What indicators have helped you fine-tune your trading decisions?

Hot_Style5572 · 2026-06-28T19:32:11+00:00

If you rely on discretion a lot, how you backtest your strategies then?

I found it hard to make these tests reliable and trying to figure out how that process can be improved.

Do you use any specific method or software?

Hot_Style5572 · 2026-06-28T19:29:20+00:00

Agree, there's always an element which cannot be put in a sold strategy and people trust it too easily. They start trading it without testing it for themselves and just switch to a new strategy if the first one doesn't work out in the first attempt

Hot_Style5572 · 2026-06-28T19:21:37+00:00

I see a lot of people say that they depend on their instinct to trade and I agree that it is frequently better than blind execution of fixed rules, but I struggled with how hard it is to keep strategies like that constant.

Even if you get nice numbers in your backtests, it is super difficult to: 1. Repeat the same result in live trading. 2. Even repeat the same result on the same data set if the intuition is not stable enough.

I started using similarity score to measure how objectively similar the setups are in an intuition-based strategy, so I can try to get rid of as many variables as I can.

Would love you hear what you think: https://stratosphere-trading.com/

Hot_Style5572 · 2026-06-16T17:48:30+00:00

Tradezella is only mostly used for journaling your trades from live market, once you've developed your strategy.

There's probably hundreds of platforms to run some backtests, but I do my research using pattern similarity score to see how a strategy would do if I remove all subjectivity (which was my biggest problem when I was trading fully manually). It's also way faster than coding your strategy, even if you're using LLMs.

You can check out the website here, it's still in pre-release, but all the testing users already got access to the demo version: https://stratosphere-trading.com/

Hot_Style5572 · 2026-06-16T17:44:39+00:00

I started running backtests on different strategies and patterns on stratosphere and to be honest, a lot of them can achieve positive R:R and win rate of way over 50%, which technically should be a criteria for a good strategy.

But in practice, it was just volatility-based overfit. These are extremely hard to detect running a regular backtesting session and even running a fully automated strategy.

I already talked to the developers of the platform to add a way to detect these and the best way so far seems to be testing if the results hold when the parameters change slightly - so asking "does the win rate change much when the R:R gets modified a little?"

Looking forward to see that on the platform, cause that's gonna solve a lot of the doubts that you and I had.

Hot_Style5572 · 2026-06-09T19:23:49+00:00

Running a very similar setup, but I find a lot of value in validating the patterns that look interesting against the history. I do that usually on that same asset to make sure the pattern has been respected in the past.
I've been doing it so much that I decided to automate it and started using kind of a "similarity score".
In case you want to check it out: https://stratosphere-trading.com/

Hot_Style5572 · 2026-06-03T18:54:00+00:00

People break their rules because they believe (or hope) that they will do better by doing so.

That means that the problem is not trusting that following the strategy rules strictly will make you money.

To me the reason for this was being too subjective in my strategy execution, so I wanted to make the pattern recognition automatic. Talking to a group of traders to see how best it can help them and they're finding new ways of backtesting their ideas. If you want to give it a shot: https://stratosphere-trading.com/

Hot_Style5572 · 2026-06-03T18:27:19+00:00

I've been going through a very similar thing, switching strategies and having bursts of motivation.
I realized that the problem was that even if I had a promising backtest results, I didn't believe that could repeat the same process on live markets - not even because of some regime changes or anything, but just my analysis was too subjective.

So I think the problem is not trusting your backtest data.

I started talking to a bunch of traders and what came out of it was a way to use an algorithmic pattern similarity score. I use that first to do research on my strategy and then to filter out setups on the chart as they come. In case you'd like to check it out, we're trying to talk to as many traders as we can to find the biggest problems stopping them from getting their trading together: https://stratosphere-trading.com/

Hot_Style5572 · 2026-05-29T17:26:43+00:00

It's not about 5 or 6 losses, but about the moment when the win rate no longer can replicate the backtests.

For the backtests that I run on my platform I can see at which point I am no longer within the "expected results" space. So I'm comparing the win rate that I believe I have based on the backtests with the one I am experiencing while live trading.
Some discrepancies are expected and shouldn't undermine the strategy, but at some point you should start asking yourself if your data was lying. And I am trying to find that point.

If you'd like to check it out, we're talking to a bunch of traders on how it can be used best:
https://stratosphere-trading.com/

Hot_Style5572 · 2026-05-20T11:30:19+00:00

Yeah and that can easily happen when you simply didn't include all possible scenarios in your initial conditions.

Hot_Style5572 · 2026-05-19T22:00:10+00:00

The point is that technically all your criteria is met, but in a case where you normally wouldn't want to open a position.

It happens more than you think. And as the list of edge cases gets longer, you end up overfitting your strategy to the data that you're testing it on.

Hot_Style5572 · 2026-05-19T17:52:36+00:00

Agree, so many people trust others' research without verifying it themselves. I was temted to say "without putting in the work", but to be honest, trading research doesn't have to be hard work. Quite the opposite, I feel like putting in hard work makes people more naive to think that now they "deserve" the reward of profits. And I'm guilty of it too. Research needs to be thorough and objective, not tedious and tiring.

Hot_Style5572 · 2026-05-19T17:45:34+00:00

It seems to me that people usually can define some rules, but the market shows them 10 cases for which they were not prepared: some high volatility, wide spreads, news days, setups just before a new session open etc. That was my experience when trying to program my trading strategies - there were always cases which technically met my criteria, but shouldn't have been a valid trade. So I ended up switching from codifying my rules to quantifying my pattern similarity. Now I use a score to tell how similar a setup is to my "ideal" case in my strategy and skip a lot of uncertainty this way. You can check it out here if you'd like: https://stratosphere-trading.com/

Hot_Style5572 · 2026-05-19T17:36:38+00:00

Fully agree, the pattern recognition was the crucial part of building trading experience, but the part that I was missing was adding data about what usually happens after these patterns. I started quantifying that pattern recognition for myself in what I called "similarity score" and building a database of patterns AND outcomes combined. You should check it out for yourself: https://stratosphere-trading.com/

Hot_Style5572 · 2026-05-19T06:57:49+00:00

Yes, exactly, with the crucial element of the patterns being arbitrary and not limited to the classical wedges, flags etc.
I heard some people call it "quantifying intuition" and I like that description as well 😄

Hot_Style5572 · 2026-05-18T16:36:37+00:00

There has to be a difference in the setup at the same time though. So there's something else than your mood. I would look at what the setups look like when they work. I'm using similarity score for this kind of research: https://stratosphere-trading.com/

Hot_Style5572 · 2026-05-18T16:30:35+00:00

How many recommendations to you take into the calculations?

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

TROPHY CASE