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API API for Niche Market Sentiment & Macro Indicators
A clean, RESTful API providing historical and daily updates for hard-to-source market sentiment metrics like options ratios, credit spread variations, and market breadth.
Why this matters
When building an algorithmic trading model, you inevitably need reliable sentiment data to measure market fear. You spend countless hours trying to locate clean historical data for metrics like options ratios or specific credit spreads. Existing institutional platforms lock this information behind massive enterprise paywalls, while free exchange websites only offer clunky daily files that require brittle custom scrapers. You just want a simple API endpoint that delivers twenty years of clean, aligned historical data straight into your Python environment so you can focus on model building instead of data janitorial work.
- · Built for Independent quantitative developers and retail algorithmic traders building automated risk models..
- · Most likely monetization: SaaS subscription.
The Pain · Narrative
When building an algorithmic trading model, you inevitably need reliable sentiment data to measure market fear. You spend countless hours trying to locate clean historical data for metrics like options ratios or specific credit spreads. Existing institutional platforms lock this information behind massive enterprise paywalls, while free exchange websites only offer clunky daily files that require brittle custom scrapers. You just want a simple API endpoint that delivers twenty years of clean, aligned historical data straight into your Python environment so you can focus on model building instead of data janitorial work.
Score Breakdown
Market Signal
Go-to-Market
Independent quant developers and algorithmic trading hobbyists writing Python scripts to manage their personal portfolios.
~30K highly active algorithmic trading hobbyists globally.
Targeted posts in quantitative finance developer communities showcasing how to retrieve the data in three lines of Python.
$39/month
25 paying subscribers generating $1,000 MRR within the first 6 weeks of launch.
MVP Scope · 1–2 weeks
- Identify 3 publicly available but fragmented sources for options ratios and credit spreads.
- Write Python ingestion scripts to download and parse historical data from these sources.
- Clean the aggregated data, handle missing values, and store it in a PostgreSQL database.
- Set up a basic FastAPI application to serve the time-series data.
- Deploy the database and API to a low-cost cloud provider.
- Implement basic API key authentication and rate limiting.
- Create endpoints for both raw daily data and pre-calculated moving averages.
- Build a simple landing page explaining the datasets available with code snippets.
- Integrate Stripe for monthly subscription billing and API key generation.
- Draft a launch post detailing the pain of data scraping and how this API solves it.
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1Upstream data providers might issue cease-and-desist letters regarding unauthorized redistribution of their proprietary metrics.
- 2Traders might just write the scraping scripts themselves rather than paying a monthly fee, severely limiting the addressable market.
- 3The historical data might contain subtle errors or look-ahead biases that ruin backtests, destroying trust in the product.
Evidence Summary
How AI synthesized this insight — no verbatim quotes
Multiple commenters expressed frustration over locating clean historical data for essential sentiment metrics. Several developers shared their exact workarounds, which involve writing custom code to pull daily files from exchange websites. Furthermore, users noted that major data vendors have recently moved these specific datasets behind paywalls, indicating clear commercial value and an unserved mid-market segment.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Build
Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
API API for Niche Market Sentiment & Macro Indicators
Sub-headline
A clean, RESTful API providing historical and daily updates for hard-to-source market sentiment metrics like options ratios, credit spread variations, and market breadth.
Who It's For
For Independent quantitative developers and retail algorithmic traders building automated risk models.
Feature List
✓ Historical time-series endpoints for specific sentiment indicators ✓ Pre-calculated moving averages and statistical z-scores ✓ Python SDK for direct integration into pandas dataframes
Where to Validate
Share your landing page in r/r/algotrading — that's exactly where these pain points were discovered.
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