# Can a Portfolio Optimized for Low VaR Simultaneously Have a High Stressed VaR? ▴ Question

**Published:** 2025-08-12
**Categories:** Question

---

![Sleek dark metallic platform, glossy spherical intelligence layer, precise perforations, above curved illuminated element. This symbolizes an institutional RFQ protocol for digital asset derivatives, enabling high-fidelity execution, advanced market microstructure, Prime RFQ powered price discovery, and deep liquidity pool access](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-digital-asset-derivatives-rfq-protocol-high-fidelity-execution-1.jpg)

![An abstract, precision-engineered mechanism showcases polished chrome components connecting a blue base, cream panel, and a teal display with numerical data. This symbolizes an institutional-grade RFQ protocol for digital asset derivatives, ensuring high-fidelity execution, price discovery, multi-leg spread processing, and atomic settlement within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-precision-execution-1.jpg)

## Concept

The assertion that a portfolio meticulously optimized for a low Value at Risk (VaR) can concurrently exhibit a high Stressed VaR (SVaR) is not only plausible but a fundamental reality in modern risk management. This phenomenon reveals a critical distinction between operating a portfolio within the parameters of “normal” [market conditions](https://prime.greeks.live/question/how-do-exchanges-define-stressed-market-conditions-for-market-makers/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and ensuring its resilience during periods of acute financial distress. The [divergence between](https://prime.greeks.live/question/to-what-extent-does-regulatory-divergence-between-the-us-and-eu-create-actionable-arbitrage-opportunities-for-global-hft-operations/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) these two risk metrics stems directly from the assumptions embedded within their respective calculation frameworks. A portfolio manager can construct a portfolio that appears statistically safe under the lens of recent, benign market data, yet harbors significant, latent vulnerabilities that only manifest when systemic pressures mount.

At its core, [standard VaR](https://prime.greeks.live/area/standard-var/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) provides a probabilistic estimate of potential loss over a defined period under typical market fluctuations. It functions by observing a recent historical window ▴ for instance, the past 252 trading days ▴ and extrapolating the likely range of portfolio returns. The optimization process, therefore, naturally favors assets with low recent volatility and stable, predictable correlations. A [portfolio manager](https://prime.greeks.live/question/what-are-the-primary-risks-associated-with-ambiguous-last-look-disclosures-for-a-portfolio-manager/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), guided by this metric, might assemble a collection of assets that are seemingly diversified and collectively produce a low VaR figure, satisfying internal risk limits and regulatory expectations under a business-as-usual forecast.

> A portfolio’s safety during calm markets offers no guarantee of its stability during a crisis, as the statistical assumptions that underpin normal-period risk models often break down precisely when they are needed most.

However, the operational environment of financial markets is not static. It is characterized by distinct regimes, shifting from periods of calm to periods of intense stress. [Stressed VaR](https://prime.greeks.live/area/stressed-var/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is a measure designed specifically to quantify portfolio risk within these turbulent regimes. Instead of using recent data, SVaR calculations are based on a historical period of significant financial stress, such as the 2008 global [financial crisis](https://prime.greeks.live/area/financial-crisis/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) or the COVID-19 market shock.

This forces the risk model to consider scenarios where [volatility](https://prime.greeks.live/area/volatility/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) surges, liquidity evaporates, and ▴ most critically ▴ the correlation structures that held during normal times completely break down. Assets that appeared uncorrelated or even negatively correlated can suddenly move in lockstep, eradicating the [diversification](https://prime.greeks.live/area/diversification/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) benefits that were central to the low standard VaR reading.

Consequently, the very strategies employed to minimize standard VaR can inadvertently amplify Stressed VaR. For example, a portfolio might rely on selling seemingly overpriced, out-of-the-money options to generate income and lower its daily volatility profile. In a [normal market](https://prime.greeks.live/question/how-can-quantitative-models-distinguish-between-pre-hedging-and-normal-market-volatility/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), these options expire worthless, contributing to a stable and positive performance. During a stress event, however, these short option positions can lead to exponential, catastrophic losses, revealing a risk profile that was entirely masked by the standard VaR calculation.

The divergence is not a flaw in one metric or the other; it is an expression of a deeper truth ▴ optimizing for one specific market regime can create profound fragility in another. The simultaneous existence of low VaR and high SVaR is the signature of a portfolio that is statistically safe but systemically brittle.

![A cutaway view reveals an advanced RFQ protocol engine for institutional digital asset derivatives. Intricate coiled components represent algorithmic liquidity provision and portfolio margin calculations](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-rfq-protocol-engine-digital-asset-derivatives-core-internal-mechanism-visualized.jpg)

![Two smooth, teal spheres, representing institutional liquidity pools, precisely balance a metallic object, symbolizing a block trade executed via RFQ protocol. This depicts high-fidelity execution, optimizing price discovery and capital efficiency within a Principal's operational framework for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/precision-execution-bridging-institutional-liquidity-pools-via-rfq-protocol-for-optimized-digital-asset-derivatives-price-discovery.jpg)

## Strategy

![A sophisticated, symmetrical apparatus depicts an institutional-grade RFQ protocol hub for digital asset derivatives, where radiating panels symbolize liquidity aggregation across diverse market makers. Central beams illustrate real-time price discovery and high-fidelity execution of complex multi-leg spreads, ensuring atomic settlement within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-grade-rfq-protocol-facilitating-atomic-settlement-and-high-fidelity-execution-of-multi-leg-spreads.jpg)

## The Illusion of Safety in Normal Market Regimes

The strategic pursuit of a low Value at Risk figure often involves a set of sophisticated techniques designed to minimize portfolio volatility based on recent historical data. Portfolio managers may utilize strategies that implicitly or explicitly depend on the continuation of a specific market environment characterized by moderate price movements and predictable asset relationships. This optimization process can create a portfolio that is highly efficient under normal conditions but is inadequately prepared for the structural shifts that define a crisis. The core of the issue lies in the assumptions that underpin standard VaR models, which often fail to account for the non-linear dynamics and behavioral finance aspects of market stress.

