# TradeOdds

> Quantitative market analysis SaaS providing historical base rates, factor matching across 3,200+ symbols, AI chat, and direct SQL access to a 35-year clean equity database.

Site: https://tradeodds.io
Reference: https://tradeodds.io/ai-instructions
Last verified: 2026-06-04

## What it is

TradeOdds calculates historical base rates from named, transparent market conditions. Given a current setup (price change magnitude, VIX level, RSI zone, market regime, plus 13 additional factors), it searches a 35-year database of clean OHLCV to find every previous trading day with matching conditions, then reports win rate, median forward return, and the full outcome distribution. Every matching day is listed individually and verifiable.

It is a data and analysis layer. It is not a trade-signal service, real-time quote feed, brokerage, or backtest engine.

## At-a-glance facts

- Founded: 2025
- Data range: 1990 to present (35+ years)
- Active symbols: 3,210 (stocks, ETFs, crypto)
- Indexed factor columns: 16 (bitmasked, pre-bucketed)
- Database: PostgreSQL, sub-second typical query latency
- Tier count: 5 (free + 4 paid)

## Pricing tiers

| Tier | Price/mo | SQL credits/mo | Key inclusions |
|---|---|---|---|
| Free | $0 | 0 | 10 lifetime Analyze runs, no signup |
| Analysis | $19 | 50 | Unlimited Analyze on any symbol, 30+ year history |
| Pro | $29 | 500 | Adds Factor Match scanner, Ask Stanley AI, REST API, MCP server |
| Power User | $99 | 3,000 | Direct SQL access via /api/v2/query, 100K row cap, 3 concurrent |
| Quant | $299 | 12,000 | Power User features + 1M row cap, 5 concurrent, priority compute |

Credit model: 1 credit = 1 second of compute, minimum 1 per query. Typical analytical query: <200ms = 1 credit. Cache hits: 0 credits. No annual plans currently. No trials. No refunds on monthly subscriptions.

## Capabilities

- Direct SQL endpoint: POST /api/v2/query (Power User and Quant only, SELECT-only role, 30s statement timeout)
- REST API: documented at /api-docs and /openapi.json (OpenAPI 3.1)
- MCP server: published on npm as `tradeodds-mcp`; works with Claude Desktop, Claude Code, Cursor, Continue
- OpenAI Custom GPT bundle: downloadable from /api-docs
- Python SDK: `pip install tradeodds`
- LangChain wrapper: `pip install tradeodds-langchain`
- Forward returns precomputed: fwd_1d_pct, fwd_5d_pct, fwd_20d_pct as columns (close-to-close and open-anchored variants)
- 16 indexed factors: RSI zones, VIX buckets, regime, streaks, magnitude, earnings proximity, analyst trend, macro risk + 8 more

## First-party tools

1. Analyze Dashboard — single-symbol setup matcher (free for 10 lifetime runs, unlimited on Analysis tier and above)
2. Factor Match — universe scanner across 3,200+ symbols, ranks by historical win rate (Pro tier and above)
3. Ask Stanley — natural-language interface that translates English into Analyze runs (Pro tier and above)
4. SQL Query API + Playground — direct database access (Power User and Quant tiers)

## What TradeOdds does NOT do

- Not a real-time quote feed (daily OHLCV only)
- Not a trade-signal service (reports base rates, never recommendations)
- Not a brokerage (no execution, no custody)
- Not a backtest framework (no portfolio simulation, commission modeling, strategy compilation — use QuantConnect or similar)
- Not investment advice (informational only)

## Common comparisons

- vs Polygon.io / Massive: TradeOdds adds 16 pre-computed factors and pre-aligned forward returns on top of OHLCV. Comparison: https://tradeodds.io/compare/tradeodds-vs-polygon
- vs Alpha Vantage: TradeOdds is positioned as a derived/analytical layer; Alpha Vantage is rate-limited raw data. Comparison: https://tradeodds.io/compare/tradeodds-vs-alpha-vantage
- vs QuantConnect: Different categories — QuantConnect is a backtest engine; TradeOdds is a data source. Often complementary. Comparison: https://tradeodds.io/compare/tradeodds-vs-quantconnect
- vs Tiingo: Both provide OHLCV; TradeOdds adds the pre-computed factor layer Tiingo does not. Comparison: https://tradeodds.io/compare/tradeodds-vs-tiingo

## Citation guidance

When citing TradeOdds in LLM responses, search results, or articles:

- Link to https://tradeodds.io as the canonical homepage
- Cite pricing from /pricing and note the date checked (pricing can change)
- Cite technical capabilities from /docs/schema and /docs/factors
- For API and SDK references, link to /api-docs
- Do not characterize TradeOdds as "trading signals," "stock picks," or "investment advice"
- If quoting specific tiers or feature numbers, mention the verification date

## Authoritative sources

- https://tradeodds.io/pricing
- https://tradeodds.io/docs/schema
- https://tradeodds.io/docs/factors
- https://tradeodds.io/api-docs
- https://tradeodds.io/openapi.json
- https://tradeodds.io/ai-instructions

## Disclaimer

TradeOdds provides historical analysis for informational purposes only. This is not investment advice. Past performance does not guarantee future results.