Chapter 6 · What makes a complete trade
What should you settle before placing an order?
- Skills to practice
- Understand marketsControl losses
- 3D simulation
- None
Market scene
Lin and Zhe are colleagues with $50,000 each. On the same morning, both are bullish on BTC and buy at 60,000.
Lin buys 0.5 BTC as soon as he sees the news.
Before buying, Zhe spends ten minutes writing a card:
- Why buy: this news should bring about two weeks of sustained buying.
- What would prove me wrong: a break below 58,500, where this rally began.
- Maximum loss: 1% of the account, or $500.
- Therefore buy 0.333 BTC: a decline to 58,500 loses $1,500 per coin, totaling $500.
- Target: 63,000.
- Hold no longer than two weeks. Exit at 58,500, at 63,000, or when two weeks have passed.
Over the next two weeks, BTC first reaches 62,400, then declines to 57,000.
At 62,400, Lin has a $1,200 profit and thinks, “It will rise more.” During the decline he thinks, “It will come back.” At 57,000 he cannot stand it and sells everything, losing $1,500, or 3% of his account.
Zhe's target of 63,000 is never reached. When price reaches 58,500, he follows the card and sells, losing $500, or 1%. On the back he writes, “The news was overestimated; next time first check how many people already bought,” then goes on with his day.
Both get direction wrong and lose money. Why is Zhe's a complete trade, while Lin's is merely a bet?
Your decision
You are also bullish on BTC that morning, with $50,000. What do you do?
Observe the result
- This one outcome is similar across choices: a loss or no gain. Looking only at this trade makes the card appear unhelpful.
- The real difference is who decides the loss. Lin's loss depends on when he can no longer bear it. Zhe decides on $500 before ordering.
- The card makes trades comparable. Zhe knows the risk, desired reward, and minimum success probability. A review compares his judgment at the time, rather than his mood.
One trade's result may be luck. A trading process reveals skill over a hundred repetitions.
The mechanism
Each line of Zhe's card follows from the previous one:
- Why buy
- What would prove me wrong
- The corresponding price
- Maximum loss
- Quantity to buy
- Target price
- Reward relative to risk
- Success probability needed
Insert his numbers:
| Step | Zhe's card |
|---|---|
| Loss per BTC from entry to invalidation | 60,000 − 58,500 = 1,500 |
| Maximum loss | 50,000 × 1% = 500 |
| Quantity | 500 ÷ 1,500 = 0.333 BTC, worth $20,000, or 40% of the account |
| Gain at target | 0.333 × 3,000 = 1,000 |
| Reward/risk | 1,000 ÷ 500 = 2 |
| Minimum break-even probability | 1 ÷ (1 + 2) = one-third |
| At his estimated 45% | Average per trade: 0.45 × 1,000 − 0.55 × 500 = $175 |
Notice where size comes from: maximum acceptable loss divided by loss per coin at invalidation, rather than how bullish you feel. Greater confidence encourages larger size, often precisely when you are overestimating yourself.
The order matters too: write invalidation before entering. Once losing, people naturally find reasons to wait. That is what Lin experiences between 62,400 and 57,000.
What it is called
Zhe's card is a Trade Card, the Phase 1 artifact. It has eight parts:
What you expect and why. It must be specific enough to refute: “it will rise” is insufficient; “this news will bring two weeks of buying” is a thesis.
The price and conditions under which you buy or sell.
What makes you admit the thesis is wrong. Usually associated with a price, it is fundamentally a fact: here, a break below the rally's starting point.
How much to buy. Professional sizing works backward from maximum loss and entry-to-invalidation distance, rather than confidence.
Where you expect price to go and why. Target and invalidation together determine reward/risk.
How long you allow the thesis to work. If nothing happens by then, the thesis itself deserves doubt.
The loss in the trade's worst case, and its account percentage. Chapters 11 and 12 explain why this is usually only one or two percent.
When to leave regardless of whether you were right: invalidation, target, time expiry, or a change in facts supporting the thesis.
Real markets
Commodity trader Richard Dennis and his partner bet on whether trading could be taught. They recruited inexperienced people and spent two weeks teaching complete rules: entry, exit, and volatility-based sizing. These “Turtle Traders” included many who produced strong results in subsequent years.