One primary assumption is that asset returns follow a well-behaved statistical distribution, such as the normal distribution. Financial returns, however, are known to exhibit “fat tails,” meaning that extreme events occur far more frequently than a normal distribution would predict. A portfolio optimized to have a low VaR under this assumption might be heavily concentrated in strategies that are vulnerable to these tail events.

For instance, a strategy might involve collecting small, consistent premiums by selling insurance against large market moves. While this lowers day-to-day volatility and looks favorable in a VaR model, it exposes the portfolio to massive, discontinuous losses when a tail event actually occurs.

![Close-up of intricate mechanical components symbolizing a robust Prime RFQ for institutional digital asset derivatives. These precision parts reflect market microstructure and high-fidelity execution within an RFQ protocol framework, ensuring capital efficiency and optimal price discovery for Bitcoin options](https://options.greeks.live/wp-content/uploads/2025/07/engineered-core-systems-driving-institutional-digital-asset-derivatives-rfq-protocol-execution.jpg)

## Correlation Breakdown and the Failure of Diversification

A second critical assumption embedded in standard VaR is the stability of correlation matrices. Diversification is the cornerstone of modern portfolio theory, and a low VaR is often achieved by combining assets that have historically shown low or negative correlation. However, a defining feature of market crises is the phenomenon of [correlation breakdown](https://prime.greeks.live/area/correlation-breakdown/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).

During a systemic shock, the intricate web of asset relationships can shift dramatically. Assets that were previously uncorrelated begin to move in the same direction, typically downwards, as investors flee to the safest available instruments.

This systemic shift means that the diversification benefits, which were a key component of the low VaR calculation, evaporate precisely when they are most needed. A portfolio that seemed diversified across various sectors, geographies, and asset classes can suddenly behave like a single, highly concentrated position. The Stressed VaR calculation, by using a historical stress period as its input, is explicitly designed to capture this effect. It models the portfolio’s performance under conditions where these correlations have already broken down, revealing a vulnerability that the standard VaR model, with its reliance on recent, more benign data, would miss.

> The divergence between VaR and SVaR is a direct measure of a portfolio’s reliance on the persistence of calm market structures and predictable asset correlations.

The table below illustrates the fundamental differences in the strategic posture implied by optimizing for VaR versus being mindful of SVaR.

| Metric | Underlying Assumption | Implied Portfolio Strategy | Hidden Vulnerability |
| --- | --- | --- | --- |
| Value at Risk (VaR) | Market conditions are an extension of the recent past. Correlations are stable. | Maximize risk-adjusted return based on recent volatility and correlation data. May involve writing options or other short-volatility trades. | Exposure to tail risk, non-linear payoffs, and correlation breakdown. The portfolio is brittle. |
| Stressed VaR (SVaR) | Market conditions can abruptly shift to a crisis regime. Correlations are unstable. | Ensure portfolio resilience during historical stress scenarios. Avoids strategies with explosive, non-linear downside risk. | May appear suboptimal or overly conservative during extended periods of market calm. The portfolio is robust but potentially less efficient. |

![A precision-engineered metallic and glass system depicts the core of an Institutional Grade Prime RFQ, facilitating high-fidelity execution for Digital Asset Derivatives. Transparent layers represent visible liquidity pools and the intricate market microstructure supporting RFQ protocol processing, ensuring atomic settlement capabilities](https://options.greeks.live/wp-content/uploads/2025/08/robust-institutional-digital-asset-derivatives-trading-platform-for-optimized-rfq-protocol-execution-and-deep-liquidity-access.jpg)

## Non-Linear Payoffs and Hidden Leverage

Modern financial markets are replete with instruments that have non-linear payoff profiles, most notably derivatives such as options. A portfolio can be structured to have a low VaR by, for example, owning a bond and simultaneously selling a call option against it (a covered call strategy). In a stable or slightly declining market, this strategy reduces volatility and generates income.

The VaR calculation, especially if based on a simple delta-normal method, may not fully capture the risk. However, in a sharp market rally (a form of stress for this particular strategy), the losses on the short call position can accelerate rapidly.

Stressed VaR, particularly when calculated using full re-evaluation methods, is better at capturing these non-linearities because it simulates the portfolio’s value under large, discrete price shocks characteristic of a stress period. This reveals the hidden leverage and risk embedded in the options positions, leading to a high SVaR figure that stands in stark contrast to the deceptively low standard VaR. The optimization for low standard VaR can thus systematically guide a portfolio manager toward structures whose true risk is camouflaged by the limitations of the measurement tool itself.

![A complex interplay of translucent teal and beige planes, signifying multi-asset RFQ protocol pathways and structured digital asset derivatives. Two spherical nodes represent atomic settlement points or critical price discovery mechanisms within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-for-optimal-liquidity-aggregation-and-high-fidelity-execution.jpg)

![A sleek, multi-layered system representing an institutional-grade digital asset derivatives platform. Its precise components symbolize high-fidelity RFQ execution, optimized market microstructure, and a secure intelligence layer for private quotation, ensuring efficient price discovery and robust liquidity pool management](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-rfq-execution-digital-asset-derivatives-platform-prime-os.jpg)

## Execution

![Two interlocking textured bars, beige and blue, abstractly represent institutional digital asset derivatives platforms. A blue sphere signifies RFQ protocol initiation, reflecting latent liquidity for atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-for-prime-os-execution.jpg)

## Operationalizing the Divergence Analysis

The practical identification and management of the gap between standard VaR and Stressed VaR is a critical function for any sophisticated [risk management](https://prime.greeks.live/area/risk-management/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) unit. It moves beyond theoretical understanding into a concrete, data-driven process designed to unearth hidden portfolio vulnerabilities. This process is not a one-time analysis but a continuous cycle of measurement, diagnosis, and strategic adjustment. The execution requires a robust technological infrastructure, a clear governance framework, and a deep understanding of the portfolio’s underlying risk factors.

