This insight was synthesized by AI from public community discussions. We do not display original user posts or comments verbatim—all content has been rewritten and aggregated. Verify before acting on it.
Futures Data Normalization Bridge for Charting Platforms
A micro-SaaS data pipeline that takes high-fidelity raw futures data (like Databento) and correctly formats, rolls, and flattens it into continuous contracts for seamless import into popular retail charting tools that suffer from opaque proprietary rolling logic.
Why this matters
As a systematic futures trader, you want to backtest your algorithms on the most reliable platforms available. However, you quickly realize that mainstream retail charting software uses proprietary, hidden logic to stitch together expiring futures contracts. This creates false price gaps and ruins the integrity of your backtest. To fix this, you purchase expensive, raw institutional data from specialized providers. But now you face a new nightmare: manually writing complex scripts to flatten the contracts using standard adjustment methods just so you can import them back into your charting software. It is a tedious, technical hurdle that distracts you from actually building trading strategies.
- · Built for Advanced retail futures traders relying on sophisticated technical analysis and custom indicators..
- · Most likely monetization: Usage-based or tiered SaaS subscription.
The Pain · Narrative
As a systematic futures trader, you want to backtest your algorithms on the most reliable platforms available. However, you quickly realize that mainstream retail charting software uses proprietary, hidden logic to stitch together expiring futures contracts. This creates false price gaps and ruins the integrity of your backtest. To fix this, you purchase expensive, raw institutional data from specialized providers. But now you face a new nightmare: manually writing complex scripts to flatten the contracts using standard adjustment methods just so you can import them back into your charting software. It is a tedious, technical hurdle that distracts you from actually building trading strategies.
Score Breakdown
Market Signal
Go-to-Market
Retail algorithmic futures traders trading ES/NQ who are frustrated by backtest discrepancies in major charting platforms.
~15,000 highly technical futures traders
Direct outreach in quantitative trading Discord servers and specialized futures forums
$15/month or $99 one-time script license
Secure 15 paid users from a targeted beta launch in niche futures trading communities
MVP Scope · 1–2 weeks
- Research and document the exact import format requirements for the target retail charting platform.
- Build a Python utility to pull raw ES/NQ futures data from a provider like Databento.
- Implement standard Panama adjustment logic to stitch expired contracts together.
- Implement standard Ratio adjustment logic as a secondary option.
- Validate the output data against known institutional benchmarks for accuracy.
- Wrap the Python utility in a simple web interface or deliverable CLI tool.
- Create an automated formatter that outputs the stitched data perfectly for charting platform ingestion.
- Write a detailed tutorial on how to bypass the charting platform's proprietary continuous contracts using this data.
- Set up a basic Stripe checkout for access to the tool.
- Distribute the tutorial as a lead magnet in algorithmic trading communities.
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1The total addressable market is extremely small, as it only targets developers trading futures who care about data micro-structure.
- 2Data providers may change their terms of service to restrict the repackaging or processing of their raw streams via third-party tools.
- 3The technical barrier to entry for the end user (uploading custom data into charting platforms) might still be too high.
Evidence Summary
How AI synthesized this insight — no verbatim quotes
Commenters expressed deep frustration with how major retail charting tools handle continuous futures contracts, noting that proprietary rolling methods corrupt backtesting results. Traders actively purchase high-quality raw data to solve this but struggle with the complex technical task of properly flattening and integrating it back into their primary testing environments. They are actively seeking reliable workarounds to model actual price action without false signals.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Validate
Promising signals, but needs confirmation. Create a landing page, collect email sign-ups, then decide.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
Futures Data Normalization Bridge for Charting Platforms
Sub-headline
A micro-SaaS data pipeline that takes high-fidelity raw futures data (like Databento) and correctly formats, rolls, and flattens it into continuous contracts for seamless import into popular retail charting tools that suffer from opaque proprietary rolling logic.
Who It's For
For Advanced retail futures traders relying on sophisticated technical analysis and custom indicators.
Feature List
✓ Automated Panama and Ratio adjustment options for continuous contracts ✓ API integration directly with premium raw data providers ✓ Export formatter specifically designed for popular charting software ingestion ✓ Historical gap-analysis reporting
Where to Validate
Share your landing page in r/r/algotrading — that's exactly where these pain points were discovered.
Sign up to unlock full deep analysis
GTM, MVP scope, why-it-might-fail, ActionPlan Copy Kit. Free signup grants 10 detail views/month.
Other opportunities in the same theme
Auto-clustered by AI from related discussions