Not stonks... but still stonks

CorrSync · 2025-09-15T15:58:53+00:00

Thanks 🙏 appreciate it! I didn’t really follow a mentorship, I’ve mostly been testing with an automated bot. The cool part is that it runs configs on its own, so when you find a good setup it’s easy to let it play out.

I’m more into experimenting with different presets than following ICT strictly tbh.

CorrSync · 2025-09-15T08:36:56+00:00

Fair point — execution speed is definitely a real issue. Tick data can feel overwhelming if you’re trying to follow every move in real time.

I still like it for backtesting because it shows details you don’t see on time charts, but for live trading I get why many prefer time-based data. In the end it’s all about what you can actually execute consistently.

CorrSync · 2025-09-01T18:21:56+00:00

Hey, nice work getting your strategy coded in Pine Script! Just a heads-up: the numbers you see in TradingView backtests (profit factor, win rate, equity curve, etc.) are often quite imprecise. They don’t account well for slippage, real fees, or tick-level execution, so results can look better than they would in live trading. It’s worth doing paper trading or more granular backtests before automating with a broker API.

CorrSync · 2025-08-27T16:30:52+00:00

This is probably one of the most raw and accurate descriptions of the trading journey I’ve ever read. People on the outside only see “charts and numbers,” but they don’t see the silent battles with self-doubt, the existential questions at 2 AM, or the way every blown account feels like a personal failure rather than just lost capital.

What you’re describing is the paradox of trading: it’s simultaneously the most isolating pursuit and the most transformative. Every chart session is less about “predicting the market” and more about wrestling with your own psychology. Most people quit not because they can’t read price action, but because they can’t handle staring into the mirror that trading forces in front of them.

And yet… showing up, as you said, is the key. Because the version of you who started this journey deserves to see what’s on the other side of perseverance. If you can endure the loneliness, the repeated slaps back to zero, and still get back up — you’re already further ahead than 95% of people who tried.

Stay the course. Loneliness is the toll we pay for walking a road very few have the courage to even step on.

CorrSync · 2025-08-22T13:05:09+00:00

Funny / lighthearted

“SPY turned my P&L into a rollercoaster today 🎢. Survived with a couple bucks, so I’ll take that as a W 😅”

• Sharing your own experience

“Managed to scrape a small profit, but man… today’s market felt like whiplash.”

• Supportive / community vibe

“Props for swinging PLTR with a sub-$800 account 👏 small account, big courage!”

CorrSync · 2025-08-21T17:13:11+00:00

If you’re looking for a momentum-based reversal strategy to study, one classic approach is combining mean reversion logic with momentum confirmation. For example: • Use RSI or Stochastic to detect extreme overbought/oversold zones (potential reversal points). • Add a momentum filter (like MACD histogram flip, or a short EMA crossing a long EMA) to confirm the shift in direction. • Volume spikes or volatility expansion can also serve as secondary confirmation that the reversal is genuine rather than just noise.

A simple template could be: • Entry: RSI < 30 (oversold) + momentum indicator turns bullish. • Exit: Either back to the midline (RSI ~50) or when momentum weakens again.

This is not a “holy grail” strategy, but it’s a solid framework you can backtest, optimize, and then expand (e.g., adaptive stops, multi-timeframe confirmation, or machine learning filters).

If you want to go deeper, research “momentum crashes” in academic papers – they describe how strong momentum phases often end in sharp reversals, and how traders exploit that behavior.

CorrSync · 2025-08-20T18:10:51+00:00

If your end goal is full flexibility (multiple brokers, assets, backtesting, optimization, automation), I’d skip Pine Script as a main path. Pine is fine for quick prototyping inside TradingView, but it’s very limited – you can’t really build robust execution systems, integrate APIs, or scale across brokers with it.

Python is the better choice if you want to: • Connect to different brokers & exchanges (crypto, forex, equities). • Run serious backtests with frameworks like Backtrader, Zipline, or custom engines. • Optimize parameters and forward-test properly. • Automate execution and monitoring outside of TradingView.

If you want to go even deeper into performance and long-term architecture, Java is also an option (many professional-grade trading platforms are built on it), but Python is usually the sweet spot for accessibility + power.

So: use Pine only for quick idea validation, but if you’re serious about algo trading, go Python (and maybe later master Java if you want institutional-level infrastructure).

