Built by Traders,
for Traders
SmartFinanceData was born out of a simple frustration: the data needed to trade with a real statistical edge wasn't freely available — or even organised in a useful way. We built it ourselves.
Why We Exist
Most retail traders operate on intuition, social media tips, or surface-level chart reading. They're missing the one thing professional desks have always had: historical probability data.
SmartFinanceData exists to close that gap. We collect, clean, and structure decades of OHLC data across Forex, Indices, Commodities, and Crypto — then run it through a rigorous statistical framework to surface patterns that genuinely repeat.
Whether you're building a rule-based system, validating a discretionary thesis, or simply trying to understand when a market is trending vs ranging — our datasets give you a quantified, reproducible foundation to work from.
What We Stand For
Every dataset starts with the raw numbers. No narratives, no opinions — just what the price history actually shows, quantified.
We test every pattern for statistical significance before publishing. If the edge doesn't hold up under scrutiny, it doesn't appear on the platform.
Institutional-grade probability data shouldn't require a Bloomberg terminal. Core datasets are free. Advanced analytics are affordable.
We explain the "why" behind every dataset. Understanding the statistical logic means you can apply it correctly — not just copy numbers blindly.
What We Analyse
Coverage spans the major tradeable markets, with priority on the pairs and instruments retail traders actually use.
How It Started
SmartFinanceData grew out of a personal project: building Excel workbooks to test whether common forex setups — wicks, Asian compression, outside days, monthly sweeps — actually had a statistical edge or just looked good on a chart.
The answer was nuanced. Some patterns had real, measurable edge. Others didn't hold up under rigorous testing. The process of finding out was where the value lay — and that process deserved to be shared.
This platform is the evolved, structured version of those workbooks: cleaner, broader, updated daily, and accessible to any trader who wants to trade with a genuine probabilistic foundation.
Manual backtesting across 20+ forex pairs using Python and openpyxl. First discovery: wick signals and Asian session compression had measurable, repeatable edges.
Published a series of statistical Excel workbooks covering streak probability, London trend days, monthly sweep probability, and outside day ranges — all formula-driven with advanced stats.
SmartFinanceData goes live — bringing together all datasets, interactive analytics pages, and educational content under one platform with daily data refreshes.
Stocks and bonds coverage, expanded crypto analytics, MT4/MT5 integration, custom alert systems, and a community space for data-driven traders.
The Person Behind the Platform
Liam has been trading forex since 2012, spending over a decade developing a price action methodology centred on supply and demand zones. His trading journey eventually led to a fundamental question most traders never get around to asking: do these patterns actually hold up statistically, or do they just look convincing on a chart?
The answer required building an entire data infrastructure from the ground up — collecting decades of OHLC data, running rigorous statistical tests, and validating which edges genuinely repeat. SmartFinanceData is the public-facing result of that research: a platform that makes institutional-grade probability data accessible to any serious retail trader.
Outside of data, Liam runs PriceActionNinja, a forex trading education platform teaching supply and demand methodology alongside the statistical reasoning needed to apply it with confidence.
"Most retail traders are making decisions based on patterns they've never actually tested. SmartFinanceData exists so that excuse disappears."