All lessons
Understand crypto before trading
1What is crypto trading? 2Blockchains, ledgers and consensus 3Bitcoin, Ethereum, coins and tokens 4Build a safe practice plan
Wallets and personal security
5Wallets, keys and custody 6Recovery phrases and backups 7Networks, addresses and transfers 8Phishing, approvals and scams
Understand the trading venue
9Centralized and decentralized venues 10Pairs, order books and spreads 11Spot orders and execution 12Fees, slippage and liquidity
Risk before returns
13Size a spot position 14Portfolio concentration and correlations 15Drawdown, R multiples and expectancy 16Stablecoins and counterparty risk
Read crypto market structure
17Candles and an around-the-clock market 18Trends, ranges and price levels 19Breakouts, volume and confirmation 20Indicators and volatility
Apply chart frameworks to crypto
21Dow-style structure: what would change your view? 22Wyckoff in spot crypto: read the range carefully 23Elliott counts: keep an alternative on the page 24Liquidity sweeps: separate the wick from the story 25FVG and OTE: transfer the rules, not the promises
Understand asset economics
26Supply, market cap and FDV 27Token unlocks and distribution 28Network activity and on-chain data 29Research a project critically
Understand derivatives before considering them
30Spot, futures and perpetual contracts 31Funding, basis and mark price 32Margin, leverage and liquidation 33Open interest and liquidation data
Derivatives through paper examples
34Linear perpetual P&L: calculate the money, not the excitement 35Collateral and liquidation: a deliberately simplified worksheet 36Funding carry: count what you keep 37Dated futures: follow both sides of the hedge 38Calls and puts: payoff is not profit
Explore DeFi with caution
39Smart contracts and applications 40AMM pools and price impact 41Liquidity provision and changing asset value 42Staking, lending and bridges
Understand ecosystem risks
43Constant-product AMMs: calculate the moving price 44LP divergence loss: choose the right comparison 45Reorgs, bridges and L2s: what is actually final? 46MEV and arbitrage: subtract the competition 47DEX approvals: inspect before you sign
Build and test market hypotheses
48Market context and catalysts 49Write a setup rulebook 50Profiles, order flow and SMC limits 51Backtest crypto data honestly
Research, allocation and review
52Token vesting: size the unlock, then ask why 53On-chain metrics: count activity, not stories 54Stablecoin depeg: map access, not just reserves 55Rebalancing: weights change even when you do nothing 56Advanced crypto capstone: defend the whole plan
Practice, review and stay informed
57Paper trade and keep a journal 58FOMO and decision routines 59Records, local rules and changing information 60Capstone: research and risk plan
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Advanced crypto capstone: defend the whole plan

3 min read

Can your idea survive costs, failed assumptions and a decision not to trade?

Here is what we will figure out

Combine the course into a paper research and risk review with measurable limits.

Choose one fictional or historical case and freeze the information available at the decision time. Describe market structure and any Wyckoff, Elliott or ICT-style hypothesis as testable rules. Record an alternative interpretation rather than stacking labels as proof.

Add token supply, unlocks and on-chain evidence with sources and dates. For every conclusion, state a confounder. Identify custody, counterparty, contract and bridge dependencies even if the price setup looks attractive.

Specify paper entry conditions, invalidation, position risk, order assumptions, fees, funding and a maximum review drawdown. A missing signal, unreliable quote or unavailable withdrawal can be a no-trade condition. Do not change rules after seeing the outcome.

Evaluate the process separately from the single result. Keep rejected cases and failed tests. A short profitable sample does not establish an edge; a cost-sensitive losing sample deserves review before any real-money use. Completing lessons certifies neither skill nor profitability.

Let’s work through it

  1. Freeze evidence and define a falsifiable hypothesis.
  2. Build the complete risk and execution sheet.
  3. Run a paper test without hindsight changes.
  4. Review net outcomes, drawdown and reasons to stop.

Let’s use numbers · hypothetical example

Twelve fictional paper trades show gross gains of 36 but total costs of 48: net −12. Separately, a review equity curve peaks at 1,000 and falls to 850: drawdown is 150/1,000 = 15%. Returning from 850 to 1,000 requires 150/850 ≈ 17.65%, not 15%. These are distinct review measures.

Easy mistakes to watch for

  • Calling many chart labels independent confirmation.
  • Evaluating gross profits while ignoring total costs.
  • Treating course completion as readiness for leverage.

Keep in mind

Use this capstone as a simulation. It does not establish suitability for leverage or replace independent financial judgement.

Your turn

Produce one page with hypothesis, contrary evidence, source dates, hypothetical sizing, all costs, security checks and a clear proceed-or-skip rule. Have another reader challenge an assumption.

A quick check before we move on

What return recovers 850 back to 1,000?

  1. 15%
  2. Exactly 150%
  3. About 17.65%
Check answer

About 17.65% Recovery uses the reduced base: (1,000 − 850)/850 ≈ 0.1765, or 17.65%.

Sources and further reading

Content reviewed: 29 October 2026

All lessons

Educational material with hypothetical examples. Trading can cause substantial losses. A course, pattern, stop order or past result cannot guarantee a profit or limit every loss. Practise in simulation and check current rules and product terms in your jurisdiction.