The first step in this operational playbook is the rigorous and systematic calculation of both metrics. This requires distinct data sets and methodological considerations as outlined by regulatory frameworks like [Basel III](https://prime.greeks.live/area/basel-iii/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). The standard VaR is typically calculated using a recent historical period (e.g. the last 252 days), while the SVaR requires the identification and application of a historical 12-month period of significant financial stress relevant to the institution’s portfolio.

- **Data Segmentation** ▴ Maintain two distinct and validated historical data sets. One represents the “normal” rolling window for standard VaR. The other represents the “stressed” period, which must be carefully selected and justified to regulators.

- **Model Consistency** ▴ Apply the same VaR model to both data sets. The only variable that changes is the input data (i.e. the market price and rate movements). This ensures that the difference between the VaR and SVaR outputs is attributable purely to the market regime shift, not to inconsistencies in the modeling methodology.

- **Divergence Reporting** ▴ Establish a routine risk report that explicitly quantifies the divergence between VaR and SVaR. This can be expressed as a ratio (SVaR / VaR) or an absolute difference. This report should be a standing agenda item for risk committees.

- **Attribution Analysis** ▴ When a significant divergence is detected, the next step is to perform a risk attribution analysis. The goal is to identify which specific positions, asset classes, or strategies are contributing most to the high SVaR. This often involves decomposing the portfolio and analyzing the impact of non-linear instruments and shifting correlations.

![A dynamic visual representation of an institutional trading system, featuring a central liquidity aggregation engine emitting a controlled order flow through dedicated market infrastructure. This illustrates high-fidelity execution of digital asset derivatives, optimizing price discovery within a private quotation environment for block trades, ensuring capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/principal-os-driving-high-fidelity-execution-for-digital-asset-derivatives-through-optimized-rfq-protocols-and-smart-order-routing.jpg)

## A Quantitative Demonstration of the VaR-SVaR Gap

To illustrate this phenomenon with concrete data, consider a simplified portfolio of three assets. The objective is to construct a portfolio with a low standard VaR. We will then subject this same portfolio to a stressed market environment to calculate its SVaR and reveal the underlying fragility.

Let’s assume the portfolio consists of:

- **Asset A** ▴ A major market equity index (e.g. S&P 500).

- **Asset B** ▴ A high-yield corporate bond fund.

- **Asset C** ▴ A strategy involving selling out-of-the-money put options on the equity index. This generates a steady premium in calm markets.

The following table presents the risk characteristics of these assets under both “Normal” and “Stressed” market conditions. The “Stressed” data is drawn from a period analogous to late 2008.

| Parameter | Asset A (Equity Index) | Asset B (High-Yield Bonds) | Asset C (Short Put Options) |
| --- | --- | --- | --- |
| Annualized Volatility | 15% | 8% | 5% (Volatility of the premium income) |
| Annualized Volatility | 50% | 25% | 300% (Payoff becomes highly non-linear and loss-making) |

Now, let’s construct a $100M portfolio optimized for low standard VaR. A plausible allocation might be 40% in Asset A, 40% in Asset B, and 20% in Asset C. The low volatility and negative correlation of Asset C in normal times make it an attractive addition for a VaR-minimizing strategy. Using a simplified variance-covariance approach for demonstration, the portfolio’s [risk metrics](https://prime.greeks.live/area/risk-metrics/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) are calculated below.

> The quantitative gap between VaR and SVaR serves as a direct financial measure of a portfolio’s hidden dependencies on the fragile assumption of market stability.

The results of this analysis are stark. The portfolio, which appeared safe with a 99% 10-day VaR of approximately $4.66 million under normal conditions, reveals its true vulnerability in a crisis. The SVaR balloons to $28.31 million, over six times the standard VaR. The drivers are clear ▴ the surge in volatility across all assets, the dramatic shift in correlations from low/negative to highly positive, and the explosive, [non-linear risk](https://prime.greeks.live/area/non-linear-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) profile of the short-option strategy.

The very element (Asset C) that helped reduce the standard VaR becomes the primary engine of catastrophic loss in the stressed scenario. This quantitative exercise moves the concept from the abstract to a concrete, measurable risk management failure, underscoring the absolute necessity of a dual VaR/SVaR framework for robust portfolio governance.

![A sleek, abstract system interface with a central spherical lens representing real-time Price Discovery and Implied Volatility analysis for institutional Digital Asset Derivatives. Its precise contours signify High-Fidelity Execution and robust RFQ protocol orchestration, managing latent liquidity and minimizing slippage for optimized Alpha Generation](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-institutional-digital-asset-derivatives-execution-via-optimized-rfq-protocols-enhancing-market-microstructure.jpg)

## References

- Basel Committee on Banking Supervision. “Guidelines on Stressed Value-At-Risk (Stressed VaR).” European Banking Authority, 2012.

- Basel Committee on Banking Supervision. “Interpretive issues with respect to the revisions to the market risk framework.” Bank for International Settlements, 2011.

