Overview
From first principles of trading to strategy research, quant methods, portfolio management, and institutional execution. A training system for professional trading.
Trader OS is not a conventional trading course.
It does not aim to train people who merely use indicators or predict whether prices will rise or fall. It trains Professional Decision Makers and Professional Capital Allocators: people who make decisions under uncertainty, allocate risk, test their beliefs, and survive long enough for compounding to work.
How you will see markets after the course
An ordinary trader sees prices. An institutional trader sees the whole system: how information becomes expectations, expectations become positions, positions consume liquidity, and prices feed back into risk and capital flows.
Where to start: choose a learning path
The same curriculum offers four ways to read it, depending on your starting point. These are four routes through one body of content, each with a recommended reading mode:
- Starting from zero: begin with Chapter 1 and read in order.
- Already trading: take the self-test at the end of each phase introduction, then continue from Phase 3.
- Want the whole picture first: read How to use this course and Knowledge nodes.
The complete loop to master
- Observe
- Hypothesis
- Mechanism
- Data
- Signal
- Research
- Backtest
- Falsification
- Strategy
- Portfolio
- Risk
- Execution
- Attribution
- Review
- Iteration
Ultimately, the course teaches this loop rather than a particular indicator. Every chapter practices one part of it.
Foundation: six phases, 36 chapters
Build the right market model: where prices come from and the parts of a complete trade.
Deliverable: Trade Card · 6 / 6 chapters available
Decide with probabilities rather than opinions. Learn survival before profits.
Deliverable: Risk Calculator · 6 / 6 chapters available
Understand orders becoming fills, slippage, and prices, and leverage turning declines into chain reactions.
Deliverable: Crypto Market Structure Report · 6 / 6 chapters available
Turn an idea into a refutable strategy hypothesis with a mechanism and signal.
Deliverable: 3 Strategy Hypotheses · 6 / 6 chapters available
Test strategies with historical data while understanding how backtests mislead.
Deliverable: First complete Backtest Report · 6 / 6 chapters available
Turn individual trades into a durable system: risk, portfolio, execution, attribution, and reviews.
Deliverable: Foundation capstone · 6 / 6 chapters available
All 36 Foundation chapters and their accompanying experiments are available. The complete chapter list follows:
| chapters | Title | Core question | Knowledge node |
|---|---|---|---|
| 1 | Why markets exist | Why would someone sell you their BTC? | TRD-MKT-001 |
| 2 | Why prices change | Why does the same BTC have a different price a minute later? | TRD-MKT-002 |
| 3 | What a candlestick really is | What information does a candle retain, and what does it discard? | TRD-MKT-003 |
| 4 | Why trends form | Why does a price rise often continue for a while? | TRD-MKT-004 |
| 5 | What support and resistance really are | Why does price often stop at the same level? | TRD-MKT-005 |
| 6 | What makes a complete trade | What should you settle before placing an order? | TRD-MKT-006 |
| 7 | Probabilistic thinking | What differs between saying BTC will rise and saying it has a 60% chance of rising? | TRD-PROB-001 |
| 8 | Expected Value | Is a trade with only a 40% chance of winning worthwhile? | TRD-PROB-002 |
| 9 | Win rate and reward/risk | Why can a strategy with a 90% win rate keep losing money? | TRD-PROB-003 |
| 10 | Variance and Drawdown | Why can a positive-expectancy strategy lose several times consecutively? | TRD-PROB-004 |
| 11 | Position Sizing | What size suits the same trading idea? | TRD-PROB-005 |
| 12 | Risk of Ruin | Why can a positive-expectancy strategy still cause ruin? | TRD-PROB-006 |
| 13 | Order Book | What happens in the book when you click market buy? | TRD-MICRO-001 |
| 14 | Liquidity | Why does a $1 million purchase barely move one coin but move another by several percent? | TRD-MICRO-002 |
