Risk management

Most traders spend their time looking for better entries. Almost all of the difference between surviving and not comes from the other side of the trade: how much you lose when you are wrong, and how often you allow it.

The arithmetic of drawdown

Losses and gains are not symmetric, and the asymmetry gets brutal quickly:

A 50% loss requires a 100% gain simply to return to where you started. This is why capital preservation is not timidity — it is arithmetic. The trader who never loses more than 20% has a recoverable situation; the one who loses 75% almost certainly does not.

The 1% rule

Risk no more than 1% of account equity on any single trade. On a £10,000 account, that is £100 — the maximum you lose if the stop is hit.

This is not about the position's size. A £100 risk can be a £2,000 position with a 5% stop or a £10,000 position with a 1% stop. What stays constant is the loss.

The reason 1% works is streak survival. Losing streaks are longer than intuition suggests — a strategy winning 45% of the time will produce a run of eight consecutive losses reasonably often over a few hundred trades. At 1% risk, eight losses costs about 8%: unpleasant, entirely survivable. At 10% risk, the same ordinary streak costs 57% and effectively ends you.

Position sizing, mechanically

1. 1
   Decide the risk amount

   Account balance × risk percentage. £10,000 × 1% = £100.

2. 2
   Find the stop distance

   The gap between entry and the price that proves you wrong. Entry £50, stop £47 = £3.

3. 3
   Divide

   £100 ÷ £3 = 33 shares. That is the position size — no judgement involved.

4. 4
   Sanity-check the notional

   33 × £50 = £1,650. If that requires more margin than you want to commit, the trade is not available to you at this account size.

Risk-reward and why win rate alone means nothing

A 90% win rate sounds excellent until you learn the losses are ten times the size of the wins. What matters is expectancy:

Expectancy = (win rate × average win) − (loss rate × average loss)

Notice the 40% row. Being wrong 6 times out of 10 is entirely compatible with making money — provided the winners are meaningfully larger. Most people find this emotionally difficult, which is precisely why the approach remains available.

Watch what variance actually does

Set a positive expectancy below and look at the spread of outcomes. Every line uses the identical strategy — the only difference is the order in which wins and losses arrived.

Now push risk per trade up and watch which number actually moves. The median outcome climbs — that is exactly why over-sizing is tempting. But the worst drawdown figure climbs faster: roughly 10% when risking 1% a trade, and 50–70% by the time you are risking 6–10%. A strategy with a genuine edge, sized that aggressively, routinely spends part of its life more than half below its peak.

That is the real mechanism of failure, and it is worth being precise about it. The arithmetic does not bankrupt you here — the behaviour does. Almost nobody keeps executing a system that is 60% underwater, so the trader abandons it at the bottom and converts a mathematical edge into a realised loss.

Correlation — the hidden concentration

Five positions at 1% each looks like 5% total risk. If all five are US technology stocks, it is closer to a single 5% position — they will fall together on the same news.

• Cap total open risk, not just per-trade risk. Around 3–6% across all positions is a common ceiling.
• Group by driver, not by name: long EUR/USD and short USD/CHF are largely the same dollar trade.
• In a genuine crisis, correlations converge toward one. Diversification helps least exactly when you need it most.

Rules worth writing down

• Maximum risk per trade: 1% (0.5% while learning)
• Maximum total open risk: 3–6%
• Maximum daily loss: 3% — then stop for the day, without exception
• Maximum weekly loss: 6% — then stop for the week and review
• Never add to a losing position to improve the average price
• Never widen a stop once the trade is live