Reviewing the Day Trading Setup w/c 19 Jan 2026 - FTSE 100
- Chris Beament
- Jan 25
- 3 min read
We wanted to show you how we day trade some indices and provide real results. If you want a full run through of this strategy then check out our Strategy Section.
First up, lets just do a quick summary of the rules.
Market: FTSE 100, intraday
Setup: spring / fake breakout on 5-min
Fixed risk per trade: 1R = £50
Initial stop = 1R, always the same £50 risk
Take half off at +1R (£50 move)
Remaining half:
Stop moved to breakeven (or effectively risk-free)
Then trail using structure / 21 EMA
Let winners run — no profit cap on the second half
So in P&L terms:
A full loss = -£50
A scratch / partial = +£25 (half at 1R, half stopped at Break Even)
A runner = £25 + whatever the second half delivers
That’s a very solid asymmetric model and the heavy lifting is done by the runners and managing risk.
Monday saw no trades. So you had to be patient.
On Tuesday, The first two trades are losses.
We were looking for those wicks to create a false breakout area. But within this sequence, price wants to push higher and the market is not interested in reversing.
That evening, there were two more trading opportunities. The third trade of the week would have stopped you out again very quickly. You could have re-entered and that ran overnight stopping us out for 1.6x....
Our rules state that we take half profits at 1R. This is to manage risk and help pay for those losses. There were 4 trades on Tuesday. 3 Losses and One that ran to 1.6R. We'll tally up and the end of the week.
You had to wait until 5pm for a trade on Wednesday. Price just undercut to prior wick low and the second candle in the sequence bounced straight back into the range. This rallied hard and produced a 6x trade. We trailed the stop below the 21 period moving average and then got stopped out on the second half of the position overnight.
The next trade is fairly subtle - it's a small wick up only 6 candles before the actual entry signal. We prefer a more obvious setup but it gives you an idea of how set ups and entries can vary. It runs to nearly 6.3x
The final two trades of the week saw a 2.2x trade and then a loss which was a little annoying as the position was a whisker away from 1R and taking first profit.
So tallying that up....
Trade-by-trade breakdown
🔴 Losses
We had 4 full losses on the week:
4 × (-£50) = -£200
Clean, controlled. No damage.
🟢 Winners
Now the fun part.
Tuesday – 1.6R runner
Half at +1R = +£25
Remaining half runs to +1.6R = +£40
Total: +£65
Wednesday – 6R runner
Half at +1R = +£25
Remaining half to +6R = +£150
Total: +£175
Thursday – 6.3R runner
Half at +1R = +£25
Remaining half to +6.3R = +£157.50
Total: +£182.50
Friday – 2.2R runner
Half at +1R = +£25
Remaining half to +2.2R = +£55
Total: +£80
Weekly totals
Winners
£65
£175
£182.50
£80
Total winners = £502.50
Losses
-£200
✅ Net P&L for the week
£502.50 – £200 = +£302.50
Why this is a very healthy profile
A few important takeaways:
1️⃣ Win rate doesn’t matter here
You had:
8 trades
4 losses
4 winners
That’s a 50% win rate, and you still made strong money.
This is exactly what you want from a spring / fake breakout model.
2️⃣ The edge is in the tails
Look at where the P&L came from:
Two trades (Wed + Thu) = £357.50
That’s more than the entire week’s profit
If you’d capped winners early, this system dies.
3️⃣ Your risk is doing the heavy lifting
Fixed £50 risk
No sizing mistakes
No revenge trades
Losses stayed boring
That’s professional behaviour, not retail behaviour.
4️⃣ Variance worked — but didn’t need to
Even if we:
removed the 6.3R trade
or replaced it with a scratch
We'd still be up on the week. That’s key to understanding this isn’t a fragile edge. it also helps to build confidence.
Big picture
We took:
No trades Monday (discipline ✅)
Sat through 3 losses Tuesday (emotional control ✅)
Let runners actually run (process integrity ✅)
This is exactly how this setup is supposed to behave over time. We also trade this setup on the Nasdaq so next week we'll run the same profile and results for that market.
Happy trading.
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