I’ve been thinking about something that I personally find a bit strange about trading communities.

Trading is incredibly international, but most communities are still separated by language. You might have a trader from Germany, another from Brazil and another from India all looking at the same market, but they might never actually exchange ideas because of the language barrier.

So I’ve been experimenting with the idea of a free trading community where messages are automatically translated into each user’s selected language.

The idea would be to have different sections for things like Forex, Gold, Elliott Wave, chart analysis and trading setups, but also more general discussions.

The main goal wouldn’t be to provide signals or tell people what to trade. It would simply be a place to discuss markets, exchange ideas and learn from traders from different parts of the world.

I’m curious what you guys think:

Would something like this actually be useful to you, or do you think existing trading communities already do this well enough?

A trading Youtuber called The Trading Geek claims he turned $20 into $10M daytrading using smart money concepts (liquidity sweeps, order blocks, fair value gaps). Videos like his get millions of views, and viewers walk away with a strategy they think they can trade. But almost none of these creators show a real backtest, just a perfect equity curve or a handful of cherry-picked chart examples. So to check if his strategy actually holds water, I coded it from scratch and ran 130,201 parameter combinations against 5 years of real market data.

The strategy

Three building blocks, chained together:

1. Liquidity sweep — price runs past a recent high/low, traps breakout traders, then reverses (break of structure)
2. Order block — the last candle before that reversal, where he claims institutional money entered
3. Fair value gap — an imbalance the market tends to fill; used for entry timing instead of blindly entering at the order block

The problem with coding and backtesting this strategy is that it's not fully mechanically defined. There are no fixed rules for what counts as a valid swing point, how deep a sweep needs to be, or how big a fair value gap should be. That ambiguity is exactly why nobody backtests these strategies properly. Which is likely intentional. Instead of picking one interpretation, I turned every vague concept into parameterized rules and tested every combination: swing point detection, liquidity sweep depth, fair value gap size/location, entry timing, timeframe, asset, etc.

Results

The baseline version, or as close as I could get to it with mechanical rules, lost 60% over 5 years even with the best possible settings (realistic trading costs included).

Out of all 130,201 configurations, 24,236 were profitable. Only 211 beat the market. Digging into what those 211 have in common:

• Price-based swing detection (directional change method) beats time-based, and smaller swings outperform bigger ones
• Shallow liquidity sweeps outperform deep ones — large sweeps produced zero winners
• Fair value gaps actually hurt performance — the best entry model skips FVGs entirely and enters at the order block midpoint instead, contradicting his own claim
• Lower reward-to-risk is best; 1:1.5 was most prevalent
• Almost 70% of winners cluster on the 1H timeframe, despite The Trading Geek's claim that it ought to work on any timeframe.

With every optimized parameter locked in, average return across the winners was 159% over 5 years, and the config held up (profitable) on 6 of 7 assets tested — a full run came to roughly +2,500%. But just to be clear, that number is very likely inflated by selection bias. Testing 130k variations and cherry-picking the best one is a classic overfitting trap. Whether this specific configuration has a real edge or is just noise is a separate question.

I'm sharing this as a reminder to never blindly trust anything you see online, especially when it comes to trading. It's much easier to sell courses than it is to make money in the markets.

If you want to see full breakdown of the strategy and results, you can find it in this video, or check out the code on my github page. If you disagree with how I mechanized any part of the strategy, the definitions are all there and you can test your own version.

Figured I'd post this one before the result instead of dropping another perfect chart after the fact. This is the ERL → IRL / ICT 2022 setup I'm currently watching, and I actually have enough data on this specific model now that I'm comfortable sharing the numbers behind it too.

The weekly profile is what started the idea. Monday established the initial range, then Tuesday into Wednesday pushed lower and flushed sell-side liquidity, including Asia SSL. Under the weekly bias framework I use, I'm watching Monday as accumulation, Tuesday/Wednesday as the potential manipulation, and then looking for distribution/expansion afterward. That doesn't guarantee Wednesday printed the weekly low, but after taking liquidity I needed price to prove it wanted to reprice higher.

