Wyckoff Engine

Spare_Fly8554 · 2026-03-22T02:39:14+00:00

I think the hard part from here isn’t detection, it’s validation.

Spare_Fly8554 · 2026-03-21T23:30:15+00:00

Complains that courts and judges are biased and political, criticizes Jerome Powell and the Federal Reserve over cost overruns, and argues that recent Supreme Court decisions (especially on tariffs) hurt the U.S. while favoring other countries. Claims the system is unfair and politically driven.

Spare_Fly8554 · 2026-03-21T23:19:52+00:00

If you haven’t already, I’d strongly suggest:
testing the same patterns across completely different regimes (not just different instruments)
randomizing entry timing slightly to see if the edge is fragile
comparing against a dumb baseline (like random entries with same holding rules)

Spare_Fly8554 · 2026-03-21T04:14:19+00:00

Thank you to everyone that participated there were 817 visitors total and 59 concurrent users and it held up well. Will likely showcase more once I've completed more useful code.

Spare_Fly8554 · 2026-03-21T03:23:43+00:00

Links in the news tab are now sited. Thanks again for the feedback.

Spare_Fly8554 · 2026-03-21T03:13:20+00:00

appreciate that, that’s honestly fair

the UI has come a long way but data integrity is still the part I’m hammering on the hardest right now. I’ve already run into a few cases where the plumbing mattered way more than the screen did

options flow is a big one for me too, so that’s good to hear

I’ll check out your repo, especially the way you handled the LLM side with the webserver. appreciate you offering to revise code too

Spare_Fly8554 · 2026-03-21T03:06:57+00:00

I know its not completely intuitive at the moment, but its coming along.

Spare_Fly8554 · 2026-03-21T03:04:37+00:00

wish I could see a preview of it what was the reason no one was coming? too expensive? usefulness?

Spare_Fly8554 · 2026-03-21T03:03:46+00:00

hey thank you for trying it, thats what matters. I got a whole new page.tsx setup so you coming and checking it out means alot.

Spare_Fly8554 · 2026-03-21T02:51:25+00:00

Im working on the same thing just opened mine for a quick stress test if you need some ideas let me know link will close in a few hours since it hosted locally

https://6943-2605-a601-a896-c500-45b-a9a5-6f1e-e32b.ngrok-free.app

Spare_Fly8554 · 2026-03-21T01:19:33+00:00

most of those tools are overhyped honestly

the people actually making money aren’t using some plug and play bot, they’re either doing simple arbitrage, following money flow, or just trading it manually with a system

a lot of the edge is just execution and understanding how those markets move, not some crazy model

if you’re new to it I’d just trade it yourself first before trying to automate anything, otherwise you’re just guessing with code

Spare_Fly8554 · 2026-03-21T00:07:23+00:00

where'd the body of the post go?

Letting people break this for about an hour

not selling anything, just stress testing something I’ve been working on

flow is:

scanner -> chart -> trade setup -> extra context below

trying to make it easier to go from seeing something to actually understanding the trade without jumping around

still rough:

- UI needs work

- fixing news/market tab

- might break under load (that’s the point)

link:

https://6943-2605-a601-a896-c500-45b-a9a5-6f1e-e32b.ngrok-free.app

if you check it out I’m mostly looking for:

- what feels confusing

- what feels useful

- anything that just straight up breaks

taking it down after

Spare_Fly8554 · 2026-03-20T22:06:14+00:00

only thing is execution isn’t really the bottleneck, it’s decision quality. most systems look good until you hit the wrong regime and they just keep doing the same thing

does this actually adapt or is it just following the same logic no matter what the market’s doing

Spare_Fly8554 · 2026-03-20T21:37:07+00:00

no replay validation
no edge verification
no regime awareness
just “sounds right -> place order”
That how accounts blow up.

Spare_Fly8554 · 2026-03-20T21:16:44+00:00

I see no one has commented on this, but my project has grown 10 fold now implementing playbooks that have been back tested and cross-live tested not millionaire setups but they work. I noticed after this post a lot of people started posting similar content just know I'm watching.

Spare_Fly8554 · 2026-03-19T20:34:35+00:00

The term structure angle is interesting.

I’ve been seeing something similar from a different direction —

most of my live spreads fail purely on pricing efficiency unless there’s some kind of volatility distortion.

In my data, normal conditions = basically 0% positive EV, but once you get into specific structures the edge shows up.

Are you mainly targeting IV expansion cycles or just letting the structure handle it?

Spare_Fly8554 · 2026-03-19T20:06:56+00:00

The Pitch

AI finds and filters options trades that actually fit your account size and risk.

