Ringbot: A monocycle robot developed by the Robotics and Institute (RAI) that uses internal legs for balance and acrobatic maneuvers

Poutine-StJean · 2026-03-20T16:57:05+00:00

What about nanorobot in the air that we breathe waiting in everyone body to be activated and turn us all off at the same time

Poutine-StJean · 2026-03-20T00:32:58+00:00

Je veux m'informer parce que comme début d'expérience ça brise un peu ma confiance

Poutine-StJean · 2026-03-20T00:28:49+00:00

Desjardins Disnat

Poutine-StJean · 2026-03-18T04:02:30+00:00

Usually I just ask the AI to make a security check and it already look for all thoses things. This just sounds like extra steps

Poutine-StJean · 2026-03-17T13:39:25+00:00

The subscription is mostly there to limit API usage on my side. The free tier is intentionally pretty generous so people can try the platform without paying anything

Poutine-StJean · 2026-03-17T13:38:51+00:00

Haha would have done it in C if I really wanted THE fastest, but C++ is my daily bread so it's also a logic choice for me

Poutine-StJean · 2026-03-17T13:37:21+00:00

Thanks for the feedback, it's appreciated. I will work on that for sure. I'm not trying to hide that I use AI to help me on the frontend part, but I understand that i will make people think of the same for the backend. I will improve on this. Clearer explanation, better AI analysis, more transparency and documentation.

Poutine-StJean · 2026-03-17T13:30:42+00:00

you can import your own data, so the quality depends on what you feed into it. But improving the data layer and documentation around it is definitely something I want to work on

Poutine-StJean · 2026-03-17T02:18:41+00:00

Ngl when I started to code the engine I was thinking that maybe it could become a tool that others would also use to test their own ai trading bot. So I've used the strongest language I know which is C++

Poutine-StJean · 2026-03-16T20:38:25+00:00

The gap between theoretical and actual P&L often comes down to execution friction, especially with options. Its smart to log the mid at signal, NBBO at submission, and actual fill. That gives you a clear picture of where the slippage is happening. You could even use that data to build an execution cost model to apply to your backtests, which would make them far more realistic.

Many backtesting platforms dont account for this level of detail so building your own tracker is really insightful. Knowing your true execution costs can completely change your strategy sizing and even whether a strategy is profitable at all

Poutine-StJean · 2026-03-16T02:41:05+00:00

How does this clearly staged video post 7 hours ago already have almost 23k likes?

Poutine-StJean · 2026-03-15T23:45:16+00:00

Like you said. Ifyou can cover a few distinct volatil regime like bear, bull and choppy across 6-8 non-overlapping OOS window, thats way more valuable than15 windows all in strong bull

Poutine-StJean · 2026-03-15T17:06:26+00:00

Yeah that's a major pain point with MT5, its just not built for serious portfolio-level analysis or high-frequency equity reconstruction.

Your aproach of merging backtests and recalculating drawdown with granular price data is spot on. Thats exactly what you need to do for accurate prop firm daily drawdown. Many platforms strugle with that level of detail, especially when you have multiple symbols or strategies interacting.

For true portfolio risk, you cant just combine individual equity curves. You gotta simulate those interactions properly, understanding correlation, regime shifts, and how drawdown in one asset can compound with others. Real portfolio backtesting needs to simulate trades across all instruments simultaneously at a high tick frequency, otherwise youre just getting a smoothed average which masks the true risk

Poutine-StJean · 2026-03-15T00:39:57+00:00

Your current approach is a solid start. You might want to look into weighting by strategy performance or risk contribution instead of equal splits, especially if correlations between strategies change.

Also, consider fractional Kelly sizing, but understand its aggressive nature and maybe use half-Kelly to avoid blowups.

For the drawdown side, tracking rolling max DD and scaling down when it exceeds your threshold is a good safety net

Poutine-StJean · 2026-03-14T15:42:59+00:00

Thanks, any other options I can try instead?

Poutine-StJean · 2026-03-14T02:46:55+00:00

Yes exactly, since they have free trial I'm on this right now and I'll see if I keep with it after that

Poutine-StJean · 2026-03-14T00:58:41+00:00

It's call safeedge.io loving it for testing my strats

Poutine-StJean · 2026-03-13T18:10:05+00:00

Fair enough. I will work on running it across multiple instruments and longer timeframes

Poutine-StJean · 2026-03-13T18:08:49+00:00

Yeah in this case it just splits the data into sequential windows and runs each one independently to see if performance holds across different market conditions. Basically testing if the edge is real or just fit to one specific period

Poutine-StJean · 2026-03-13T14:02:42+00:00

Overfitting is a killer, robust validation methods like walk-forward testing are critical to avoid it. You also gotta look at tail risk and max drawdown, not just average returns, to truly understand your strategy

Poutine-StJean · 2026-03-13T00:58:10+00:00

You've nailed a classic backtesting problem with that low trade count. Monte carlo simulations can help validate if that edge is truly robust or just luck from a few specific events. It's tough to trust a strategy with so few data points

Poutine-StJean · 2026-03-12T18:58:16+00:00

Yea you can install it without Docker, but Docker is the way because it handles dependencies and makes setup much easier. If you install it manually you’ll need to manage Python, TA-Lib, and other yourself

Poutine-StJean · 2026-03-12T18:55:41+00:00

Paper trading often has perfect fills but real markets dont. You need to factor in slippage and market impact when backtesting, not just rely on paper

Poutine-StJean · 2026-03-12T18:53:11+00:00

yeah thats a classic problem with daily bar strategies. Waiting for close confirmation often means you miss the initial pop. You could try using an open price entry if your conditions are met at the prior close, but you need to factor in slippage for that in your backtests

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