameters.

- **Risk Array Publication** ▴ These parameters are used to compute the 16-scenario Risk Array for every single cleared contract. The array contains the precise profit or loss value for that contract under each scenario. This data is compiled into a single, large data file, the SPAN Risk Parameter File, and published for clearing members to download.

- **Portfolio Scan** ▴ The clearing firm ingests the SPAN file into its risk system. The system then scans the firm’s portfolio. For each position, it looks up the corresponding P/L value for each of the 16 risk scenarios in the array. It then sums these values across all positions to find the total portfolio P/L for each scenario. The largest loss among these 16 totals is the “Scan Risk.”

- **Charge and Credit Application** ▴ The system applies additional calculations. It identifies positions that qualify for Intra-Commodity (calendar) spread charges and Inter-Commodity spread credits, adjusting the total requirement accordingly. It also calculates a Short Option Minimum charge to account for deep out-of-the-money options risk. The final margin is the sum of these components.

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## OCC TIMS Execution Workflow

The TIMS process is a more centralized and holistic valuation exercise.

- **Scenario Grid Definition** ▴ The OCC defines and maintains a grid of market scenarios. This grid is multi-dimensional, specifying a range of underlying asset prices and corresponding implied volatility levels. This grid is less a public data file and more a set of instructions for the valuation engine.

- **Portfolio Submission** ▴ The clearing member submits its complete portfolio of positions to the OCC’s calculation engine or a proprietary system that replicates the OCC’s methodology.

- **Holistic Revaluation** ▴ The TIMS engine iterates through every point on the Scenario Grid. At each point (e.g. [Underlying Price](https://prime.greeks.live/question/does-the-underlying-assets-liquidity-profile-determine-the-optimal-execution-protocol/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) down 10%, Volatility up 5%), it uses a theoretical options pricing model to re-calculate the value of every single position in the portfolio and sums them to get a total portfolio value for that specific scenario.

- **Worst-Case Loss Identification** ▴ After revaluing the portfolio across all scenarios in the grid, the system identifies the single scenario that resulted in the lowest portfolio value. The difference between this value and the current market value of the portfolio represents the “worst-case loss,” which becomes the basis for the margin requirement. Broker-dealers may augment these scenarios with their own “house” scenarios to capture additional risks like extreme market moves or position concentration.

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## Quantitative Modeling and Data Analysis

To make the distinction concrete, we can visualize the core data structures of each system. The tables below are simplified representations, but they accurately reflect the structural difference between a Risk Array and a Scenario Grid.

> A SPAN risk array is a list of P/L values for one contract, whereas a TIMS scenario grid is a map of valuation points for an entire portfolio.

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## Table ▴ Example of a CME SPAN Risk Array

This table shows a hypothetical Risk Array for a single S&P 500 e-mini futures contract (ES). The Price Scan Range is assumed to be 90 points ($4,500 per contract), and the Volatility Scan Range is 7%.

| Scenario | Underlying Price Move | Volatility Move | Gain/Loss per ES Contract |
| --- | --- | --- | --- |
| 1 | Unchanged | Up 7% | $0 |
| 2 | Unchanged | Down 7% | $0 |
| 3 | Up 30 pts (+33%) | Up 7% | $1,500 |
| 4 | Up 30 pts (+33%) | Down 7% | $1,500 |
| 5 | Down 30 pts (-33%) | Up 7% | -$1,500 |
| 6 | Down 30 pts (-33%) | Down 7% | -$1,500 |
| 7 | Up 60 pts (+67%) | Up 7% | $3,000 |
| 8 | Up 60 pts (+67%) | Down 7% | $3,000 |
| 9 | Down 60 pts (-67%) | Up 7% | -$3,000 |
| 10 | Down 60 pts (-67%) | Down 7% | -$3,000 |
| 11 | Up 90 pts (+100%) | Up 7% | $4,500 |
| 12 | Up 90 pts (+100%) | Down 7% | $4,500 |
| 13 | Down 90 pts (-100%) | Up 7% | -$4,500 |
| 14 | Down 90 pts (-100%) | Down 7% | -$4,500 |
| 15 | Up 270 pts (Extreme Move) | Unchanged | $13,500 33% = $4,455 |
| 16 | Down 270 pts (Extreme Move) | Unchanged | -$13,500 33% = -$4,455 |

