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Simulation of Finantial Scenarios

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BY USE CASES

To anticipate how a portfolio, market segment, or financial strategy will behave under different conditions — such as interest rate hikes, inflation changes, or geopolitical events.

The Challenge:

Simulating financial scenarios is computationally intensive and often limited by traditional models that:

  • Depend on predefined rules and assumptions

  • Struggle with nonlinear dynamics or black swan events

  • Can’t efficiently explore the vast number of possible futures

This makes it hard for institutions to stress test portfolios, plan under uncertainty, or prepare for market shocks with precision.

Bright living room with modern inventory
Bright living room with modern inventory

Quantum-Inspired Solution: Smarter Simulations with HessQ

HessQ leverages Quantum-Inspired Optimization (QUBO) and probabilistic modeling to simulate and analyze thousands of potential market conditions simultaneously — without needing a quantum computer.

Scenario Encoding

Market variables (interest rates, volatility, inflation, asset correlations, etc.) are encoded into high-dimensional QUBO structures.

Inspired by quantum parallelism, HessQ explores numerous “what-if” situations at once, not sequentially.

It identifies potential risks, tipping points, and opportunities across simulated realities — even the ones traditional models often ignore.

Parallel Exploration
Outcome Mapping
Bright living room with modern inventory
Bright living room with modern inventory

The Result:

Outputs Delivered:

  • Dynamic stress-testing models

  • Forecasts under diverse scenarios (e.g., economic slowdown, currency shocks)

  • Early warning signals for systemic risk or performance drops

  • Visual heatmaps of best/worst-case projections

Why HessQ Outperforms Traditional Models

  • Thinks in possibilities: Explores a wider space of potential outcomes

  • Uncovers hidden risk: Detects fragile zones traditional models overlook

  • Optimizes forward planning: Supports scenario-based decision making

  • Adapts as markets evolve: Adjusts simulations with real-time data

  • Informs strategy under uncertainty: Essential for volatile or high-risk periods