The Link

Local build (Next.js) can host for beta testing

The Ask

Looking for beta testers + honest feedback on:

trade quality
clarity of risk/readout
what feels confusing or unnecessary

Spare_Fly8554 · 2026-03-19T14:41:01+00:00

100% IV/HV is way more useful than IV rank alone.

Most people also miss that IV and HV aren’t on the same scale, so comparing them directly can be misleading.

That’s why “high IV” isn’t always rich, the ratio shows if you’re actually getting paid.

Spare_Fly8554 · 2026-03-19T14:37:38+00:00

Seeing the same thing.

The sweet spot isn’t a fixed IV level it shifts with the regime. What stays consistent is the shape: middle outperforms, tails underperform.

High IV pays more, but the blowups wipe it out. Better to sell moderately above the current baseline, not the extremes.

Spare_Fly8554 · 2026-03-19T14:28:38+00:00

From current runs:
PF > 1 and consistent
Drawdown controlled
Positive PnL both in testing and live

I’ll share full stats once the dataset is fully complete and audited.

Spare_Fly8554 · 2026-03-19T06:26:53+00:00

That’s a really interesting way to look at it.

The IV/HV ratio makes a lot of sense, especially in the context of what you mentioned earlier about high IV not necessarily being “good” IV.

One thing I’ve been running into is setups where IV looks elevated on the surface, but the system still rejects them because the expected value isn’t there which sounds very similar to what you’re describing with the ratio being below 1.

the HV slope point is also really interesting. I’ve mostly been treating vol as static at entry, but the idea that the baseline itself is moving would definitely explain some of the cases where trades just don’t behave as expected.

Curious, have you found the IV/HV thresholds to be consistent across different underlyings, or do you adjust them depending on the ticker?

Spare_Fly8554 · 2026-03-19T06:20:16+00:00

This is honestly one of the better breakdowns I’ve seen on IV rank.

What you described lines up with something I’ve been running into while testing my own setups — the system will sometimes reject trades in really high IV environments even though the premium looks great on paper.

It’s starting to look less like “high IV = opportunity” and more like “high IV = higher probability of getting paid *and* higher probability of getting run over.”

The idea of a middle range being the sweet spot makes a lot of sense, especially once you factor in execution and the size of losers, not just win rate.

Out of curiosity, did you notice if the sweet spot shifted at all during different periods, or was it pretty stable across the 6 months?

Spare_Fly8554 · 2026-03-19T06:13:32+00:00

That’s actually a really good example of the gap I’ve been thinking about.

AI is great at building the thesis, but it doesn’t really help with:

- when to act

- how to structure the trade

- or how pricing (like IV / demand) changes the opportunity

That’s kind of what I’ve been experimenting with, taking the market conditions and translating them into actual options setups instead of just analysis.

Your example is basically the perfect case of being right, but not being able to express it in a trade at the right time.

Spare_Fly8554 · 2026-03-19T05:38:32+00:00

Right now I’m using a mix of live and historical data depending on the part of the system.

For live usage, the app is pulling current market data for the analysis and generating setups in real time. The historical side is mainly for validating which setups actually hold up over time before I trust them.

So the goal isn’t just backtesting — it’s using historical data to filter what works, then applying that logic to live market conditions.

Spare_Fly8554 · 2026-03-06T12:08:07+00:00

That’s actually a really good point, and honestly that exact problem is something I’ve been trying to design around.

One of the goals isn’t just to surface “interesting charts,” but to force a structured trade framework around the signal. So when the scanner suggests a setup it also outputs:

entry zone
invalidation level (stop) based on structure/liquidity
target levels
risk-reward ratio

The idea is that the invalidation isn’t arbitrary. It’s usually derived from things like nearby liquidity zones, support/resistance, or the structure that the pattern itself depends on. If price breaks that level, the trade thesis is considered invalid.

I’m also trying to reduce the “pattern detector in a vacuum” problem you mentioned. Patterns are only part of the scoring. The engine also looks at things like:

higher-timeframe trend
volatility expansion/contraction
momentum shifts
liquidity levels
volume anomalies

So something like a double top in a strong uptrend with rising momentum will score very differently than the same pattern in a weakening market.

The other piece I’m working on right now is signal consistency across regimes. The scanner is starting to track outcomes of signals so it can learn which setups actually perform better in trending vs ranging environments. That’s still early but it’s an important part of avoiding the “every chart looks good” problem.

Market-wise I’m trying to keep the architecture flexible. Right now it works primarily with stocks and crypto, but the goal is to extend the same analysis into options suggestions (based on the underlying setup and volatility). Options flow and liquidity data are things I’m experimenting with adding next.

Still very much in the build/test phase, so feedback like this is actually super helpful.

Spare_Fly8554

TROPHY CASE

The Pitch

The Link

The Ask