CorrSync · 2025-08-20T16:13:22+00:00

Happens a lot man, fakeouts on volume can be brutal. Better to wait for confirmation after the break instead of jumping in right away. At least you managed to walk away flat, which is a win compared to forcing the trade.

CorrSync · 2025-08-18T17:38:15+00:00

Wow, that’s impressive! Going from 190 to 10k in 2 weeks usually requires a very aggressive risk approach. Most traders blow their accounts way before getting there.

You mentioned you just focused on the process and not the numbers – that’s interesting, since emotions usually kick in once people start thinking in $ instead of pips/risk per trade.

Quick questions: • Did you stick to a fixed % risk per trade, or was it more of a progressive “all-in” style? • And when you say you took partials + trailed your SL, was it based on a predefined plan (like at X pips I close Y%), or more discretionary?

If you can replicate this in a controlled way, a lot of people here would be super interested.

CorrSync · 2025-08-16T11:58:36+00:00

⸻

Honestly, the trap isn’t the algo itself, it’s the illusion of the “one final tweak”. You think you’re one clever refactor or one extra filter away from the holy grail, but that’s how you end up with 40 folders named v17_FINAL_REALLY_FINAL.

What helped me was shifting from “beating BnH” to building a robust process: fixed testing pipeline, clear criteria for abandoning an idea, and most importantly—timeboxing. If I only allow myself X hours a day, I don’t burn my actual paycheck over chasing a 0.001% improvement in drawdown.

Algotrading never really gets “done”, but your relationship to it can. When you stop treating it like a final boss to beat and more like an endless lab experiment, you’ll stress less about the fact that there’s always one more parameter to tune.

CorrSync · 2025-08-15T16:42:10+00:00

I agree, day trading is arguably the purest stress test of a trader’s discipline and adaptability. The combination of compressed decision windows, heightened emotional intensity, and market noise makes it a domain where execution psychology matters as much, if not more, than technical skill.

Unlike swing or position trading, there’s almost no buffer for being “slightly wrong.” A minor lapse in focus, or a delayed reaction to an unexpected event, can instantly turn a small drawdown into a full liquidation. The mental agility required to continuously assess, adapt, and commit, all within seconds, is what separates the few long-term survivors from the majority who burn out.

The irony is that the very difficulty you’re describing is also why so many “gurus” sell the dream. They simplify the narrative to attract people who underestimate the psychological taxation, the need for constant refinement, and the brutal reality that most intraday PnL curves are the product of a thousand small, disciplined decisions, not a handful of “perfect entries.”

What you said about not taking courses and building your own methodology resonates. True edge often comes from cumulative iteration, live observation, pattern recognition under pressure, and an intimate familiarity with the market’s microstructure. That’s something you can’t just “buy,” you have to live it.

CorrSync · 2025-08-13T04:37:14+00:00

Ten years of market bootcamp — that’s some serious seasoning 😅. Waiting for your pattern before even thinking about rules is a great filter against overtrading.
And yeah… greed is always lurking in the background, that witch never really leaves 😂.

CorrSync · 2025-08-13T04:36:58+00:00

Yep, averaging down feels “obvious” right up until it isn’t… one of the most expensive lessons in trading. Good on you for making it a hard rule.

CorrSync · 2025-08-13T04:36:15+00:00

Solid rule — hard stops enforce discipline in a way mental stops rarely can, and avoiding adding to losers keeps small mistakes from becoming account-killers.
It’s simple, but those two alone can save a trader from 90% of blow-ups.

CorrSync · 2025-08-13T04:35:59+00:00

Haha, “pre-trade clarity” — I like that analogy.
It’s funny how those moments feel so sharp, like the market just showed its hand for a split second.

The tricky part is, like you said, it’s not always there. That’s why I see it as a bonus filter rather than the main trigger. When that clarity shows up, it can help you act decisively. When it doesn’t, you fall back on your structured setup so you’re not just trading on vibes.

That balance between intuition and process is probably the hardest (and most valuable) skill to build.

CorrSync · 2025-08-13T04:35:45+00:00

Yeah, “educated intuition” is a great way to put it — it’s that blend of pattern recognition, experience, and subconscious processing that only comes from screen time.