- Chen, J. M. “Measuring Market Risk Under the Basel Accords ▴ VaR, Stressed VaR, and Expected Shortfall.” Journal of Financial Regulation and Compliance, vol. 22, no. 4, 2014, pp. 353-371.

- Jorion, Philippe. Value at Risk ▴ The New Benchmark for Managing Financial Risk. 3rd ed. McGraw-Hill, 2007.

- Duffie, Darrell, and Kenneth J. Singleton. Credit Risk ▴ Pricing, Measurement, and Management. Princeton University Press, 2003.

- McNeil, Alexander J. Rüdiger Frey, and Paul Embrechts. Quantitative Risk Management ▴ Concepts, Techniques and Tools. Revised ed. Princeton University Press, 2015.

- Taleb, Nassim Nicholas. The Black Swan ▴ The Impact of the Highly Improbable. 2nd ed. Random House, 2010.

- Berkowitz, Jeremy, and James O’Brien. “How Accurate Are Value-at-Risk Models at Commercial Banks?” The Journal of Finance, vol. 57, no. 3, 2002, pp. 1093-1111.

- Rockafellar, R. Tyrrell, and Stanislav Uryasev. “Optimization of Conditional Value-at-Risk.” Journal of Risk, vol. 2, no. 3, 2000, pp. 21-41.

- Perignon, Christophe, and Daniel R. Smith. “The Level and Quality of Value-at-Risk Disclosure by Commercial Banks.” Journal of Banking & Finance, vol. 34, no. 2, 2010, pp. 362-377.

![A glowing central lens, embodying a high-fidelity price discovery engine, is framed by concentric rings signifying multi-layered liquidity pools and robust risk management. This institutional-grade system represents a Prime RFQ core for digital asset derivatives, optimizing RFQ execution and capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-prime-os-core-for-high-fidelity-rfq-execution-and-latent-liquidity-aggregation.jpg)

## Reflection

![A central metallic mechanism, an institutional-grade Prime RFQ, anchors four colored quadrants. These symbolize multi-leg spread components and distinct liquidity pools](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-digital-asset-derivatives-rfq-engine-prime-os.jpg)

## Beyond Measurement to Systemic Resilience

The recognition that a portfolio can be simultaneously low-risk by one metric and high-risk by another compels a shift in perspective. The goal of a risk management function transcends the mere calculation and reporting of a number. It becomes a system for interrogating the assumptions that underpin those numbers. The divergence between VaR and SVaR is not a problem to be solved in the sense of forcing the two numbers together.

Instead, the magnitude of the gap itself is a critical piece of intelligence. It provides a clear signal about the portfolio’s dependence on a particular market regime and its vulnerability to a structural break.

Thinking of this in architectural terms, a risk framework should function less like a simple fire alarm and more like a comprehensive structural engineering analysis. The fire alarm (VaR) is calibrated to detect common, everyday smoke. The structural analysis (the VaR/SVaR comparison) is designed to assess how the entire edifice will withstand an earthquake.

A portfolio manager must not only be aware of the daily risk weather but also understand the seismic faults running beneath their strategy. This requires a framework that values robustness over superficial optimization and cultivates a deep institutional skepticism toward any single measure of risk.

Ultimately, the insights gained from this dual analysis inform the strategic allocation of capital and risk. It may lead to the conclusion that certain strategies, while attractive in calm markets, carry an unacceptably high “cost of robustness” and should be limited in size. It may prompt investment in hedges that are explicitly designed to perform well during correlation breakdowns, even if they act as a drag on performance in normal times.

The process moves risk management from a passive, compliance-oriented function to an active, strategic partner in the pursuit of sustainable, all-weather returns. The final question for any portfolio manager is not “What is my VaR?” but “What are the hidden conditions that could render my VaR meaningless?”

![A futuristic metallic optical system, featuring a sharp, blade-like component, symbolizes an institutional-grade platform. It enables high-fidelity execution of digital asset derivatives, optimizing market microstructure via precise RFQ protocols, ensuring efficient price discovery and robust portfolio margin](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-prime-os-for-high-fidelity-rfq-execution-and-optimal-price-discovery.jpg)

## Glossary

<a href="https://prime.greeks.live/question/to-what-extent-does-regulatory-divergence-between-the-us-and-eu-create-actionable-arbitrage-opportunities-for-global-hft-operations/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A conceptual image illustrates a sophisticated RFQ protocol engine, depicting the market microstructure of institutional digital asset derivatives. Two semi-spheres, one light grey and one teal, represent distinct liquidity pools or counterparties within a Prime RFQ, connected by a complex execution management system for high-fidelity execution and atomic settlement of Bitcoin options or Ethereum futures](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-market-microstructure-2.jpg)

## Divergence Between

Regulatory divergence between the US and EU creates arbitrage by embedding exploitable structural and temporal inefficiencies in market protocols. </a><a href="https://prime.greeks.live/question/how-do-exchanges-define-stressed-market-conditions-for-market-makers/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Stacked precision-engineered circular components, varying in size and color, rest on a cylindrical base. This modular assembly symbolizes a robust Crypto Derivatives OS architecture, enabling high-fidelity execution for institutional RFQ protocols](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-protocol-architecture-optimized-for-high-fidelity-execution.jpg)

## Market Conditions

Exchanges define stressed market conditions as a codified, trigger-based state that relaxes liquidity obligations to ensure market continuity. </a><a href="https://prime.greeks.live/question/what-are-the-primary-risks-associated-with-ambiguous-last-look-disclosures-for-a-portfolio-manager/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A transparent geometric structure symbolizes institutional digital asset derivatives market microstructure. Its converging facets represent diverse liquidity pools and precise price discovery via an RFQ protocol, enabling high-fidelity execution and atomic settlement through a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-for-optimized-liquidity-aggregation-and-high-fidelity-execution.jpg)