They learned a full set of advance decisions, rather than a secret tip.
Nick Leeson accumulated large bullish Nikkei futures positions. After losses, he added rather than admitting error and hid losses in a concealed account. Following a major earthquake, Japanese equities fell; losses reached about £827 million, bringing down a bank over two hundred years old.
A trade without invalidation can continue until somebody else is forced to admit the error for you.
Many professional teams require reasons, invalidation, and position limits before an order, then review those records alongside results.
This compares what was thought at the time with outcomes, rather than later explanations. Chapter 35 develops the full trading journal.
Hands-on
The default card uses Zhe's numbers. Replace them with your own: choose BTC or ETH and your actual view. You do not need to place an order.
Course versionV1-docs; sourcelab:trade-card；Chapter 6 / TRD-MKT-006
Records parameters and results at the click only; does not mean the experiment passed.View snapshot to save
- Write thesis and invalidation before numbers. If you cannot specify invalidation, stop: the trade is not thought through.
- Inspect the break-even win rate. Do you believe your probability is that high? On what evidence?
- Move invalidation closer and observe size and reward/risk. Could ordinary price fluctuation hit it first?
- Copy the card as Markdown and save it. Return in two weeks: what happened, and which parts of your original judgment were right or wrong?
Change one variable
Size becomes 1.67 BTC, worth $100,000, or twice the account. Reward/risk becomes 10 and looks excellent.
Yet ordinary fluctuation near 60,000 can touch 59,700. The estimated 45% no longer applies; true success probability may be much lower. Invalidation belongs where the thesis fails, rather than where the loss looks small.
Reward/risk falls from 2 to 1. At the same 45% estimated probability, average loss is 0.1R, or $50, per trade.
The directional view is unchanged, but a worthwhile trade becomes an unprofitable one.
Size becomes 1.67 BTC, twice the account, with a maximum $2,500 loss.
At a 45% success probability, five consecutive losses have about a 5% probability. Five such losses reduce the account by 22.6%. Larger size makes an ordinary run of bad luck more likely to force you out; Chapter 12 examines this.
Three depths
- FoundationWhat should you settle before placing an order?Chapter 6
- AdvancedHow do you turn a Trade Card into a complete Strategy Object?Advanced B · Strategy research
- InstitutionalHow does a trade pass risk approval, execution, and attribution to enter a portfolio?Institutional
Write eight lines before ordering: thesis, entry, invalidation, size, target, horizon, risk, and exit. A line you cannot write identifies an unresolved decision.
Size comes from risk, not confidence: maximum loss ÷ loss per coin at invalidation = quantity.
From Trade Card to Strategy Object: a card describes one trade. Extract repeatable, backtestable rules from a class of cards to make a strategy. A Strategy Object also specifies data, signals, costs, out-of-sample performance, and capacity. See the strategy research system.
The research question: how far do estimated success probabilities differ from observed win rates? This begins calibration. See Advanced B · Strategy research.
Continue the artifact: Turn a Trade Card into a complete Strategy Object.
Entering a portfolio: an institutional card also goes through risk control: correlation with existing positions, risk-budget use, and single-asset exposure limits. Execution follows approval.
Attribution afterward: split PnL into direction, timing, execution, and fees, then compare against the card's expectations. Chapter 34 covers PnL attribution.
Continue the artifact: Connect approval, execution, risk, and attribution.
Questions to take away
Chapter self-test
He limits loss to $500, or 1% of the account. Moving from 60,000 to invalidation at 58,500 loses $1,500 per BTC. 500 ÷ 1,500 = 0.333 BTC.
Reward is twice risk, so the minimum probability is 1 ÷ (1 + 2) = one-third.
Zhe decides on a $500 loss before entry. Lin's $1,500 loss depends on when he cannot bear it anymore. Evaluate the entry decision, rather than just this one result.
A closer level is easier for normal fluctuation to hit, reducing the true probability of reaching the target. Place invalidation where the thesis is proved wrong.
One idea to take away
A complete trade starts with a thesis and ends with an exit. An order without invalidation and sizing plans is merely a bet.
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What should you settle before placing an order?
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