▸ orientation & learning paths

Start here. Tell us where you’re going, and we’ll show you the route.

To learn HFT and quant trading well, climb the money ladder: start with market microstructure (the order book), then the data, then a strategy family (most usefully market making), and end at how it makes money in your venue and what you’d need to run it. This page hands you that route, by goal.

Money-ladder path explorerpick your routeIX-PATH
Pick a market, where you're starting from, and what you want to reach. The atlas assembles a route from a microstructure foundation up to a strategy that makes money, and the tool you'd need to run it.
Market
Starting point
Goal rung
Your route: Microprice → market making → crypto. Every path bottoms out at the order book and tops out at how it makes money.
1
The microprice

a fair-value estimate from book imbalance – the input a smarter quote is built on

2
Order-flow information

quoting around that fair value using flow – one information-based flavour of

3
Market making

earn the spread, manage inventory, survive adverse selection – the same maths carried onto

4
Crypto market making

open venues, gettable data, no prime broker – to actually run it you need

⤓
Datasets & tools

clean L2/L3 data, an MM harness, a microprice/A–S reference impl

What to notice. Change the market and the maths stays the same; only the venue at the apply rung swaps. Change the goal and the middle rungs swap, but the foundation (the order book) and the destination (how it makes money) never move. The ladder is the insight.

Curated reading paths

Pick the one that’s you.

Self-taught quant: zero → market making

For a strong engineer who can backtest but isn’t sure which ideas hold or how they connect. The flagship path.
  1. The limit order book – the object everything refers to; trade against it
  2. Price-time priority & queue value – why queue position is an asset
  3. Bid-ask bounce – why raw data lies to your backtest
  4. Market making – earn the spread, manage inventory, survive adverse selection
  5. Avellaneda–Stoikov – the inventory model; blow it up
  6. The microprice – a better fair value from book imbalance
  7. Backtesting & simulation – how to not lie to yourself
  8. Crypto market making – the open venue to actually start on
  9. Datasets & tools – the data and tools to run it

Crypto / Polymarket engineer: fundamentals onto your venue

For someone already shipping bots against an order-driven venue, reinventing microstructure badly.
  1. Quote-driven vs order-driven markets – where your venue sits
  2. The limit order book – the mechanics behind your WebSocket feed
  3. Adverse selection – the risk you’re already half-feeling
  4. Order-flow imbalance – the signal you’re already half-feeling
  5. Inventory management – the discipline your bot is missing
  6. Prediction markets (Polymarket) – the same maths, your venues
  7. Datasets & tools – clean L2/L3 data for crypto and Polymarket

Isolated bank quant going independent

For a credentialed quant walled off on one slice of a desk, who wants the end-to-end commercial picture.
  1. The economics of HFT – how the P&L is actually made
  2. Market participants – the taxonomy of who’s in the flow
  3. Market making – running a book, not just a calibration routine
  4. Capacity & alpha decay – what a small book can realistically hold
  5. Going independent in 2026 – the AI + solo-shop thesis, honestly
  6. Crypto market making – venues a one-person shop can reach
  7. Datasets & tools – the infrastructure that replaces a desk’s data team

Mathematician: the models, in market context

For someone whose maths is not the obstacle. The market context is.
  1. Market making – the problem statement the models solve
  2. Avellaneda–Stoikov – the stochastic-control formulation
  3. The microprice – a clean estimation problem from book imbalance
  4. Almgren–Chriss optimal execution – the impact-vs-risk frontier you know how to optimise
  5. PIN / VPIN – the estimation / inference side
  6. Irregular time & point processes – ACD point processes – maths you’ll recognise
  7. Datasets & tools – reference implementations

None of these is linear required reading; they’re suggested orders. Every page links to what comes before and after it, so you can wander off a path at any point and find your way back from the map.

How the site works

So you can read everything else.

Topics → hubs → concepts

The field is cut into ten topics, each a hub that links down to its concept pages, plus two cross-cutting layers: Markets and the 2026 lens.

“Where this fits”

Every concept ends with four link classes: ↑ Up (building block of), ↔ Across (composes with), → Apply (makes money in), ⤓ Build/Buy (the tool you’d need). Follow ↑ and you climb the ladder.

The interactives

Wherever a concept can be shown moving, there’s a live widget, 28 of them. Reading tells you what a thing is; moving it tells you why it matters.

The 2026 verdict badges

Every technique carries an honest, dated verdict: ∞structural ◆still alpha ≈commoditised †dead . That’s our current read, argued and sourced on the page.

Qualify the audience early

What this is not.

Not get-rich-quick.

No indicator that prints, no signal-selling, no black box with a P&L promise. We sell understanding and (later) infrastructure.

Not a literature review.

Rigorous and sourced, but the lens is applied: what works, where, and what it costs to run.

Not for people who won’t do the work.

The content front-loads real maths and engineering. If that’s not what you want, this isn’t the site, and that’s fine.

Common questions

Do I need a PhD to do quant or high-frequency trading?
No. You need strong probability, statistics and programming, and real microstructure understanding; a PhD signals those but is not the gate, especially for independent crypto and prediction-market work. Sell-side HFT desks often prefer them; an open venue does not check credentials. This site front-loads the maths so the prerequisite is competence, not a certificate.

Where this fits

↑ Up · building block of HFT Book ↔ Across · composes with The concept map ↔ Across · composes with Glossary ↔ Across · composes with About & methodology → Apply · makes money in Markets → Apply · makes money in Crypto market making ⤓ Build / Buy · tool needed Datasets & tools