## Portfolio Manager

Ambiguous last look disclosures inject execution uncertainty, creating information leakage and adverse selection risks for a portfolio manager. </a><a href="https://prime.greeks.live/area/standard-var/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precision optical system with a teal-hued lens and integrated control module symbolizes institutional-grade digital asset derivatives infrastructure. It facilitates RFQ protocols for high-fidelity execution, price discovery within market microstructure, algorithmic liquidity provision, and portfolio margin optimization via Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/08/principal-grade-digital-asset-derivatives-rfq-optics-for-high-fidelity-execution-and-optimized-liquidity.jpg)

## Standard Var

Meaning ▴ Standard VaR, or Value at Risk, quantifies the maximum expected loss of a portfolio over a defined time horizon at a specific confidence level, under normal market conditions. </a><a href="https://prime.greeks.live/area/financial-crisis/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A transparent, multi-faceted component, indicative of an RFQ engine's intricate market microstructure logic, emerges from complex FIX Protocol connectivity. Its sharp edges signify high-fidelity execution and price discovery precision for institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-engine-optimized-for-best-execution.jpg)

## Financial Crisis

Meaning ▴ A Financial Crisis represents a severe, systemic disruption within financial markets, characterized by rapid and widespread loss of confidence, sharp declines in asset valuations, significant credit contraction, and failures of key financial institutions. </a><a href="https://prime.greeks.live/area/stressed-var/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A central dark nexus with intersecting data conduits and swirling translucent elements depicts a sophisticated RFQ protocol's intelligence layer. This visualizes dynamic market microstructure, precise price discovery, and high-fidelity execution for institutional digital asset derivatives, optimizing capital efficiency and mitigating counterparty risk](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine-visualizing-high-fidelity-execution-and-market-microstructure-dynamics.jpg)

## Stressed Var

Meaning ▴ Stressed VaR represents a risk metric quantifying the potential loss in value of a portfolio or trading book over a specified time horizon under extreme, predefined market conditions. </a><a href="https://prime.greeks.live/area/diversification/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Modular institutional-grade execution system components reveal luminous green data pathways, symbolizing high-fidelity cross-asset connectivity. This depicts intricate market microstructure facilitating RFQ protocol integration for atomic settlement of digital asset derivatives within a Principal's operational framework, underpinned by a Prime RFQ intelligence layer](https://options.greeks.live/wp-content/uploads/2025/07/modular-high-fidelity-execution-architecture-for-institutional-digital-asset-derivatives-rfq-protocol-integration-and-principals-operational-framework-optimization.jpg)

## Diversification

Meaning ▴ Diversification is the strategic allocation of capital across distinct assets or strategies to reduce overall portfolio volatility and systemic risk. </a><a href="https://prime.greeks.live/area/volatility/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, dark, metallic system component features a central circular mechanism with a radiating arm, symbolizing precision in High-Fidelity Execution. This intricate design suggests Atomic Settlement capabilities and Liquidity Aggregation via an advanced RFQ Protocol, optimizing Price Discovery within complex Market Microstructure and Order Book Dynamics on a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-prime-os-high-fidelity-execution-protocol-liquidity-market-microstructure.jpg)

## Volatility

Meaning ▴ Volatility quantifies the statistical dispersion of returns for a financial instrument or market index over a specified period. </a><a href="https://prime.greeks.live/question/how-can-quantitative-models-distinguish-between-pre-hedging-and-normal-market-volatility/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, dark teal, curved component showcases a silver-grey metallic strip with precise perforations and a central slot. This embodies a Prime RFQ interface for institutional digital asset derivatives, representing high-fidelity execution pathways and FIX Protocol integration](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine.jpg)

## Normal Market

Quantitative models distinguish pre-hedging from volatility by detecting its directional, information-driven footprint in the market's microstructure. </a><a href="https://prime.greeks.live/area/correlation-breakdown/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A symmetrical, reflective apparatus with a glowing Intelligence Layer core, embodying a Principal's Core Trading Engine for Digital Asset Derivatives. Four sleek blades represent multi-leg spread execution, dark liquidity aggregation, and high-fidelity execution via RFQ protocols, enabling atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-optimized-execution.jpg)

## Correlation Breakdown

Meaning ▴ Correlation breakdown defines a critical systemic event characterized by the sudden and significant deviation from established statistical relationships between distinct asset classes or within a diversified portfolio, particularly impacting digital asset derivatives. </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">
![The image displays a central circular mechanism, representing the core of an RFQ engine, surrounded by concentric layers signifying market microstructure and liquidity pool aggregation. A diagonal element intersects, symbolizing direct high-fidelity execution pathways for digital asset derivatives, optimized for capital efficiency and best execution through a Prime RFQ architecture](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-architecture-powering-institutional-digital-asset-derivatives-high-fidelity-execution-via-optimized-rfq-protocols.jpg)

## Risk Management

Meaning ▴ Risk Management is the systematic process of identifying, assessing, and mitigating potential financial exposures and operational vulnerabilities within an institutional trading framework. </a><a href="https://prime.greeks.live/area/basel-iii/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, symmetrical digital asset derivatives component. It represents an RFQ engine for high-fidelity execution of multi-leg spreads](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-engine-for-optimized-market-microstructure.jpg)

