Candle Replay

Candle Replay is a browser-based trading simulator built as a single-person project for the OpenAI 2026 hackathon. The author states it allows users to practice trading one candle at a time without seeing future price movements, aiming to reduce hindsight bias in market analysis.

The product is described as a web application that processes CSV data and reveals historical market information step-by-step, with controls for replay speed, chart layout, and trade simulation. It includes features like session saving, CSV export, bilingual interface (Japanese/English), and synthetic demo data.

Key commercial signals are absent: no evidence of revenue, customers, pricing, or adoption. The project is self-reported as a hackathon submission, with no indication of traction or market validation beyond the author’s own account.

The description states that Candle Replay is a browser-based trading practice simulator. It operates on historical market data, revealing one candle at a time without showing future price movements.

Key functional elements include:

• Play, pause, step, and speed controls
• Support for 1-minute, 3-minute, 5-minute, and 15-minute charts
• Two-chart layout option
• Simulated Buy/Sell orders with profit/loss tracking
• Trade history and session statistics review
• Ability to add notes, moving averages, and horizontal price levels
• Session saving and CSV export capability
• Bilingual (Japanese/English) interface

The author describes it as designed for education and trading practice, not investment advice or guaranteed results.

Inference The product appears to be a technical prototype built using React, Next.js, TypeScript, and OpenAI tools. It uses CSV data input and implements time-bound logic to prevent future candle visibility during replay.

The author positions Candle Replay as a tool for realistic trading practice, specifically targeting the problem of hindsight bias in chart analysis.

Claims made:

• Users can "practice trading one candle at a time—without seeing the future"
• Designed to provide a training environment that avoids future price visibility
• Intended for education and practice, not investment advice or result guarantees

Inference The positioning reflects an intent to offer a more authentic simulation experience than traditional charting tools, where future data is visible. This implies a focus on behavioral finance or skill-building rather than direct trading.

There is no evidence of prior positioning evolution or market feedback incorporated into the product.

The description states that Candle Replay is designed for education and trading practice, with no mention of specific customer segments beyond that.

It does not identify:

• Specific user personas (e.g., beginner traders, educators, institutional users)
• Industry verticals or use cases
• Any target market segmentation

Inference Based on the description, the ICP likely includes individuals interested in trading education or deliberate practice, possibly including students, hobbyists, or aspiring traders. However, no explicit targeting is evidenced.

There is no evidence of a business model or pricing structure in the provided description.

The author states that Candle Replay:

• Does not provide investment advice
• Does not guarantee trading results
• Is designed for practice and education

No mention of monetization, subscriptions, licensing, or paid features.

Inference The project appears to be a prototype with no commercial intent evident from the self-report. It may be offered as a free tool or open-source project, but this is not stated.

The author reports that Candle Replay was built using:

• Frontend: React, Next.js, TypeScript, CSS3, HTML5
• Backend/Tools: Codex, Vercel
• Data Handling: CSV market data processing, multi-timeframe synchronization
• Features Implemented:
  • Play/pause/step controls
  • Multi-chart layouts
  • Trade simulation and P&L tracking
  • Session saving and CSV export
  • Bilingual UI (Japanese/English)
  • One-click demo with synthetic data

Challenges mentioned include:

• Preventing future information from appearing across synchronized timeframes
• Synchronizing controls, positions, and session data while handling large datasets (>100k rows)

Accomplishments include:

• Deployment on Vercel
• Automated testing (362 tests passed)
• Production-ready build with linting and verification

Inference The technical stack suggests a modern web application built for performance and usability. The use of Codex indicates AI-assisted development, though no evidence of production deployment or scalability beyond the demo is given.

There is no evidence of traction, adoption, or user engagement in the provided description.

The project is described as a single-person hackathon submission, with no mention of:

• Users
• Customers
• Revenue
• Downloads
• Usage metrics
• Market feedback
• Product iteration history

The author notes that it was completed during Build Week and plans to conduct user testing afterward, but no such testing or results are reported.

Inference The product is at a very early stage—likely prototype or MVP—and has not yet demonstrated any measurable traction or maturity in the market.

There is no evidence of competitive analysis or awareness of existing tools in the space.

The description does not reference:

• Competitors
• Similar products
• Market gaps addressed
• Differentiation from other trading simulators or educational platforms

Inference No competitive positioning or landscape is evident. The author does not appear to have benchmarked against other tools, nor does the description suggest awareness of existing solutions.

Key risks and red flags based on the self-reported account:

• Prototype-only status: The project is described as a hackathon submission with no evidence of further development or commercialization.
• No revenue or customer data: No indication of monetization, users, or adoption.
• Single-person team: Limited resources for scaling or product development.
• Unverified claims: All features and functionality are self-reported without external validation.
• Lack of market context: No evidence of understanding of target markets or competitive landscape.

Inference The lack of traction, commercial viability, or product-market fit is a major concern. The tool may not have progressed beyond initial concept or testing phase.

1. What is the current status of the product? Is it live and accessible to users?
2. Have you conducted any user testing or received feedback from traders or educators?
3. Are there plans for monetization, and if so, what model are you considering?
4. How do you plan to scale beyond a single-person development effort?
5. What is the source of your historical market data? Is it proprietary or publicly available?
6. Do you have any partnerships or integrations with educational institutions or trading communities?
7. What are the key performance indicators (KPIs) you track for product success?