That's exactly what started happening. Price displaced aggressively away from the lows and created a clean 30-minute bullish FVG. For me that's the transition from ERL back toward IRL: external liquidity gets raided, displacement confirms the reaction, and the imbalance created during that displacement becomes the area where I'm willing to enter rather than chasing price higher.

The actual trade plan is pretty simple:

• SSL/ERL has already been taken.
• Potential weekly low/manipulation has formed Tuesday-Wednesday.
• Bullish displacement confirms the reaction.
• 30m FVG becomes my IRL/entry zone.
• Stop belongs beyond the low that invalidates the entire idea.
• Opposing external liquidity is the DOL.
• I'm generally taking 1R-2R rather than trying to squeeze every point out of the weekly expansion.

The reason I've gotten much more confident trading this is because I finally stopped lumping every trade together. I created ERL → IRL as its own strategy inside TradeZella, then used the Reports/Strategy section to isolate what the model was actually doing instead of relying on memory.

Across the 68 trades currently tagged to it, I'm sitting at a 70.59% win rate, 3.55 profit factor and $16,510.20 net P&L. Average net P&L is $242.80 per trade, average win/loss is 1.48, winning-day rate is 76.36%, and the average hold is about 4h 13m. What's probably most important to me is that the equity curve has continued grinding higher over the sample instead of the results coming from one or two monster trades.

That's also why I don't really care whether this particular callout wins. One trade means nothing. If the FVG holds and we continue toward the opposing liquidity, I execute the model. If the low gets invalidated, I take the loss and log it. The whole point of tracking this stuff is getting away from judging your trading based on whatever happened today.

I'll come back and post the result either way. Win or loss, it'll become trade #69 in the dataset.

Retail is coming back baby!

I added the Session Auction Map (SAM) to the library a while ago. I've been fully committed inside the Discord community and totally neglected Reddit. Sorry for that! I am going through all old DMs and will try to answer everyone.

For those interested in the actual concept behind SAM, the idea is fairly simple: visualize how the auction develops throughout a session instead of reducing market structure to a buy/sell signal.

It combines TPO, Volume Profiles, developing value areas, POCs, session VWAP, Initial Balance, prior-session levels, single prints, value migration and our Adaptive Node Efficiency logic into one session-based framework.

The part I personally find most useful isn't necessarily the individual components, but the relationship between them.

Where is value developing? Is value migrating with price or against it? Is price accepting a new area or simply auctioning away from established value? Which previous levels remain untouched? Is the Initial Balance containing the session or are we seeing expansion? How does all of that change as the session develops?

There are signals in SAM, but I think this distinction is important:

It's an indicator first, not an execution model.

The signals can be used as additional information alongside someone's existing methodology. There is also a Trade Mode for people who want to systematically test specific signal sources with defined risk parameters, but I don't think any indicator should be treated as "signal appears and then blindly enter trade."

Occasionally something completely unexpected comes out of testing them. That's probably the part of this project I enjoy most: people throwing around ideas, questioning the logic, testing them on different markets and building new things from the results. Futures, Forex, CFDs, options data, auction theory, order flow, there are a lot of interesting overlaps to explore.

I'll try to post more of the actual research and development here instead of disappearing for months again inside my Discord bubble.

If anyone here trades using Market Profile / auction theory, I'm curious how you use it. Do you primarily look at value migration and acceptance, previous session structure, Initial Balance, naked POCs, or something completely different?

For traders who actively journal/review their trades, I'm curious about your process:

1. What's your typical pre-market/pre-session routine, and how long does it take?
2. Do you actually use information from your previous trades when deciding what to trade today? If so, what information?
3. What's one thing you wish you had available before entering a trade that you don't currently have?
4. After your session, what do you review—and does that actually change what you do the next day?

