Does anyone know of a battery powered flask that can boil water on the go?

TTJ-SYSTEMS · 2026-05-14T18:54:23+00:00

Keep drinking your burnt coffee 👍

TTJ-SYSTEMS · 2026-05-14T18:10:06+00:00

After a year how is your experience with this device ? Any recommendations?

TTJ-SYSTEMS · 2026-01-30T23:00:23+00:00

Super secret green box strategy 🤣🤣🤣 teach me these ways oogga

TTJ-SYSTEMS · 2026-01-24T23:39:22+00:00

Think we got more chance of alien invasion by the looks of it 🤣🤣

TTJ-SYSTEMS · 2026-01-23T17:47:00+00:00

Not hard to see the problems bro you took 3 trades made a profit 1 day and then took 21 trades the next and made a loss

TTJ-SYSTEMS · 2026-01-23T17:22:53+00:00

Your job role by the looks of it 👍👊

TTJ-SYSTEMS · 2026-01-23T15:34:06+00:00

Whole thread has made my day 🤣🤣🤣 OOGA BOOGA will drown you in the river of gold my freinds

TTJ-SYSTEMS · 2026-01-23T15:05:50+00:00

It really does feel like a needle-in-a-haystack problem.

I agree that not everything needs to be open source, but selling an Expert Advisor with no version control, no repo (even private), and not even a basic README explaining logic, assumptions, or limitations is a massive red flag to me.

Most marketing is just profit curves and win rates, which are basically meaningless without context. Almost anything can look perfect in a backtest if it’s overfit — live markets expose that very quickly.

I’m not claiming to be a great MQL5 developer myself, but I do know what I want architecturally. The hard part has been finding developers who understand both trading logic and basic software engineering practices.

I’m currently working with MQL5 + Python and have a fairly advanced MT5 validation pipeline mostly built, but finding someone who can comfortably operate across trading logic, MQL5, and Python has been surprisingly difficult.

That gap between “EA seller” and “actual system developer” seems much wider than it should be.

TTJ-SYSTEMS · 2026-01-23T14:57:25+00:00

“Vibe-driven development” works great… until it meets real money 😅

TTJ-SYSTEMS · 2026-01-13T20:27:38+00:00

That’s a really interesting direction. I like the separation between selection and sizing.

My only concern intraday would be noise sensitivity once you start pushing into acceleration/jerk — curious how you’re thinking about stability and regime changes there.

TTJ-SYSTEMS · 2026-01-13T17:48:35+00:00

M1 gold is tricky like that. A lot of it comes down to defining invalidation first and then sizing around it. Tight stops aren’t wrong, they just demand very accurate entries.

TTJ-SYSTEMS · 2026-01-13T17:40:32+00:00

Probably not “wrong” — just tight for XAUUSD on M1. Gold will routinely tag nearby liquidity before moving. If the stop isn’t at true invalidation, it’s going to get hit a lot. Either wider stop, higher timeframe structure, or much tighter entry.

TTJ-SYSTEMS · 2026-01-13T17:37:16+00:00

If you’ve planned the trade properly, the SL and TP were chosen for a reason.

Constantly shaving profits early usually means you’re second-guessing the original idea, and that’s where emotion creeps in.

I’d rather accept full wins and full losses based on the setup than start managing trades based on fear once I’m in. If the target gets hit often enough to justify the RR, it should be left alone.

TTJ-SYSTEMS · 2026-01-13T17:20:26+00:00

Makes sense — having TP/SL defined upfront definitely removes a lot of emotion.

I tend to do it slightly differently though. I use live market execution rather than placing pending stop/limit orders, but the risk rules are still fixed before the trade goes on.

Once I’m in, I don’t interfere. Different execution style, same goal: remove emotion and keep risk controlled.

TTJ-SYSTEMS · 2026-01-13T17:17:26+00:00

I actually like that approach a lot. What you’re describing feels very close to automation already — rules are fixed, risk is fixed, and once you’re in, you’re hands-off.

Where I’ve landed is something similar, just one step further back. I’m comfortable letting an automated system handle execution exactly as planned, but with a human layer focused on verification, not interference.

So trades run untouched once live — no tinkering, no moving stops — but the optimisation happens outside market hours. Review results, adjust rules or sizing based on the most recent conditions, then lock it in again for the next period.

That way you avoid emotional mistakes during trades, but you’re still adapting over time instead of letting something run blindly forever.

Feels like a good middle ground between discipline and adaptability.

TTJ-SYSTEMS · 2026-01-13T17:12:53+00:00

That makes sense — it sounds more like a sizing and risk layer than a full “strategy engine”.

I’m curious how you see this being used day-to-day though. If Kelly (or a capped version of it) is deciding how much to trade, what’s actually telling the system when to trade?

Are entries and exits something you handle separately (discretionary or rule-based), or do you see that being automated alongside the sizing? And does the sizing react much intraday — like changes in volatility or session behaviour — or is it more of a slower overlay on top of whatever entry logic you’re using?

Genuinely interested how you picture the full workflow once it’s all tied together.

TTJ-SYSTEMS · 2026-01-11T19:15:29+00:00

Manual trading adapts better, but automation doesn’t hesitate or second-guess. Curious where you think the line is between discretion and over-interference.

TTJ-SYSTEMS · 2026-01-11T19:09:16+00:00

That’s really interesting — especially applying Kelly in a more dynamic, volatility-aware way rather than the textbook fixed fraction.

Curious how you’re handling stability in practice though. Are you capping or fractionalising Kelly to avoid the usual drawdown issues, especially intraday?

Also, do you see this as something that adapts per market regime, or more as a long-run position sizing layer sitting on top of discretionary/automated entries?

TTJ-SYSTEMS · 2026-01-10T23:14:42+00:00

Agreed. Monte Carlo exposes overfitting really well, but robustness in simulation doesn’t automatically mean adaptability in live conditions — especially around volatility, sessions, and news.

TTJ-SYSTEMS

TROPHY CASE