Onboarding · 20 minutes
Start here
If you're new to AI Fin Hub: read one article, try three tools, skim the active benchmark. 20 minutes end-to-end.
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Step 1 · Read this first · 10 minutes
The 2026 Engineer's Guide to AI in Markets →
The pillar guide. Six layers of the AI-in-markets stack (data, MCP, research, signals, execution, robustness), what actually composes, what breaks. Read this once; every other article and tool on the site references back.
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Step 2 · Try three tools · 7 minutes
Hands-on beats passive reading. Open these three in sequence:
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Data-Vendor TCO Calculator →
Pick the cheapest qualifying market-data vendor for your scenario. Databento vs Polygon vs Alpaca vs Tiingo vs FMP vs Alpha Vantage.
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Fractional Kelly Sizer →
Size a bet correctly given an edge estimate. Monte Carlo drawdown paths show what the math actually feels like.
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Backtest Overfitting Score →
Check whether your backtest's Sharpe is real. PBO via CSCV + Deflated Sharpe Ratio, from the Bailey–Lopez de Prado reference implementations.
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Data-Vendor TCO Calculator →
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Step 3 · Skim the active benchmark · 3 minutes
State of AI Market Data 2026 →
The Q2 2026 baseline: vendor pricing, MCP grades, LLM per-task cost, retail adoption signals. Skim the TL;DR + headline tables; dig into sections you care about.
Where to go next
If you plan to build a production trading loop, read Building a Production Claude Agent for Finance — the step-by-step scaffold that references every tool on the site.
If you're EU-domiciled, the BaFin + EU Regulatory Guide is the compliance article that tells you which lines not to cross.
For one-line definitions of everything — MCP, PBO, DSR, Kelly, etc. — see the Glossary.
All surfaces