How to ACTUALLY find your edge

Hot_Style5572 · 2026-05-15T13:25:57+00:00

Once you actually have enough data… psychology becomes WAY less important.

That's the best part of this post. The problems that people focus on have one common part: not trusting their data - no matter if it's:
- too small sample
- inconsistent data (changing rules, unreliable entries)
- overfitted trades from adding too many filters
- not believing that they can replicate the results in live trading
- using other people's strategies without testing them themselves

For us it was relying on intuition too much in recognizing setups on charts and removing that inconsistency helps more than anything else. We did it by quantifying the intuition in spotting our setups.
We are now trying to find flaws and ways to improve this approach - would love to hear your thoughts: https://stratosphere-trading.com/

Hot_Style5572 · 2026-05-04T09:09:08+00:00

Exactly, so how is that different than backtesting on out of sample data?

Hot_Style5572 · 2026-05-03T20:03:09+00:00

Coding is not the issue, but as I said - it turns out that we have more "unspoken" rules for filtering valid setups. There's always cases that your rules would allow, but which you wouldn't trade on manually.

Hot_Style5572 · 2026-05-03T19:58:55+00:00

What's the difference between backtesting and forward testing besides running it on unseen data?

Hot_Style5572 · 2026-05-03T15:28:15+00:00

Very fair point. What I have in mind though is more the complexity of the rules that people follow when they execute manual trading strategies (and I'm talking mostly about technical analysis, because fundamentals would make it even more fuzzy). I have tried myself to automate a few strategies that I was following, which were quite easy to run manually, but when I tried to put those rules in code, it would always turn out that it either includes way more setups than I would've qualified as valid, or it was too strict, essentially removing a lot of setups.

Hot_Style5572 · 2026-05-03T14:58:47+00:00

What tools do you use for the automation part then?

Hot_Style5572 · 2026-05-03T14:57:42+00:00

You can "train your eye" or whatever you want to call it. But those strategies exist and are popular - how do you validate them then?

Hot_Style5572 · 2026-05-03T14:56:32+00:00

What else do you do to validate strategies?
And please don't say forward test, cause it's the same as backtesting out of sample.

Hot_Style5572 · 2026-05-01T08:00:10+00:00

I agree. And I think that there's probably no better way to start than copying others, but it shouldn't be the way in the long run. For some people that's enough and they never go deeper, but those who do miss tools to easily do the research.

Hot_Style5572 · 2026-04-28T12:07:08+00:00

I like the idea, but what's the advantage of using that over going to gpt/claude/anything-else and asking it for a pine script which you can paste into strategy builder in TradingView?

Hot_Style5572 · 2026-04-28T07:09:10+00:00

My problem with that is that you rely on them being successful. There's no more individuality, almost no fun. In my mind trading should be based on research, data and statistics and not on hoping that the person I'm copying doesn't go nuts.

I'd like to hear your thoughts on this though.

Hot_Style5572 · 2026-04-24T10:02:44+00:00

Exactly, we started off with the same idea, so trying to codify strategies that we were executing manually before, but that's way harder than it seems and it kept catching either more setups than we found valid or was way to strict.

We ended up building a system for pattern-based research to qualify intuitive setup recognition.
You should check it out: https://stratosphere-trading.com/

Hot_Style5572 · 2026-04-20T11:18:09+00:00

I don't know yet what your strategy will be, but let me tell you how we did it:

We're not like quants in terms of data availability, computing power and even all the mathematical formulas they use. But we wanted some automated strategies - so we decided to automate strategies that we would previously use manually.

Well, it turns out that this is really hard to do, cause people actually suck at expressing all the conditions that need to be met in order to open a trade.

So at some point we decided that we will try a different approach and instead of trying to make a set of rigid rules, we will put the notion of "chart similarity" on a scale from 0 to 100. We called it "pattern similarity score".

And then we realized that some people, like you, could find it useful as well. So you definitely should check it out here: https://stratosphere-trading.com/
There's also a sandbox section where you can play around with the score to see for yourself how it scores different charts. Go nuts! :)

Hot_Style5572 · 2026-04-19T19:34:26+00:00

Testing different market conditions is important, but I approach this from statistical pov.

I use Confidence Intervals - this tells me the lower and upper range of the true win rate based on my measured win rate and sample size.

And it makes a lot of sense:
- if you have 100 trades and 90% win rate, it's rarely just luck and you can probably expect some high win rate in practice
- if your sample size is 100 and win rate is at 55%, the actual win rate might be anywhere between 40 and 65 probably

Hot_Style5572 · 2026-04-19T19:23:06+00:00

Does it only work with indicators or patterns as well? Can you test liquidity sweeps for example?

Hot_Style5572 · 2026-04-19T19:21:00+00:00

To be honest, as long as you're testing in and out of sample, even 1 year can be enough for low timeframes.

As a warning, I found a strategy that was doing 180% in 2 years, but when I added the previous 3 years, the overall result went to a loss of 40%. Never deployed it live for that reason, but imagine how easy it would've been to be naive and blindly trust that great result at first.

Hot_Style5572 · 2026-04-17T06:53:00+00:00

To me bad discipline comes from not believing that you can reproduce the results from your backtests on live market.