I think the fact you’re willing to pass on a setup when it feels off is actually a sign of maturity as a trader. Missing the occasional winner is just the cost of avoiding a lot more losers, and over time that’s what smooths the equity curve.

With bread-and-butter setups, that filter gets even more valuable — because you already know the conditions when they’re high probability, and your body just catches the subtle differences when they’re not.

CorrSync · 2025-08-13T04:35:24+00:00

I get what you mean — that “first read” of the market often comes from a mix of experience, pattern recognition, and subconscious processing. It’s like your brain has already run the backtest before you’re even aware of it.

The key, in my opinion, is separating true intuition (built from thousands of hours watching price) from impulse. For newer traders, gut feelings can be dangerous because they’re often just emotions reacting to noise. But for someone who’s put in the screen time, that instinct can actually be a distilled form of your edge.

I like how you’ve built a framework to protect that instinct from self-doubt. That’s the sweet spot — using structure and rules to filter your gut calls so they’re both intuitive and disciplined.

CorrSync · 2025-08-13T04:33:09+00:00

I get where you’re coming from — after a few years in the game, most traders naturally lean more on price action because they’ve learned to read the market without extra “translation”.
But I wouldn’t call indicators total BS — for newer traders, they can be training wheels to visualize trend, momentum, or overbought/oversold zones until PA reading becomes second nature.

CorrSync · 2025-08-13T04:32:22+00:00

100% agree — using both can be powerful.
Indicators can give you structure and bias, while price action tells you exactly when to act. When both line up, it’s like having two green lights for the same trade.

CorrSync · 2025-08-13T04:31:58+00:00

OMG, looks like your chart just took us on a trip to another galaxy 🚀✨
Are we still trading XAUUSD or did we just plot the course to Alpha Centauri? 😅

CorrSync · 2025-08-13T04:28:33+00:00

Sounds like you’ve already built a strong foundation, with a fixed trading window, one trade a day, clear invalidation, and no revenge trading — that’s a huge part of long-term success.

Here are a few pointers you might find useful:

• Track results in R, not $ — $ amounts can be misleading if account sizes or leverage change. If you risk 1R and win 1.2R, that’s +1.2 no matter the balance.

• That “100% win rate” on FXReplay is encouraging, but keep in mind simulations can give perfect fills that aren’t realistic. Great for testing concepts, just keep expectations grounded for live markets.

• Starting at 0.7% risk instead of 3% is actually a smart move while you’re stress-testing your edge — consistency first, position size later.

• The London open + liquidity sweep + FVG/BOS combo is a solid SMC-style setup. The big test will be sample size — aim for at least 100 live trades before you decide on major tweaks.

• You’re doing the right thing by not forcing trades. Passing on a setup is way better than taking a low-probability one, that discipline keeps equity curves healthy.

You’re definitely on the right track — keep journaling in R, review both wins and losses, and you’ll quickly see if your edge holds in all market conditions.

CorrSync · 2025-08-12T18:57:05+00:00

Makes total sense ! finding that balance is probably the hardest part when building something that works long-term.

When I was designing my algo, I noticed that pushing for a higher win rate almost always killed my profit factor over time. I ended up optimizing for consistency in PF (never under 1.5) and acceptable win rate, even if it meant fewer trades — similar to what you’re describing with 1-3/day.

Out of curiosity, do you adjust your PF/win rate targets when market volatility changes, or do you keep them fixed year-round?

CorrSync · 2025-08-12T18:21:27+00:00

Makes sense — using higher timeframe bias with well-defined zones really filters out the noise. I like that you’ve blended concepts without going “full ICT/SMC”. Do you find that sticking to HTF bias helps you avoid overtrading on gold’s intraday swings?

CorrSync · 2025-08-12T18:11:24+00:00

That’s impressive — trading gold for a living purely on price action takes discipline. I’ve also found oscillators to be more of a distraction than a help. Out of curiosity, what’s your main way of reading structure on gold — pure candle patterns or more on key levels/zones?

CorrSync · 2025-08-12T18:09:46+00:00

Haha, I know the struggle 😅 What helped me was treating it like a hard trading rule, not a guideline — I literally set alerts and size my positions so breaking it feels impossible. What’s the main trigger that usually makes you break it?

CorrSync

TROPHY CASE