## Basel Iii

Meaning ▴ Basel III represents a comprehensive international regulatory framework developed by the Basel Committee on Banking Supervision, designed to strengthen the regulation, supervision, and risk management of the banking sector globally. </a><a href="https://prime.greeks.live/area/risk-metrics/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Abstract geometry illustrates interconnected institutional trading pathways. Intersecting metallic elements converge at a central hub, symbolizing a liquidity pool or RFQ aggregation point for high-fidelity execution of digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-cross-market-microstructure-for-digital-asset-derivatives.jpg)

## Risk Metrics

Meaning ▴ Risk Metrics are quantifiable measures engineered to assess and articulate various forms of exposure associated with financial positions, portfolios, or operational processes within the domain of institutional digital asset derivatives. </a><a href="https://prime.greeks.live/area/non-linear-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A spherical, eye-like structure, an Institutional Prime RFQ, projects a sharp, focused beam. This visualizes high-fidelity execution via RFQ protocols for digital asset derivatives, enabling block trades and multi-leg spreads with capital efficiency and best execution across market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-grade-prime-os-rfq-protocol-digital-asset-derivatives-block-trade-execution.jpg)

## Non-Linear Risk

Meaning ▴ Non-linear risk quantifies the sensitivity of a portfolio or instrument's value to changes in underlying market factors, where this sensitivity is not constant but varies disproportionately with the magnitude or direction of the factor's movement. </a>

**Tags:** [Standard VaR](https://options.greeks.live/area/standard-var/), [Quantitative Finance](https://options.greeks.live/area/quantitative-finance/), [Correlation Breakdown](https://options.greeks.live/area/correlation-breakdown/), [Market Regimes](https://options.greeks.live/area/market-regimes/), [Volatility](https://options.greeks.live/area/volatility/), [Tail Risk](https://options.greeks.live/area/tail-risk/)	

## Discover More

- 
### [What Are the Strategic Flaws in VaR Based Margin Models?](https://options.greeks.live/question/what-are-the-strategic-flaws-in-var-based-margin-models/)
![A marbled sphere symbolizes a complex institutional block trade, resting on segmented platforms representing diverse liquidity pools and execution venues. This visualizes sophisticated RFQ protocols, ensuring high-fidelity execution and optimal price discovery within dynamic market microstructure for digital asset derivatives. It reflects capital efficiency and intelligent smart order routing.](https://options.greeks.live/wp-content/uploads/2025/07/principal-rfq-aggregation-digital-asset-derivative-execution-optimization.jpg)

VaR-based margin models contain architectural flaws that understate tail risk and amplify systemic shocks through procyclicality.

- 
### [Using Conditional Value at Risk to Build a Resilient Portfolio](https://options.greeks.live/guide/using-conditional-value-at-risk-to-build-a-resilient-portfolio/)
![A sleek, dark teal, curved component showcases a silver-grey metallic strip with precise perforations and a central slot. This embodies a Prime RFQ interface for institutional digital asset derivatives, representing high-fidelity execution pathways and FIX Protocol integration. The dark environment hints at dark pool operations and private quotation via RFQ protocols, ensuring capital efficiency.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine.jpg)

CVaR quantifies the expected loss in worst-case scenarios, engineering a portfolio for resilience against extreme market stress.

- 
### [To What Extent Does the Increased Capital Efficiency of Var Justify Its Lower Predictability for a Trading Desk?](https://options.greeks.live/question/to-what-extent-does-the-increased-capital-efficiency-of-var-justify-its-lower-predictability-for-a-trading-desk/)
![A modular institutional trading interface displays a precision trackball and granular controls on a teal execution module. Parallel surfaces symbolize layered market microstructure within a Principal's operational framework, enabling high-fidelity execution for digital asset derivatives via RFQ protocols.](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-institutional-digital-asset-derivatives-rfq-protocol-controls.jpg)

VaR's capital efficiency is justified only when integrated into a framework that uses stress testing and ES to manage its predictability gaps.

- 
### [In What Ways Can a Trader Quantify and Manage the Risks Associated with the Breakdown of the “Smart Trading” Model’s Assumptions?](https://options.greeks.live/question/in-what-ways-can-a-trader-quantify-and-manage-the-risks-associated-with-the-breakdown-of-the-smart-trading-models-assumptions/)
![A sophisticated metallic mechanism, split into distinct operational segments, represents the core of a Prime RFQ for institutional digital asset derivatives. Its central gears symbolize high-fidelity execution within RFQ protocols, facilitating price discovery and atomic settlement. This system manages fragmented liquidity and optimizes portfolio margin for block trades.](https://options.greeks.live/wp-content/uploads/2025/07/precision-rfq-engine-for-institutional-digital-asset-derivatives-trading.jpg)

A trader manages model risk by quantifying assumption sensitivity and implementing dynamic, protocol-driven responses.

- 
### [What Specific Risk Metrics Do Specialized Dealers Use to Price Correlated Option Positions?](https://options.greeks.live/question/what-specific-risk-metrics-do-specialized-dealers-use-to-price-correlated-option-positions/)
![Precision-engineered abstract components depict institutional digital asset derivatives trading. A central sphere, symbolizing core asset price discovery, supports intersecting elements representing multi-leg spreads and aggregated inquiry. Surrounding structures denote a robust Prime RFQ framework for high-fidelity execution and capital efficiency within market microstructure.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-microstructure-optimization.jpg)

Specialized dealers use a system of cross-asset and higher-order Greeks to price the non-linear, interdependent risks of correlated positions.

- 
### [The Definitive Method for Calculating Your Portfolio’s True Risk](https://options.greeks.live/guide/the-definitive-method-for-calculating-your-portfolios-true-risk/)
![Abstract geometric forms depict a sophisticated Principal's operational framework for institutional digital asset derivatives. Sharp lines and a control sphere symbolize high-fidelity execution, algorithmic precision, and private quotation within an advanced RFQ protocol. This visualizes market microstructure optimization and robust capital efficiency.](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-architecture-for-optimized-digital-asset-derivatives-rfq-protocols.jpg)

Calculate your portfolio's true breaking point by quantifying its expected shortfall in a crisis.