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## Table ▴ Visualization of an OCC TIMS Scenario Grid

This table visualizes the concept of the TIMS grid for an entire portfolio. The cells would contain the calculated Net P/L of the entire portfolio after re-pricing all instruments under that specific market condition.

| Portfolio Net P/L | Change in Underlying Price | -10% | -5% | 0% | +5% | +10% |
| --- | --- | --- | --- | --- | --- | --- |

In this TIMS example, the margin requirement would be based on the worst loss identified in the grid, which is -$1,250,000, occurring in the scenario where the underlying price drops by 10% and volatility increases by 10%.

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## References

- CME Group. “CME SPAN Methodology Overview.” CME Group, 2023.

- CME Group. “Span Methodology.” March 2019.

- Interactive Brokers. “Overview of Margin Methodologies.” IBKR Guides, 2024.

- KDPW_CCP. “SPAN ▴ margin calculation methodology.” 2023.

- Duffie, Darrell, and Rui M. C. Martins. “A Review of the Standard Portfolio Analysis of Risk (SPAN) System.” Financial Analysts Journal, vol. 52, no. 4, 1996, pp. 53 ▴ 67.

- Options Clearing Corporation. “OCC Margin Methodology.” OCC, 2022.

- Figlewski, Stephen. “Hedging with Financial Futures for Institutional Investors ▴ From Theory to Practice.” The Journal of Finance, vol. 39, no. 3, 1984, pp. 657-670.

- Kupiec, Paul H. “Techniques for Verifying the Accuracy of Risk Measurement Models.” The Journal of Derivatives, vol. 3, no. 2, 1995, pp. 73-84.

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## Reflection

The examination of SPAN’s [Risk Arrays](https://prime.greeks.live/area/risk-arrays/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and TIMS’s Scenario Grid moves beyond a simple comparison of two margining systems. It reveals a fundamental duality in risk management architecture ▴ the tension between a standardized, component-based model and a holistic, valuation-based model. Neither architecture is inherently superior; they are purpose-built systems designed with different strategic objectives to manage the risks of different market ecosystems.

The critical insight for an institutional operator is that the margining system is an active component of the market’s structure. It defines the cost of capital, influences strategic decisions, and sets the operational tempo for risk management. Your internal risk models and pre-trade analytics must be architected with a deep understanding of whether the clearinghouse uses a system of assembling pre-defined risk components or one of dynamic, holistic valuation.

Does your own operational framework treat risk as a series of additive parts or as the emergent property of an integrated portfolio? The answer dictates how effectively you can manage capital and navigate the complex topology of institutional risk.

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## Glossary

<a href="https://prime.greeks.live/area/margin-requirement/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Margin Requirement

Meaning ▴ Margin Requirement in crypto trading dictates the minimum amount of collateral, typically denominated in a cryptocurrency or fiat currency, that a trader must deposit and continuously maintain with an exchange or broker to support leveraged positions. </a><a href="https://prime.greeks.live/area/theoretical-intermarket-margin-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Theoretical Intermarket Margin System

Meaning ▴ A conceptual framework or model for calculating margin requirements across multiple, interconnected markets or asset classes, aiming to recognize offsets and correlations between positions to reduce overall collateral needs. </a><a href="https://prime.greeks.live/area/risk-array/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A Principal's RFQ engine core unit, featuring distinct algorithmic matching probes for high-fidelity execution and liquidity aggregation. This price discovery mechanism leverages private quotation pathways, optimizing crypto derivatives OS operations for atomic settlement within its systemic architecture](https://options.greeks.live/wp-content/uploads/2025/08/principals-rfq-engine-driving-optimal-digital-asset-derivatives.jpg)

## Risk Array

Meaning ▴ A Risk Array is a structured data representation, typically a matrix, that quantifies an entity's exposure to various financial risks across different market factors or scenarios. </a><a href="https://prime.greeks.live/question/how-does-an-rfq-provide-a-competitive-spread/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Spread Credits

The RFQ protocol engineers a competitive spread by structuring a private auction that minimizes information leakage and focuses dealer competition. </a><a href="https://prime.greeks.live/question/how-can-a-single-inaccurate-trade-report-jeopardize-the-entire-financial-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Entire Portfolio