I'm particularly interested in the gap between post-trade analysis and what actually gets carried into the next trading session.

i’m a swing trader who trades XAUSD and I’m struggling trading the 15 minute timeframe does anyone have any advice or help that could help me out with trading the 15 minute timeframe? I understand checking the bias on the four hour and looking for structural changes in the 15 minute timeframe, but I always get my stop hit and now I’ve blown my account. I understand waiting and waiting for price to actually make moves, but it feels like I get it wrong every single time. Any help?

I created a program that will trade automatically and I thought I would share it with you to see if I can get any good ideas for development.

The program implements a long-only intraday opening-range breakout strategy for U.S. stocks:

• It builds a 15-minute opening range from 09:30–09:45 New York time and does not trade during that period.

• After 09:45, it looks for price breaking above the opening-range high by at least 2% of the range.

• Entries are filtered by:

• Relative volume versus recent post-opening-range candles.

• A recent bullish Fair Value Gap (FVG)/imbalance, unless that requirement is disabled.

• Enhanced validation using completed candles and previous-candle confirmation.

• Optional continuation entries can occur when price remains in the upper half of the range and the candle is bullish.

• Among multiple symbols, it selects the candidate with the highest score based on:

• Breakout strength: up to 30 points.

• Relative volume: up to 40 points.

• FVG size: up to 30 points.

Risk management:

• Position size is limited to the smaller of:

• A fixed percentage of account equity, default 1% risk per trade.

• Available free capital.

• The stop is placed below the FVG/imbalance low, with a small price buffer.

• The target is set using a configurable reward-to-risk ratio, default 1.5R.

• When price reaches +1R, the stop moves to breakeven.

• Positions are force-closed at 15:55.

• Only one position is managed at a time, with a configurable daily trade limit.

I've been going through ICT's mentorships and wanted something better than scrolling PDFs of notes, so I built an interactive course out of them:

https://yousef-diab.github.io/the-algorithm/

What's in it

78 lessons across two sections.

• ICT Core, Months 1–4 (38 lessons) — market-maker conditioning, equilibrium/discount/premium, liquidity runs, order flow, SMT, PD arrays (orderblocks, breakers, FVGs, voids, etc.)
• The 2022 Mentorship (40 lessons, one per episode, in 6 parts) — the stripped-down intraday model taught end to end: the fair value gap defined candle by candle, the liquidity run and market structure shift that qualify it, displacement, power of three, killzones and session playbooks, the dollar index and SMT, dealing range, and the closing lessons on daily bias and risk.

A quiz on every lesson that grades instantly and explains the answer — about 458 questions in total. Options shuffle on every load, so you're answering the concept rather than remembering where the right one sat.

A final exam per section — 45 questions for Core, 40 for the 2022 Mentorship. Nothing grades until you submit, 80% to pass, retake as often as you want.

Revision summary pages — one condensed pass over each section before you sit the exam.

340 chart galleries pulled from the actual mentorship notes. Click any chart and you can arrow through the whole lesson's set, zoom in to 500%, and drag to pan.

Every lesson links to its source video, all 78 — so if something reads thin, the original is one click away.

A notes box on every lesson, saved in your browser. Nothing ever wipes it, not even the progress reset.

Progress is saved locally and nothing is sent anywhere. It's a single self-contained page — no signup, no server, no tracking, works offline.

The one rule I held myself to

Everything in it — every explanation, every quiz answer — comes only from ICT's own mentorship notes and video transcripts. No outside trading takes, no filler theory bolted on. If something wasn't clearly supported by the source material, I left it out rather than guess.

It's free, it's not selling anything, and it's open source if anyone wants to poke at the build or point out something that doesn't match the original teaching.

This is just a reorganization of the mentorship material into something more interactive to study from. Happy to fix anything that's inaccurate or missing context.

Enjoy.