A director of a bank’s trading division sat across the table from my business partner, looked at our audited CTA results – 75-80% return with 11% drawdown – and said: “That’s not possible.” Their best programme makes 5-6% per year with an 80% drawdown. When the audit confirmed the results were genuine, their top trader called it Photoshop.
When my partner explained the framework – genetic algorithms, three levels of robustness testing, Monte Carlo analysis – the director’s response was: “That sounds suspicious. That’s not the traditional way to do trading.”
That story is funny and sad in equal measure. But it’s also a perfect illustration of a problem I see constantly in retail trading: a deep, reflexive attachment to “traditional” methods that stopped working a long time ago.
What Does “Traditional” Actually Mean?
When traders call something “traditional,” they usually mean one of two things: it’s been around for a long time, or it’s what most people do. Neither of those is a good reason to trust it.
Most traders don’t make money. I’ve worked with thousands of traders over my career. The majority follow what they’d describe as traditional approaches – standard indicators, common entry rules, widely-taught exit methods. And the majority lose. There’s a strong correlation between following traditional methods and losing. That correlation should bother people more than it does.
The trading edge doesn’t live in what everyone knows. It lives in what most people haven’t tested, haven’t thought about, or are afraid to try because it doesn’t look “traditional.”
Creativity in Trading Isn’t What Most Traders Think
When I say creativity, I don’t mean making things up or ignoring data. I mean systematically testing ideas that diverge from the consensus – especially ideas that directly contradict what’s conventionally taught.
The simplest entry point for creativity is this: take any traditional indicator or rule, and test the exact opposite.
RSI and Williams %R are good examples. The traditional application is textbook: RSI above 70 or 80 means overbought, expect a reversal, prepare for counter-trend. I spent years testing both indicators. Some of my strongest conditions came from using them in the opposite direction. One condition looked something like: if Williams %R is overbought for at least two consecutive bars, and the second bar is higher than the first – buy. The condition shouldn’t work by traditional logic. It worked extremely well.
The twist that made it work wasn’t just reversing the signal – it was adding a second bar requirement. That’s the creative layer: take the opposite, then add one wrinkle. That combination creates something genuinely new, and new is where edge comes from.
I know a trader who uses a 40-50 period RSI as a trend filter – the opposite of the short-period counter-trend application most people learn. Completely non-traditional. Works well for him. That’s the pattern: find the traditional use, invert it, see what happens.
Where to Apply Creativity – Beyond Entries
Most traders limit their creativity to entries. That’s understandable – entries feel like the most important decision. But entries are not where most of the edge lives in systematic trading. Here’s where I’d focus instead:
Exits and Trade Management
Exits have more impact on the shape of your equity curve than most traders realise. Standard exits – dollar-based stop losses, fixed profit targets – work fine, and we use them in the hedge fund. But the creative territory is in technical exits: moving averages, Bollinger Bands, swing points, combinations of all three.
Chuck LeBeau’s Chandelier Exit is a good historical example. The concept – trail your stop from the highest high reached since entry, using a multiple of ATR – was novel when he invented it. People probably told him it wasn’t traditional. Cut to 30-40 years later and it’s considered a standard tool. That’s what happens to good non-traditional ideas: eventually, they become traditional.
The point isn’t to be different for its own sake. The point is that fixed, traditional exits leave performance on the table that smarter exit logic can capture.
Position Sizing
This is probably the least-explored area in retail trading and one of the highest-leverage opportunities. Traditional position sizing approaches – fixed fraction, fixed dollar amount – are a reasonable foundation. But dynamic position sizing, where you vary your position size based on the estimated probability of a given trade, is where the real gains are.
I covered dynamic position sizing in detail in Episode 17, but the short version is this: not all trades within the same strategy have the same probability of success. The average win rate is an average, not a constant. When you can identify conditions where the probability is higher than average, you should be taking more risk. When conditions suggest lower probability, take less – or skip the trade entirely. In our hedge fund, risk per trade fluctuates between zero and 3.5% of capital depending on the assessed probability of each specific trade.
One BTA student – Al – went further than that. He built over 80 different filter conditions based on the course material, combining them in ways to identify exactly where a strategy’s strongest signals are concentrated, then applied dynamic position sizing only in those conditions. The results were dramatic equity curve improvements. That’s creative application of non-traditional thinking.
Robustness Testing
The traditional approach to strategy validation is simple walk-forward testing – run the strategy on out-of-sample data and see if it holds up. That’s a starting point, not an endpoint. In our hedge fund, we developed three distinct robustness levels, each with progressively tougher validation requirements. Robustness Level 3 – the highest – is something very few strategies ever reach.
Most retail traders don’t think of robustness testing as an area for creativity. I think it’s one of the most important areas. The question isn’t just “does this strategy work on out-of-sample data?” It’s “how many different ways can I stress-test this strategy before I trust it with real capital?” The more creative and demanding you are with robustness testing, the fewer curve-fitted strategies end up in your portfolio.
Read Masterclass Part 2 for more on how we approach the robustness question.
The Sweet Spot Between Wild and Conservative
I’m not saying ignore all traditional thinking. Some traditional foundations are solid – they’re traditional because they’ve proven durable. But using traditional concepts as a foundation and then pushing aggressively against them is very different from treating traditional approaches as the ceiling of what’s possible.
My usual process: start with the conservative, conventional approach to a problem. Ask what the traditional solution looks like. Then ask what the right opposite would be. Then test both, and everything in between. Wild ideas often don’t survive testing – but the ones that do tend to be genuinely novel and genuinely useful.
The bank director who called our results “not possible” is an extreme example of what happens when you optimise for fitting in with the traditional consensus. His trading division earns 5% per year at 80% drawdown. That’s not a problem of execution or resources. It’s a problem of thinking. He’s surrounded by smart people who have collectively decided to operate within a set of assumptions that no longer produce results.
Why Traders Resist Non-Traditional Approaches
Two reasons come up consistently:
Fear of being wrong in a non-standard way. If you try a traditional approach and it fails, you were just unlucky. If you try a non-traditional approach and it fails, you were reckless. This is a social and psychological pressure that has nothing to do with whether the approach would have worked.
Lack of confidence in their own ideas. A lot of traders don’t believe they’re capable of generating original insights. In my experience, this is almost always wrong. Some of the best trading ideas I’ve seen came from people I wouldn’t have predicted. The ability to come up with fresh perspectives isn’t rare – the willingness to test and act on them is.
Trading is a competitive field. The participants you’re competing against include professional quants, hedge funds with hundreds of millions in R&D budgets, and market makers with informational advantages. Copying what everyone else does isn’t a path to an edge. Systematically exploring what others haven’t tried – and testing it rigorously – is.
A Practical Starting Point
If you want to build creativity into your process right now, here’s a simple exercise. Take any indicator or rule you currently use in the traditional way. Write down the conventional application. Then write down the exact opposite. Then think of one twist – a second condition, a modified lookback period, a different timeframe – that creates a third version. Test all three.
You won’t always find something useful. But you’ll often find something that surprises you. And you’ll start to see your own strategies not as fixed rules to follow but as hypotheses to test – which is the mindset that separates improving traders from static ones.
For a structured approach to building and validating breakout strategies, start with our free content before you go into anything more advanced.
Ready to stop guessing and start trading with a systematic edge that actually holds up? Check out Breakout Trading PRO. It’s a structured, visual strategy builder inside BreakoutOS, powered by the proven Mr. Breakouts Formula used by thousands of traders.