A single inaccurate trade report jeopardizes the financial system by injecting false data that cascades through automated, interconnected settlement and risk networks. </a><a href="https://prime.greeks.live/area/scenario-grid/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Scenario Grid

Meaning ▴ A Scenario Grid is a structured analytical tool used to map out various potential future states or conditions, typically defined by a combination of key uncertain variables, to assess their impact on a system or strategy. </a><a href="https://prime.greeks.live/area/capital-efficiency/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Capital Efficiency

Meaning ▴ Capital efficiency, in the context of crypto investing and institutional options trading, refers to the optimization of financial resources to maximize returns or achieve desired trading outcomes with the minimum amount of capital deployed. </a><a href="https://prime.greeks.live/area/risk-management/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Risk Management

Meaning ▴ Risk Management, within the cryptocurrency trading domain, encompasses the comprehensive process of identifying, assessing, monitoring, and mitigating the multifaceted financial, operational, and technological exposures inherent in digital asset markets. </a><a href="https://prime.greeks.live/area/cme-group/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A teal-colored digital asset derivative contract unit, representing an atomic trade, rests precisely on a textured, angled institutional trading platform. This suggests high-fidelity execution and optimized market microstructure for private quotation block trades within a secure Prime RFQ environment, minimizing slippage](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-engine-optimization.jpg)

## Cme Group

Meaning ▴ CME Group is a preeminent global markets company, operating multiple exchanges and clearinghouses that offer a vast array of futures, options, cash, and over-the-counter (OTC) products across all major asset classes, notably including cryptocurrency derivatives. </a><a href="https://prime.greeks.live/area/cme-span/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Sleek, modular infrastructure for institutional digital asset derivatives trading. Its intersecting elements symbolize integrated RFQ protocols, facilitating high-fidelity execution and precise price discovery across complex multi-leg spreads](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-system-optimizing-high-fidelity-block-trade-liquidity-and-multi-leg-spread-precision.jpg)

## Cme Span

Meaning ▴ CME SPAN (Standard Portfolio Analysis of Risk) is a proprietary methodology developed by the CME Group for calculating margin requirements for futures and options portfolios. </a><a href="https://prime.greeks.live/area/margin-calculation/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Dark precision apparatus with reflective spheres, central unit, parallel rails. Visualizes institutional-grade Crypto Derivatives OS for RFQ block trade execution, driving liquidity aggregation and algorithmic price discovery](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-system.jpg)

## Margin Calculation

Meaning ▴ Margin Calculation refers to the complex process of determining the collateral required to open and maintain leveraged positions in crypto derivatives markets, such as futures or options. </a><a href="https://prime.greeks.live/area/price-scan-range/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precision-engineered, multi-layered system architecture for institutional digital asset derivatives. Its modular components signify robust RFQ protocol integration, facilitating efficient price discovery and high-fidelity execution for complex multi-leg spreads, minimizing slippage and adverse selection in market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-institutional-digital-asset-derivatives-rfq-execution-platform.jpg)

## Price Scan Range

Meaning ▴ Price Scan Range, in crypto derivatives trading and risk management systems, refers to the maximum anticipated price fluctuation, both upward and downward, that a clearing house or exchange projects for a specific cryptocurrency asset or derivative contract over a defined period. </a><a href="https://prime.greeks.live/area/volatility-scan-range/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sophisticated metallic apparatus with a prominent circular base and extending precision probes. This represents a high-fidelity execution engine for institutional digital asset derivatives, facilitating RFQ protocol automation, liquidity aggregation, and atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/precision-engine-for-institutional-digital-asset-derivatives-rfq-protocol.jpg)

## Volatility Scan Range

Meaning ▴ The Volatility Scan Range defines the specific spectrum of implied volatility values used when pricing or analyzing options contracts, typically for scenario analysis or model calibration. </a><a href="https://prime.greeks.live/area/inter-commodity-spread/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Central, interlocked mechanical structures symbolize a sophisticated Crypto Derivatives OS driving institutional RFQ protocol. Surrounding blades represent diverse liquidity pools and multi-leg spread components](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-architecture-optimizing-high-fidelity-execution-across-diverse-liquidity-pools.jpg)

