US Markets Trading Lab

Course outline and operating guide

30 lessons · 6 teaching weeks · US stocks and unleveraged ETFs · Paper-first
Version 1.0 · Prepared September 11, 2026 · Singapore study context

Build a repeatable decision process, test it honestly, and learn when not to trade. This independently authored curriculum uses the broad public themes of The Trading Channel outline; it is not affiliated with that provider and does not reconstruct paid material or adopt its marketing claims.

Start here

Begin Lesson 01 — Trading, investing, and your learning contract

Lesson 01 is ready to study; no learner answers or grades have been recorded. The recommended sequence is one lesson at a time: read, attempt the example independently, submit practice and the knowledge check, then review feedback. Do not confuse opening a page with demonstrating competence.

Scope and prerequisites

You need basic arithmetic, a way to write notes, and later access to lawful historical OHLCV data and a paper environment. Paid software, broker deposits and real orders are not prerequisites. Technical comfort helps with the optional Python lab; coding is not required for Lessons 1–26.

The core practice is long-only ordinary US stocks and unleveraged, non-inverse ETFs. Swing trades receive the most attention, with a separate weekly position-trading research track. Day trading, shorting and other markets are awareness topics, not practical trading assignments. Long-term investing has its own policy rather than serving as an excuse to retain a failed trade.

What you will learn

Read quotes and charts; distinguish an order from a fill; calculate position size and realized R; define reproducible market observations; evaluate two swing setups and one position setup; analyze portfolio exposure and gap risk; design a falsifiable backtest; maintain a journal; interpret uncertainty; and write an independent operating playbook.

By the end you should be able to reject a weak trading idea with evidence. No return, income, win rate or transition to live trading is promised.

Schedule

Plan five 60–90 minute study sessions per teaching week. This is a suggested workload, not a completion deadline. Historical research, 30–50 forward paper fills, or months-long position observations can extend beyond six weeks. Do not force trades to meet a classroom count. Record the actual evidence available and leave unobserved work pending.

Week	Focus	Evidence of learning
1	Foundations and risk literacy	Learning charter; market/data contract; three sizing and execution scenarios.
2	Price action and reproducible observations	Ten blind analyses, including six provided synthetic cases; uncertainty labels.
3	Two swing strategies and the research pilot	A twenty-case pilot target across A/B, with actual observed counts and limitations reported.
4	Portfolio risk, metrics and behavior	Portfolio stress test; metrics report; incident review and weekly review.
5	Position trading, investing and Singapore operations	Weekly trail table; company note; investment policy; account verification checklist.
6	Validation and independent operation	Research registration; calculator tests; forward protocol; scored capstone.

Complete lesson map

Week 1 — Foundations and risk literacy

Understand the instrument, session, data, orders and risk arithmetic before chart-based setups.

01 — Trading, investing, and your learning contract
02 — US market mechanics from Singapore
03 — Candles, returns, and honest chart data
04 — Orders, fills, stops, and execution failures
05 — Risk units, position sizing, and expectancy

Week 2 — Price action and reproducible observations

Describe charts using timestamped, explicit rules rather than stories about inevitable price moves.

06 — Market structure without hindsight
07 — Support, resistance, trendlines, and invalidation
08 — Moving averages, ATR, volume, and relative strength
09 — Market regimes, benchmarks, and event context
10 — Blind chart-reading laboratory

Week 3 — Two swing strategies and the research pilot

Evaluate pullback A and breakout B using complete entry/exit and rejection rules.

11 — Build a stock-screening pipeline
12 — Strategy A: daily trend pullback v1.0
13 — Strategy B: daily breakout continuation v1.0
14 — Manage trades without changing the experiment
15 — Swing-trading research practicum

Week 4 — Portfolio risk, metrics and behavior

Measure account exposure, losses, costs, uncertainty and decision quality.

16 — Portfolio exposure and correlated losses
17 — Earnings, news, gaps, and trading halts
18 — Performance metrics that do not hide losses
19 — Losing streaks, uncertainty, and drawdown controls
20 — Journaling, psychology, and the weekly review

Week 5 — Position trading, investing and Singapore operations

Study weekly strategy C, business context and a distinct investment policy; understand FX and intraday scope.