| 15 | Market Maker | Why is quoting both sides and earning the spread harder than it looks? | TRD-MICRO-003 |
| 16 | Crypto Market Structure | Why do exchanges, on-chain AMMs, and aggregators quote and execute the same coin differently? | TRD-MICRO-004 |
| 17 | Crypto Derivatives | Spot, dated futures, and perpetuals all say buy BTC. What differs? | TRD-MICRO-005 |
| 18 | Liquidation Feedback | Why can a decline accelerate beyond anyone's expectations? | TRD-MICRO-006 |
| 19 | Where strategies originate | Whose money funds a sustainably profitable strategy? | TRD-STRAT-001 |
| 20 | Hypothesis | What is wrong with trading whenever an indicator signals? | TRD-STRAT-002 |
| 21 | Mechanism | What economic mechanism makes a strategy profitable? | TRD-STRAT-003 |
| 22 | Signal | How can a computer evaluate a feeling such as the market is too hot? | TRD-STRAT-004 |
| 23 | Market Regime | Why does the same strategy profit last year and keep losing this year? | TRD-STRAT-005 |
| 24 | Falsification | What would show that your strategy is wrong? | TRD-STRAT-006 |
| 25 | What a Backtest is | Can historical simulation prove future profitability? | TRD-BT-001 |
| 26 | Data Bias | Why do perfect backtest curves often disappear in live trading? | TRD-BT-002 |
| 27 | In-sample / Out-of-sample | Why is tuning parameters to a perfect backtest bad news? | TRD-BT-003 |
| 28 | Transaction Cost | What remains after costs from a strategy backtesting at 50% annualized? | TRD-BT-004 |
| 29 | Robustness | What does losing profitability after a small parameter change imply? | TRD-BT-005 |
| 30 | Paper Trading | Why can you not invest real money immediately after a passing backtest? | TRD-BT-006 |
| 31 | Risk Management | Why do professionals inspect risk before opportunities each morning? | TRD-PRO-001 |
| 32 | Portfolio | Does holding BTC, ETH, and SOL diversify risk? | TRD-PRO-002 |
| 33 | Execution | Why do two traders earn different returns from the same signal? | TRD-PRO-003 |
| 34 | PnL Attribution | If you profited this month, do you know why? | TRD-PRO-004 |
| 35 | Trading Journal | Is a profitable trade necessarily a good decision? | TRD-PRO-005 |
| 36 | Professional Trading System | What is still missing between an idea and a durable trading system? | TRD-PRO-006 |
Three depths, one knowledge core
Trader OS has Foundation, Advanced, and 3D teaching formats, but they are not three independent courses. They share the same knowledge graph, chapter numbering, and learning progress. What changes is the depth of content and mathematics, the interaction, and the complexity of the market.
Each concept has just one Canonical Knowledge Node. For example, the order book is TRD-MICRO-001. In Foundation it is Chapter 13; in Advanced it is a research question in execution and microstructure; in 3D it is a simulation where you can place orders in a trading hall. See Knowledge nodes.
Every chapter has the same structure
- Market scene
- Your decision
- Observe the result
- The mechanism
- What it is called
- Real markets
- Hands-on
- Change one variable
See the phenomenon first, understand the mechanism next, and learn the terminology last. After the eight steps come three depths of the same node, questions to take away, and a chapter self-test.
Versions
| Version | Format | Status |
|---|---|---|
| V1 documentation edition | The site you are reading: 36 Foundation chapters, six Advanced domains, eight tracks, and full specifications for strategy research, the risk engine, trading journals, and AI | Current version |
| V2 3D edition | Enter a trading hall in your browser: six rooms and ten simulations, each attached to a knowledge node | Prototype |
Both editions read the same curriculum data. See Version roadmap.
What this course does not do
- It gives no investment advice and recommends no token or exchange. It teaches mechanisms and methods, not what to buy.
- It promises no returns. Whenever profit figures appear, they train you to ask where the money comes from and who bears the risk.
- Labs never use real money. Exercises use calculations, public data, paper trading, or this site's simulators.