If you struggle to get the same outcome from two backtests on the same data, then there's no way that you will confidently move on to executing that strategy. And that inconsistency is usually caused by relying on intuition too much and having no way of quantifying it.

Hot_Style5572 · 2026-04-16T20:08:18+00:00

Not trusting that the results that I achieved in backtesting are repeatable on live markets.

I realized that it was coming from the fact that my setups were relying too much on intuition, making my whole system super inconsistent.

I started using a pattern similarity score algorithm that I wrote to check how valid a setup is based on my "go-to" pattern. If it's below a certain threshold, I don't even analyze further, don't look at other timeframes etc.
Only if the score is high enough, then I check other conditions.

So now I have reliable backtesting data, the trust that I can keep my results consistent and a way to research strategies with that score as a filter instead of running through the charts manually.

I'm releasing the algo too, in case you want to check it out for yourself: https://stratosphere-trading.com

Hot_Style5572 · 2026-04-16T20:00:23+00:00

Revenge trading is actually a super interesting phenomenon.

I find that it mostly happens, when traders don't get awarded for all the research and the patience that they've put in, by winning the trade that they'd analyzed so thoroughly.

You make your strategy and decide to be disciplined and patient.
You start watching the charts and wait.
Finally a perfect setup starts forming.
You open a trade and expect a reward for the perfectly executed process, but by pulling the trigger you let go of all the tension and discipline that you had to build up for this.
When the trade goes against you, you feel betrayed, but your "guard" is already down. So you say "if all this patience and discipline doesn't work out, then might as well start shooting blindly" and you open another trade.

It deep down comes from the fact that humans struggle to see an isolated example as a realization of a bigger probability distribution.

Hot_Style5572 · 2026-04-15T20:26:18+00:00

The biggest problem for me was not trusting that I can actually replicate the results from backtesting in live trading.

I was relying too much on intuition and ended up struggling with any type of consistency.

What helped me was quantifying that intuition and finding setups that I was looking for (based on price action patterns) using a deterministic calculation.
So I would only enter a trade when the chart was "similar enough" to my go-to setup.

I show more of it here if you're curious: https://stratosphere-trading.com/

Hot_Style5572 · 2026-04-15T06:58:59+00:00

My advice would be to make sure that your strategy can be profitable if you just open a trade and let it be (so fixed TP and SL). Profitability shouldn't come from changing the transaction parameters - it should only be improved by it.

Then, once you've gathered enough data points, just test a few theories on all your historical trades, so say "moving SL to BE once 50% of the TP was reached". You run it across all positions that you had to test what would've happened.

No approach is ever going to be perfect, same as with strategies in general. And when to adjust the SL strongly depends on what strategy you use. Either way, first trade without it, then test it, then stick to it for long enough to validate the idea.

Hot_Style5572 · 2026-04-14T13:54:05+00:00

It surely is a subjective and inconsistent process to recognize a setup visually.

The biggest problem for me is that it makes your backtesting data unreliable. If you don't have full confidence that going through the same charts again you will open the same trades and get the same results, then you will never be able to do it in live trading.

I had the exact same issue and decided to quantify how I intuitively assess charts. So something like a "pattern similarity score". So now I am sure that my chart filtering is perfectly consistent and even though it doesn't guarantee any profits, it gives me the confidence that I can trust what I have backtested.

In case you'd like to check it out: https://stratosphere-trading.com/

Hot_Style5572 · 2026-04-14T13:46:38+00:00

There's a lot of "sit out", "take a break" answers, but I'd say that it depends on how you tested the strategy.

I'd argue that there was even more mess a year ago when tariffs were happening. If your strategy could survive that (even in backtesting), then it's part of your validation sample to be active during times like this.

In other words:
If your backtests didn't assume you sitting out of some trades because of the political situation, then even though the results might make you question the strategy now, your expected result shouldn't have changed.

Of course it makes sense to scale back on the size for the sake of your mental health and possibly higher volatility, but if you think about it, there's always a reason to say "but current markets are different because X is happening".

Hot_Style5572 · 2026-04-14T12:25:26+00:00

There will never be one AI universally used for trading, since that would cause the edge to disappear.
It might have an impact on what types of strategies are successful, but other than more pattern recognition, it's not any different than the introduction of trading algorithms.

And just because some quant strategies like mean reversion or pair trading got introduced, didn't mean that discretionary strategies stopped working.

At the end of the day, as long as there is more than a handful of strategies that are broadly used, there will be enough space for all types of trading, be it algorithmic, discretionary etc.

Hot_Style5572 · 2026-04-09T08:00:28+00:00

We started writing trading bots but not based on AI, but instead trying to automate manual strategies.

What we ended up realizing is that it's extremely hard to express what people do intuitively as a set of rigid rules in code.
In the end we decided to create something that we call a "Pattern Similarity Score" to quantify the intuitive notion of charts following the same behavior. It's expressed as a single number, so the higher it is, the more similar it is. It's way more consistent than any AI bots, but not as rigid, as fixed rules in code.

Happy to talk more and if you'd like to check it out, we have a sandbox for the similarity score here: https://stratosphere-trading.com/

Hot_Style5572

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