- 
### [How Do Extended Quote Commitments Influence Market Maker Risk Management?](https://options.greeks.live/question/how-do-extended-quote-commitments-influence-market-maker-risk-management/)
![A central metallic bar, representing an RFQ block trade, pivots through translucent geometric planes symbolizing dynamic liquidity pools and multi-leg spread strategies. This illustrates a Principal's operational framework for high-fidelity execution and atomic settlement within a sophisticated Crypto Derivatives OS, optimizing private quotation workflows.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-facilitating-high-fidelity-price-discovery-and-optimal-capital-efficiency-within-advanced-market-microstructure.jpg)

Extended quote commitments amplify market maker temporal and inventory risks, demanding advanced dynamic hedging and capital optimization.

- 
### [A Professional’s Guide to Beta-Weighted Portfolio Hedging](https://options.greeks.live/guide/a-professionals-guide-to-beta-weighted-portfolio-hedging/)
![Complex metallic and translucent components represent a sophisticated Prime RFQ for institutional digital asset derivatives. This market microstructure visualization depicts high-fidelity execution and price discovery within an RFQ protocol. The intricate design suggests algorithmic trading and capital efficiency across multi-leg spreads.](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-institutional-digital-asset-derivatives-rfq-protocol-dynamics.jpg)

A beta-weighted hedge insulates your portfolio from market chaos, creating a platform for pure alpha generation.

- 
### [A Systematic Guide to Identifying High-Potential Crypto Projects before the Market](https://options.greeks.live/guide/a-systematic-guide-to-identifying-high-potential-crypto-projects-before-the-market/)
![A sleek, institutional-grade system processes a dynamic stream of market microstructure data, projecting a high-fidelity execution pathway for digital asset derivatives. This represents a private quotation RFQ protocol, optimizing price discovery and capital efficiency through an intelligence layer.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-rfq-digital-asset-derivatives-execution-microstructure-prime-os.jpg)

Unearth crypto's next giants with a systematic guide to superior project identification and strategic capital deployment.

