# Documentation

> Turn a plain English trading idea into a rigorously backtested strategy.

Source: https://docs.texttoquant.com

---

TextToQuant turns a sentence into a backtested trading strategy. You describe an idea in plain
English, and the platform parses it into a precise, deterministic strategy specification, runs it
bar by bar against real market data, and hands you an honest report: performance, risk, and an
overfitting verdict.

These docs are organised by intent: **learn** the ideas, follow a **guide** to get a job done, or
consult the **reference** for exact behaviour.

## How it works

<Steps>
  <Step n={1} title="Describe">
    Write your idea the way you'd say it out loud: asset, signal, exits, timeframe.
  </Step>
  <Step n={2} title="Parse">
    The query compiles deterministically into a fixed strategy spec. The AI never scores the result,
    so it can't steer toward a good looking number.
  </Step>
  <Step n={3} title="Backtest">
    A bar by bar engine simulates the strategy on real data, using only closed bar information (no
    look ahead).
  </Step>
  <Step n={4} title="Read the report">
    Metrics, chart, trade ledger, robustness checks and a letter grade, with everything you need to
    trust or reject the result.
  </Step>
</Steps>

<RunInTerminal query="Buy BTC when RSI(14) crosses above 30, exit at 3R or 2% stop, on the 4h" />

## Start here

<CardGrid>
  <Card href="/docs/reference/metrics" title="Metrics" eyebrow="Reference">
    Every performance metric, what it means, and how to read it honestly.
  </Card>
  <Card href="/academy" title="Academy" eyebrow="Tutorials">
    Guided, hands on lessons across Foundations, Validation and Risk.
  </Card>
</CardGrid>

## What makes it different

- **Deterministic by construction.** Same query ⇒ same spec fingerprint ⇒ same test. Results are
  reproducible, and the header shows a Reproducible chip to prove it.
- **Overfitting aware.** Beyond Sharpe and win rate, the report ships probabilistic and deflated
  statistics that correct for how many configurations you tried.
- **No look ahead.** Signals read only closed bar data, so a backtest can't cheat with information
  it wouldn't have had live.

<Callout variant="tip" title="New here?">
  Read the [Metrics reference](/docs/reference/metrics) next: understanding what the numbers
  mean is the fastest way to get value from every backtest you run.
</Callout>