## Inter-Commodity Spread

Meaning ▴ An Inter-Commodity Spread in crypto investing involves simultaneously buying and selling different but related crypto assets or derivatives that typically exhibit a historical price relationship. </a><a href="https://prime.greeks.live/question/does-the-underlying-assets-liquidity-profile-determine-the-optimal-execution-protocol/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Two abstract, segmented forms intersect, representing dynamic RFQ protocol interactions and price discovery mechanisms. The layered structures symbolize liquidity aggregation across multi-leg spreads within complex market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-microstructure.jpg)

## Underlying Price

An asset's liquidity profile is the primary determinant, dictating the strategic balance between market impact and timing risk. </a><a href="https://prime.greeks.live/area/risk-arrays/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A metallic, disc-centric interface, likely a Crypto Derivatives OS, signifies high-fidelity execution for institutional-grade digital asset derivatives. Its grid implies algorithmic trading and price discovery](https://options.greeks.live/wp-content/uploads/2025/07/rfq-block-price-algo-fidelity-alpha-capital-institutional-digital.jpg)

## Risk Arrays

Meaning ▴ Risk Arrays are multi-dimensional data structures or matrices used in financial systems to systematically quantify and represent the potential impact of various risk factors on a portfolio or individual financial positions. </a>

**Tags:** [Options Margining](https://options.greeks.live/area/options-margining/), [CME SPAN](https://options.greeks.live/area/cme-span/), [Inter-Commodity Spread](https://options.greeks.live/area/inter-commodity-spread/), [Risk Arrays](https://options.greeks.live/area/risk-arrays/), [Theoretical Intermarket Margin System](https://options.greeks.live/area/theoretical-intermarket-margin-system/), [Margin Calculation](https://options.greeks.live/area/margin-calculation/)	

## Discover More

- 
### [What Are the Main Differences between SPAN and VaR Based Margining Systems?](https://options.greeks.live/question/what-are-the-main-differences-between-span-and-var-based-margining-systems/)
![A dark blue sphere and teal-hued circular elements on a segmented surface, bisected by a diagonal line. This visualizes institutional block trade aggregation, algorithmic price discovery, and high-fidelity execution within a Principal's Prime RFQ, optimizing capital efficiency and mitigating counterparty risk for digital asset derivatives and multi-leg spreads.](https://options.greeks.live/wp-content/uploads/2025/07/market-microstructure-driven-institutional-digital-asset-derivatives-rfq.jpg)

SPAN is a product-level, scenario-based risk model; VaR is a holistic, statistically-driven portfolio risk management system.

- 
### [To What Extent Does Historical Simulation Var Capture Tail Risk Compared to Span Scenarios?](https://options.greeks.live/question/to-what-extent-does-historical-simulation-var-capture-tail-risk-compared-to-span-scenarios/)
![A sleek blue surface with droplets represents a high-fidelity Execution Management System for digital asset derivatives, processing market data. A lighter surface denotes the Principal's Prime RFQ. A teal square symbolizes a block trade inquiry, facilitating price discovery and optimal execution via RFQ protocols.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-execution-for-optimal-price-discovery.jpg)

Historical Simulation VaR measures tail risk based on past events; SPAN measures it against predefined, simulated scenarios.

- 
### [How Does Portfolio Margining Affect the Execution of Complex Derivatives Strategies?](https://options.greeks.live/question/how-does-portfolio-margining-affect-the-execution-of-complex-derivatives-strategies/)
![Abstract visualization of an institutional-grade digital asset derivatives execution engine. Its segmented core and reflective arcs depict advanced RFQ protocols, real-time price discovery, and dynamic market microstructure, optimizing high-fidelity execution and capital efficiency for block trades within a Principal's framework.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-engine-interface.jpg)

Portfolio margining transforms execution by reframing capital cost, making systemically-hedged complex strategies viable through unified risk computation.