---

## Raw Schema Data

```json
{
    "@context": "https://schema.org",
    "@type": "BreadcrumbList",
    "itemListElement": [
        {
            "@type": "ListItem",
            "position": 1,
            "name": "Home",
            "item": "https://options.greeks.live"
        },
        {
            "@type": "ListItem",
            "position": 2,
            "name": "Question",
            "item": "https://options.greeks.live/question/"
        },
        {
            "@type": "ListItem",
            "position": 3,
            "name": "Can a Portfolio Optimized for Low VaR Simultaneously Have a High Stressed VaR?",
            "item": "https://options.greeks.live/question/can-a-portfolio-optimized-for-low-var-simultaneously-have-a-high-stressed-var/"
        }
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "Organization",
    "@id": "https://greeks.live/#organization",
    "name": "Greeks.Live",
    "url": "https://greeks.live/",
    "description": "Greeks.live is the definitive toolkit for the professional options trader, dedicated to empowering our users with institutional-grade data, advanced analytics, and a comprehensive suite of trading tools designed to provide a decisive edge in the market. Every article and guide published under the Greeks.live name is a product of our deep commitment to data-driven analysis and our mission to support the global trading community.",
    "email": "support@greeks.live",
    "logo": {
        "@type": "ImageObject",
        "url": "https://options.greeks.live/wp-content/uploads/2025/07/Greeks.Live-Logo-Icon.svg"
    },
    "hasPart": [
        {
            "@type": "WebSite",
            "name": "About Us",
            "url": "https://about.greeks.live"
        },
        {
            "@type": "WebSite",
            "name": "App Download Page",
            "url": "https://about.greeks.live/#/download/basic_trade"
        },
        {
            "@type": "WebSite",
            "name": "Newcomers' Guide",
            "url": "https://twisty-sign-c8b.notion.site/Guide-for-Greeks-live-X-Deribit-Newbies-5a08a3052822427d800af6eaf3704c8d"
        },
        {
            "@type": "WebSite",
            "name": "Knowledge Base",
            "url": "https://linktr.ee/greeks.live"
        },
        {
            "@type": "WebSite",
            "name": "Option Terminology",
            "url": "https://greekslive.notion.site/88dfc00e7c584d4d8969b6302a79a12f?pvs=4"
        },
        {
            "@type": "WebSite",
            "name": "Terms of Service",
            "url": "https://greeks.live/#/tos"
        },
        {
            "@type": "WebSite",
            "name": "Disclaimer",
            "url": "https://greeks.live/#/disclaimer"
        }
    ],
    "sameAs": [
        "https://x.com/greekslive",
        "https://youtube.com/@greeks_live?si=-KjT0Lkw4WUCI0tD",
        "https://t.me/greekslive_notifications",
        "https://t.me/greekslive",
        "https://pinterest.com/greekslive/"
    ],
    "makesOffer": [
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "RFQ Platform",
                "url": "https://rfq.greeks.live",
                "description": "Execute institutional-grade block trades for crypto options and futures. This platform provides deep, over-the-counter (OTC) liquidity via a professional Request for Quote system.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Lending Tools",
                "url": "https://lend.greeks.live",
                "description": "Manage crypto lending and borrowing activities to earn yield or secure loans. This suite of tools helps users analyze interest rates and manage collateralized debt positions.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Data Lab",
                "url": "https://greeks.live/#/deribit/tools/datalab/BTC",
                "description": "Analyze historical and real-time options data with advanced metrics. This tool is designed for backtesting strategies and identifying market trends through comprehensive data visualization.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Profit & Loss Analysis (PnL)",
                "url": "https://greeks.live/#/deribit/tools/pnl_analysis",
                "description": "Track and analyze the Profit and Loss (PnL) of your options portfolio. This tool provides detailed performance metrics to help traders evaluate and refine their strategies.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Position Visualization",
                "url": "https://greeks.live/#/deribit/tools/pv/BTC",
                "description": "Visualize complex options positions and their corresponding risk profiles. This tool generates payoff diagrams to help traders intuitively understand potential profit, loss, and exposure.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Options Calculator",
                "url": "https://greeks.live/#/deribit/tools/calculator",
                "description": "Calculate the theoretical price and risk parameters ('the Greeks') of crypto options. An essential tool for pricing new trades and analyzing the sensitivity of existing positions.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Greeks.live Main Platform",
                "url": "https://greeks.live/",
                "description": "The central hub for the Greeks.live suite of professional cryptocurrency options and derivatives trading tools. Access analytics, manage positions, and explore the ecosystem.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Community Forum",
                "url": "https://t.greeks.live",
                "description": "Join the official Greeks.live community. Connect with other traders, share insights, and receive the latest updates directly from the team.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Greeks.live for Deribit",
                "url": "http://deribit.greeks.live",
                "description": "A dedicated interface for trading on the Deribit exchange. This platform leverages Greeks.live's advanced analytics and tools specifically for users of Deribit's options and futures markets.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "Greeks.live for OKX",
                "url": "http://okx.greeks.live",
                "description": "A dedicated interface for trading on the OKX exchange. This platform integrates Greeks.live's powerful analytics with the OKX marketplace, focusing on its options and derivatives products.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "GLVS.AI Trading Platform",
                "url": "https://www.glvs.ai/",
                "description": "An AI-powered platform for automated crypto options trading. Leverage advanced algorithms and data-driven signals to develop and deploy sophisticated, hands-free trading strategies.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        },
        {
            "@type": "Offer",
            "itemOffered": {
                "@type": "Service",
                "name": "API Testnet & Sandbox",
                "url": "https://test.greeks.live",
                "description": "A dedicated testnet environment for developers to test their API integrations and automated trading strategies. This sandbox allows for full functionality testing without risking real funds.",
                "provider": {
                    "@id": "https://greeks.live/#organization"
                }
            }
        }
    ],
    "subOrganization": [
        {
            "@type": "Organization",
            "name": "GreeksLive HK Co., Limited",
            "email": "support@greeks.live",
            "telephone": "+852-56418949",
            "address": {
                "@type": "PostalAddress",
                "streetAddress": "Unit 11, 27/F, K. Wah Centre, 191 Java Road",
                "addressLocality": "Hong Kong",
                "addressRegion": "North Point",
                "addressCountry": "CN",
                "postalCode": "0000"
            },
            "geo": {
                "@type": "GeoCoordinates",
                "latitude": "22.2932357",
                "longitude": "114.2022026"
            },
            "image": "https://options.greeks.live/wp-content/uploads/2025/08/Wah-Centre-Hong-Kong.jpg"
        }
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "Article",
    "mainEntityOfPage": {
        "@type": "WebPage",
        "@id": "https://options.greeks.live/question/can-a-portfolio-optimized-for-low-var-simultaneously-have-a-high-stressed-var/"
    },
    "headline": "Can a Portfolio Optimized for Low VaR Simultaneously Have a High Stressed VaR? \u25b4 Question",
    "description": "A portfolio optimized for low VaR can have a high Stressed VaR because its stability relies on market conditions that evaporate during a crisis. \u25b4 Question",
    "url": "https://options.greeks.live/question/can-a-portfolio-optimized-for-low-var-simultaneously-have-a-high-stressed-var/",
    "datePublished": "2025-08-12T20:50:13+00:00",
    "dateModified": "2025-08-12T20:50:15+00:00",
    "articleSection": [
        "Question"
    ],
    "author": {
        "@id": "https://greeks.live/#organization"
    },
    "publisher": {
        "@id": "https://greeks.live/#organization"
    },
    "image": {
        "@type": "ImageObject",
        "url": "https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-prime-os-core-for-high-fidelity-rfq-execution-and-latent-liquidity-aggregation.jpg",
        "caption": "A sophisticated, spherical institutional-grade system is presented, centered by a luminous lens signifying a high-fidelity price discovery engine. Its concentric layers represent complex market microstructure, enabling multi-leg spread execution and robust portfolio margin management for digital asset derivatives. This Prime RFQ node facilitates optimized RFQ protocols, ensuring best execution, mitigating counterparty risk, and aggregating latent liquidity for block trades, driving alpha generation."
    },
    "keywords": [
        "Basel III",
        "Correlation Breakdown",
        "Diversification",
        "Financial Crisis",
        "Market Regimes",
        "Non-Linear Risk",
        "Portfolio Optimization",
        "Quantitative Finance",
        "Risk Management",
        "Risk Metrics",
        "Standard VaR",
        "Stressed VaR",
        "Tail Risk",
        "Value-at-Risk",
        "Volatility"
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "WebSite",
    "url": "https://options.greeks.live/",
    "potentialAction": {
        "@type": "SearchAction",
        "target": "https://options.greeks.live/?s=search_term_string",
        "query-input": "required name=search_term_string"
    }
}
```


---

**Original URL:** https://options.greeks.live/question/can-a-portfolio-optimized-for-low-var-simultaneously-have-a-high-stressed-var/
