Traders Mastermind

Sponsored by Pepperstone

Why can't I run my winners? It's one of the most common questions I get from traders. And the obvious answers (be more disciplined, walk away from the screen, trust the trade) usually don't work.

So in this episode, I borrow an idea from Rory Sutherland, the Ogilvy behavioural economist: "the question is a lazy formulation of the problem." And I apply it to running winners.

Turns out the reason most traders never solve this is because they're asking the wrong question. We work through better ones, and what changes when you do.

Sponsored by Pepperstone

John had his best month ever. Then gave back 70% of it the month after. He asked: Did I crack it, or did I just get lucky?

Here's the real answer and the high-watermark trick that stops your brain from sabotaging the run after a good one.

Sponsored by Pepperstone

AI has just taken a massive leap. You can now ask it pretty much any question about price action, drop in a free CSV from TradingView, and properly interrogate the data. But most traders are asking the wrong questions.

In this episode, Mark breaks down a simple 5-question framework for using AI to support discretionary trading… not replace it.

It's not about building quant algorithms. It's about testing the hunches you've carried around for years, layering another edge onto your setups, and trading with a bit more conviction because the data has your back.

Covers:

Why "what will happen?" is the wrong question
The 5 questions to ask before writing any prompt
How to export a CSV from TradingView in 10 seconds
Real prompt examples for FX, indices and metals
The mindset shift from prediction to historical probability

If you've ever said "gaps always fill" or "after a trend day we always retest" this is the episode that shows you how to actually test it. Quickly.

Sponsored by Pepperstone

Most traders just pick 1% because someone told them to. But where did that number come from? And does it actually make sense for your goals, your win rate, and your R:R?

In this episode I break down how to reverse engineer your risk per trade from your actual trading data.

We look at why trade frequency can be a trap, why small changes in R:R massively shift the maths, and why the textbook approach ignores the one thing that matters most... your goal. I also built a risk per trade calculator you can play with.

Risk Per Trade Calculator

Sponsored by Pepperstone

Charlie Munger used to do something interesting when he was stuck on a problem.

Instead of asking how do I succeed, he'd ask how do I guarantee failure… then simply not do that.

In this episode I take that idea and apply it to trading. How would you guarantee you never improved?

How would you make sure a small loss became a big one?

How would you design a routine that burned you out within a year?

The answers are uncomfortably familiar.

Sometimes the edge isn't something you add to your trading. It's what you stop doing.