- 
### [How Does Portfolio Margining Affect Liquidity for Complex Options Strategies?](https://options.greeks.live/question/how-does-portfolio-margining-affect-liquidity-for-complex-options-strategies/)
![A central engineered mechanism, resembling a Prime RFQ hub, anchors four precision arms. This symbolizes multi-leg spread execution and liquidity pool aggregation for RFQ protocols, enabling high-fidelity execution. Reflections suggest price discovery and atomic settlement in institutional digital asset derivatives.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-framework-enabling-multi-leg-spread-strategies-for-optimized-liquidity.jpg)

Portfolio margining enhances liquidity for complex options strategies by aligning capital requirements with the portfolio's net risk.

- 
### [What Are the Quantitative Impacts of Central Clearing on Initial Margin Requirements for Crypto Options?](https://options.greeks.live/question/what-are-the-quantitative-impacts-of-central-clearing-on-initial-margin-requirements-for-crypto-options/)
![Abstract geometric forms, including overlapping planes and central spherical nodes, visually represent a sophisticated institutional digital asset derivatives trading ecosystem. It depicts complex multi-leg spread execution, dynamic RFQ protocol liquidity aggregation, and high-fidelity algorithmic trading within a Prime RFQ framework, ensuring optimal price discovery and capital efficiency.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-liquidity-aggregation-market-microstructure-high-fidelity-execution-alpha-generation-prime-os-capital-efficiency.jpg)

Central clearing quantitatively reduces crypto options initial margin through portfolio netting and advanced risk models, enhancing capital efficiency.

- 
### [How Does Multilateral Netting Reduce Initial Margin Requirements?](https://options.greeks.live/question/how-does-multilateral-netting-reduce-initial-margin-requirements/)
![Abstract geometric design illustrating a central RFQ aggregation hub for institutional digital asset derivatives. Radiating lines symbolize high-fidelity execution via smart order routing across dark pools. Modular elements represent atomic settlement and capital efficiency within a Principal's operational framework.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-high-fidelity-execution-architecture.jpg)

Multilateral netting centralizes and compresses portfolio risk, drastically lowering initial margin by offsetting exposures across all counterparties.

- 
### [How Does Portfolio Margining at a Ccp Mitigate Lost Netting Benefits?](https://options.greeks.live/question/how-does-portfolio-margining-at-a-ccp-mitigate-lost-netting-benefits/)
![A sleek, modular institutional grade system with glowing teal conduits represents advanced RFQ protocol pathways. This illustrates high-fidelity execution for digital asset derivatives, facilitating private quotation and efficient liquidity aggregation. The precise architecture suggests optimized market microstructure and atomic settlement for Bitcoin options and Ethereum futures.](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-ecosystem-powering-high-fidelity-rfq-execution-and-optimal-liquidity-discovery.jpg)

Portfolio margining at a CCP mitigates lost netting benefits by calculating margin on the net risk of an entire portfolio, enhancing capital efficiency.

- 
### [From a Risk Perspective Which Is Superior for Complex Derivatives Portfolios SPAN or VaR?](https://options.greeks.live/question/from-a-risk-perspective-which-is-superior-for-complex-derivatives-portfolios-span-or-var/)
![A beige, triangular device with a dark, reflective display and dual front apertures. This specialized hardware facilitates institutional RFQ protocols for digital asset derivatives, enabling high-fidelity execution, market microstructure analysis, optimal price discovery, capital efficiency, block trades, and portfolio margin.](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-rfq-terminal-for-high-fidelity-execution-and-precise-market-microstructure-analysis.jpg)

From a risk perspective, VaR's holistic, probabilistic analysis is superior for complex portfolios, offering greater capital efficiency.

- 
### [What Role Does the Options Clearing Corporation Play in the TIMS Framework?](https://options.greeks.live/question/what-role-does-the-options-clearing-corporation-play-in-the-tims-framework/)
![Polished, intersecting geometric blades converge around a central metallic hub. This abstract visual represents an institutional RFQ protocol engine, enabling high-fidelity execution of digital asset derivatives. It embodies precise market microstructure, liquidity aggregation, price discovery, and multi-leg spread strategies, optimizing capital efficiency and atomic settlement.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-high-fidelity-execution-market-microstructure.jpg)

The OCC architected and mandates the TIMS framework to calculate portfolio-based margin, ensuring market stability via precise risk assessment.

---

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---

**Original URL:** https://options.greeks.live/question/how-does-spans-use-of-risk-arrays-differ-from-timss-scenario-grid/