21 — Strategy C: weekly position-trend research v1.0
22 — Business quality, valuation, and catalysts
23 — Long-term investing is a separate system
24 — Singapore investor operations: FX, tax questions, and records
25 — Day trading and other markets: awareness without scope creep

Week 6 — Validation and independent operation

Register an unbiased experiment, use audited tools and assemble a defensible playbook.

26 — Design a backtest that can fail honestly
27 — Python lab: inspect the math, do not automate risk
28 — Untouched validation and forward paper trading
29 — Your playbook and operating checklist
30 — Capstone: defend the evidence and choose the next step

Training account and controls

All exercises begin with US$10,000 simulated equity, not a statement about your finances. Keep emergency spending, housing money and long-term allocations outside the experiment. Risk tolerance and goal horizon matter to asset allocation. [S06, S08]

The teaching portfolio uses a maximum 0.5% planned total-loss budget per entry, including modeled friction; a 10% new-entry notional cap per name; total reserved open budgets no greater than 1.5% of equity; and no more than 1% in a common theme. It uses available cash without borrowing. These are illustrative controls, not validated optimal settings or personalized recommendations. Original budgets remain reserved until positions close. Changing equity can put a portfolio above a control; do not add new risk while over its limits.

A stop is not insurance. Gaps, halts, unavailable liquidity and execution problems can create losses larger than the plan. [S05] Always distinguish a maximum planned budget from a guaranteed maximum loss.

Three strategies, not three proven edges

A is a daily trend pullback; B is daily breakout continuation; C is a separate weekly trend-following experiment. Their entry, exit, event, ranking and fill rules are fixed in the strategy specifications. Thresholds are hypotheses to test, not factual claims about market behavior. No market-data backtest was run during this course's construction.

Assessment and progression

Each lesson has learning outcomes, teaching notes, a worked example, a practical task, three knowledge-check questions, a completion artifact and references. That gives 90 lesson questions. The six weekly checkpoints add 30 questions. The final capstone adds ten questions and a research dossier.

Attempt work before opening instructor keys. Weekly checkpoints are scored out of 20; target 16/20 with safety-critical errors corrected. The capstone is scored out of 100; target 80/100 with all safety-critical errors corrected. These are classroom rubrics, not credentials. A failed strategy can still produce an excellent research submission.

Report knowledge completion separately from research maturity. A hundred historical cases or 30–50 paper fills are useful learning milestones, not statistical proof. Positive sample results do not establish a reliable edge; paper execution does not fully reproduce live trading. [S11, S12] An acceptable final decision is to continue paper research, change the experiment after versioning it, reject a strategy, or choose not to trade actively.

Libraries and reusable tools

Reference library contains exact strategy specifications, a glossary, six blind synthetic cases and source notes. Worksheets cover the learning charter, trade plan/journal, weekly review, research registration, investment policy, broker checks and incident control. Assessments contains weekly keys, blind-case outcomes and capstone materials.

The local workspace includes a Python position-size calculator, a synthetic journal analyzer, an educational bootstrap tool and automated tests. They do not submit orders or connect to a broker. The offline reader keeps optional completion ticks only in the current browser; it does not submit answers, award grades or synchronize with Lark.

Publication and workspace status

The canonical local text lives in Markdown files. This bundle was created in the chat session's filesystem; it is not a fork of the conversation into a desktop Codex project, and it has not been written to your Mac. Extract the ZIP to use it as your own local workspace.

The intended Lark root is the page supplied by the learner. Live publication was blocked by the absence of an authenticated Lark connector/CLI. No remote page was read, overwritten, shared or created. The publishing manifest maps the existing root, six weekly sections, thirty lesson subdocuments, and reference/worksheet/assessment libraries. The included local publishing helper defaults to a no-network preview; its live Lark integration has not been tested in this session.

Source and evidence policy

S01: public topic outline · S05: SEC stop orders · S06: FINRA risk disclosure · S08: SEC allocation · S11: paper simulation limitations · S12: backtest-overfitting research record.

See the complete source register for dates, boundaries and methods. Current broker rules, taxes, sessions and product features must be rechecked before action. Every numeric trading scenario in this course is synthetic unless the learner later supplies properly labeled observed data.