My quarterly look back at how my risk per trade drifted

[Fairman]

My quarterly look back at how my risk per trade drifted

every three months I go through my journal and look only at one thing: my actual risk per trade compared to what I'd planned. I'd assumed I'd been consistent. The data said I hadn't.

What I found is that my size drifted in a pattern. After a few wins, it crept up a little. After a couple of losses, it dropped. So my biggest positions often came right after good runs, when I was overconfident, and my smallest came after losses, when I was shaken. Neither was a decision, they were reactions.

The difference was not huge on a single trade, but in total it was a drag. My losing trades averaged a bit larger than my winning ones, mostly due to the timing of the size changes.

Since seeing that, I've fixed the risk in money for each trade, and I check it before every entry. I calculate the lot size from the stop distance, and I don't change the percentage based on how the last trades went. I'll check again next quarter to see if it's holding.

[Fairman]

How I check it in practice. My journal has a column for planned risk in money and one for actual risk, which I calculate from the entry, stop and lot size after the trade. Once a quarter I plot them side by side in order. Any drift jumps out as a wavy line instead of a flat one. It takes about fifteen minutes and it is the only way I have found to see these patterns honestly. Doing it quarterly keeps it from becoming a chore.

[Fairman]

Something I did after this review was make the lot size calculation automatic. I put my risk amount into a small calculator, enter the stop distance, and use whatever it gives me. No adjusting it up or down based on how I feel. It removed the decision completely, and since then my size has been almost flat. I still check every quarter, but there is a lot less to find now. Taking the choice away was the real fix, more than any amount of willpower or reminders written on sticky notes.

[Shadow Trader]

One thing worth separating in a review like this is timing and trade quality. If trades are independent, sizing up after wins should not on its own make the losers larger on average, because the trade after a winning run is still roughly a coin flip.

So if the losers do come out larger, the bigger trades may also have been worse trades. Checking the win rate of the oversized trades on their own would show whether confidence was loosening the entry rules as well as the size.

Lot rounding is a quieter source of drift on small accounts. Say the account is 2,000 dollars at 0.5 percent risk, which is 10 dollars, and the stop is 7 pips, so the exact size is 0.143 lots.

Rounding that to 0.14 or 0.15 moves the risk by a few percent each time. That is small on one trade, but if the rounding always goes up when feeling good and down when nervous, it becomes the same pattern in a smaller form.

Does the calculator include commission and the spread in the risk figure? With a 7 pip stop, paying 0.7 pips round trip adds about 10 percent to the real loss, which a flat planned risk column will never show.

[Shadow Trader]

An average is a weak test for this kind of drift, because the swings up and down can cancel out. A quarter where risk ran well above plan after wins and well below after losses can still average close to the planned figure.

Say planned risk is 50 dollars and a made up run of 20 trades shows actual risk between 35 and 66. The mean comes out at 51.25, which would pass a check that only looks at the average.

img_13554_r2.png (55.18 KiB) Viewed 71 times

A tolerance band tells a different story, as the chart (illustration) shows with a band from 45 to 55. Eleven of the 20 trades sit outside it, seven above and four below, so more than half the sizing was a reaction rather than the plan.

The band width can be set from the rounding problem. If minimum lot steps alone move risk by up to about 5 percent, a 10 percent band absorbs that noise while still catching the deliberate changes.

Counting trades outside the band each quarter gives one number that can be compared over time. Would a stricter band of 5 percent be realistic once the calculator is doing the sizing?

[FXS Prop Desk]

The drift pattern you found, size creeping up after wins and dropping after losses, shows up in almost every journal we look at. It is the reverse of what helps: bigger size when confidence is high usually comes just before the normal losing streak.

A fixed lot size table for each stop distance, prepared in advance, removes the decision. With the size taken from a table instead of calculated in the moment, there is much less room for mood to change it.

[Shadow Trader]

Scalpers can take hundreds of trades a day. Whether they should is another question.

Costs scale with trade count, attention declines through the session, and the quality of later trades is usually worse than the earlier ones. A cap on daily trades forces selectivity: with only fifteen trades allowed, each one needs to be worth taking.

Analyse the journal. Plot average result per trade by trade number within the day. Many traders find the first ten trades carry nearly all the profit, and later ones erode it.

A cap also protects against the spiral. After a bad start, the urge to trade more to recover is strong, and a limit blocks it.

How to pick the number? Look at the data. Find the point where average expectancy turns flat or negative, and set the cap slightly before it.

What does trade quality look like by trade number, and where does it fall off?