~ Enhancing Competitiveness Through Faster Computation, High-Precision Forecasting, and Optimization ~

XYZ Corporation

1. Our Understanding

Business Environment

We understand that your company seeks to strengthen competitiveness in the trading business amid rapid developments in quantum technology and a volatile market environment.

From the external environment perspective, the following factors are noteworthy:

• Political Factors
  Governments worldwide are strategically advancing research and development in quantum technology. In Japan, the Cabinet Office has formulated the Quantum Technology Innovation Strategy.
• Economic Factors
  Geopolitical risks and trade frictions affect exchange rates and capital flows, leading to increased volatility in financial markets. Additionally, fluctuations in inflation and monetary policy drive changes in interest rates, impacting investment strategies.
• Social Factors
  Many companies are promoting DX (Digital Transformation) to improve operational efficiency and competitiveness. Competitors are expanding trading revenue opportunities by leveraging advanced technologies.
• Technological Factors
  Quantum computers are continuously evolving and are being increasingly applied in fields like stock return forecasting and portfolio optimization in the financial industry.

We believe quantum technology can significantly enhance trading operations and expand revenue opportunities.

2. Solutions to the Challenges

Key Challenges in Current Trading Operations

• Limits of Calculation Speed and Precision
  With the explosive growth in data volume and complexity of algorithms, traditional computing infrastructure struggles to process tasks like real-time portfolio optimization and stock return forecasting. Long computation times cause delays in decision-making.
• Lack of Quantum Technology Talent
  There is a lack of internal personnel with expertise in quantum technology, making it difficult for engineering teams to develop and operate quantum algorithms.
• Constraints on Development Costs and Time
  Building a quantum trading system from scratch demands significant resources, making it hard to adopt in-house.

Our Solutions

XYZ Corporation addresses these challenges through a SaaS-based quantum computing service:

• High-Speed and High-Precision Computing Resources
  Quantum algorithms deliver greater accuracy and ultra-fast processing capabilities compared to conventional approaches.
• Platform Requiring No Specialist Knowledge
  Our platform allows users to perform advanced quantum computations by simply inputting data. We provide expert support for swift onboarding and ongoing assistance.
• Reduced Initial Investment and Shorter Development Time
  Being SaaS-based, no hardware investment is required. Pre-built algorithm libraries eliminate the need for development from scratch.

3. Service Overview

XYZ’s platform is a cloud-based SaaS quantum computing solution equipped with powerful trading-focused quantum algorithms.

Key Features

• Cloud-Based & Hardware-Independent
  Accessible via browser or API with no hardware installation needed. Multiple quantum computers are supported, allowing automatic selection of optimal computing resources. Users also benefit automatically from ongoing improvements in quantum hardware.
• Pre-Built Powerful Algorithms
  Supports algorithms optimized for small to medium-sized quantum computers, including cutting-edge quantum circuit learning and quantum approximate optimization. No quantum programming is needed—just input data.
• Multiple Use Cases for Trading
  • Portfolio Optimization: Capable of deriving highly optimal portfolios (maximizing expected returns) even as asset combinations increase, in significantly less time.
  • Stock Return Forecasting: Quantum machine learning captures subtle market correlations and improves prediction accuracy beyond traditional machine learning.

4. Competitive Comparison

XYZ’s solution has clear advantages in versatility and cost-effectiveness compared to other providers.

Item	XYZ	Company A	Company B
Cloud Environment	Supported	Not Supported	Not Supported
Hardware Dependency	Independent	Dependent	Dependent
Quantum Processor	Multiple Supported	Single Only	None (Traditional HPC)
Speed	Ultra-fast	Ultra-fast	Fast
Development Environment	API, SDK	SDK	SDK
Use Cases	Finance, Quantum Chemistry	Quantum Chemistry	General
Adaptability to Tech Advancements	High (multi-hardware support)	Medium (single hardware)	Low (manual updates)
Introduction Cost	Low	Medium (vendor lock-in)	High (requires investment)

5. Implementation Effects

Significant improvements are expected in both speed and accuracy of trading operations:

• Portfolio Optimization
  Calculation time for large-scale portfolios is reduced from 3 hours to 18 minutes using quantum approximate optimization—a ~90% reduction.
• Stock Return Forecasting
  More advanced data pattern analysis enables better feature extraction, improving prediction accuracy by approximately 20%.

6. Case Study – D Securities Co., Ltd.

D Securities successfully built stock investment portfolios based on forecasts generated by our algorithms, achieving better performance.

Challenges Before Implementation

• Delayed decision-making in trading
• Time-consuming stock price forecasts and portfolio recalculations
• Inability to react promptly to market changes
• Lost revenue opportunities
• Inefficient operations due to inadequate modeling of asset correlations

Benefits After Implementation

• Real-time or near real-time portfolio adjustments and price forecasting
• Faster and more accurate decision-making on trading strategies
• 15% improvement in Sharpe ratio
• Significant enhancement in portfolio risk-return profile
• Revenue improvement and risk reduction amounting to several hundred million yen annually

7. Pricing Plans

Billing is based on consumed compute resources and number of API calls on a monthly basis.

• Standard Plan – ¥500,000/month
  • Suitable for small teams analyzing small to mid-size portfolios or conducting regular stock forecasts
    • Initial Setup Fee: ¥1,000,000
    • Up to 2 accounts
    • 50 compute hours/month (¥4,000/hour overage)
    • 50,000 API calls/month (¥1 per excess call)
    • Support via chat during business hours
• Premium Plan – ¥2,000,000/month
  • Ideal for medium to large teams needing high compute power and real-time responsiveness
    • Initial Setup Fee: ¥1,000,000
    • Up to 8 accounts
    • 200 compute hours/month (¥3,500/hour overage)
    • 200,000 API calls/month (¥0.8 per excess call)
    • 24-hour support via chat and phone
• Custom Plan – Quote Upon Request
  • Tailored for large teams or those with special requirements
    • Large-scale compute resource allocation
    • Discount based on usage scale
    • Custom algorithm development available

8. Implementation Process

The typical schedule from application to full operation is approximately 1.5 months.

1. Application (a few days)
   • Fill out application form
   • Sign NDA
2. Preparation (1–2 weeks)
   • Conduct kickoff meeting
   • Gather business requirements and assess current system
3. Contract (a few days)
   • Finalize proposal details and contract terms
   • Prepare and sign agreement
4. Test Environment Setup & Verification (2–3 weeks)
   • Issue test account and set up API connections with internal systems
   • Configure security (e.g., access restrictions)
   • Run pilot tests on limited use cases using partial real data
   • Validate output against existing methods
5. Production Environment Setup (1 week)
   • Issue production account and integrate with live systems
   • Begin full system operation covering all target assets and data