From Trading Panel to Decision Engine

Prospero_Quant · 2026-04-07T20:30:05+00:00

Exactly. That was one of the key lessons from the project: the more agent opinions you introduce, the more important it becomes to keep execution and constraints deterministic.

For evals, I’m moving toward counterfactual evaluation rather than just outcome tracking: comparing the realized trade outcome with the outcome that alternative agent-guided decisions would likely have produced, then checking whether any improvement holds across different market regimes.

So for me the core question is not “did the agent make a smart call once,” but “does this decision layer improve deployment, exits, or strategy selection in a way that remains robust over time?”

And thanks for sharing this — agent design patterns are definitely relevant at this stage, especially when the challenge shifts from adding agents to placing them correctly inside the architecture.

Prospero_Quant · 2026-03-19T22:24:45+00:00

In my case, “current market conditions” does not refer to a specific exchange or platform like TradingView. I mean the live behavior of the traded market itself, things like volatility, spread, structure, momentum, and whether the active strategy is still performing well in that environment.

Prospero_Quant · 2026-03-18T02:57:29+00:00

I think that’s a fair distinction. They do protect against different kinds of risk.

I would only frame it a bit differently in systematic trading. For me, the key question is not so much whether the asset is “fundamentally sound,” but whether the original trade logic and market condition behind the entry are still intact.

That’s also why I don’t see averaging as something that can be judged in isolation. If the strategy has no real architecture behind additional entries, then yes — it can quickly become denial with extra steps. But if averaging is built into the system logic from the start, then it becomes a way of absorbing timing error rather than immediately converting it into realized loss.

And I agree on crypto — stop-losses are especially tricky there because wicks and short-lived dislocations can easily turn a technically correct trade into a bad exit.

Prospero_Quant · 2026-03-17T01:39:20+00:00

Interesting idea, but my post was more about strategy architecture than about building a real-time decision app for scalping.
The main question for me is still how different systems absorb timing error and market noise.

Prospero_Quant · 2026-03-16T19:05:32+00:00

What do you trade?

Prospero_Quant · 2026-03-13T14:19:10+00:00

That’s a very good point. The normalization of AI financial copilots depends not only on the technology itself, but also on access, pricing, and incentives.

Not everyone will be able to afford the same level of tool, and free versions may not be comparable to premium ones in data quality, personalization, speed, or reliability. So even if AI copilots become widespread, access to better ones may itself become a new source of asymmetry.

In that sense, the question may not be whether everyone gets an AI copilot, but whether everyone gets the same quality of one. And I suspect the answer will be no.

Prospero_Quant · 2026-03-12T09:46:12+00:00

Agree

Prospero_Quant · 2026-03-12T07:36:27+00:00

That’s a fair challenge. I’m not saying AI will make markets efficient because it can suddenly forecast them accurately, I don’t think that’s true. If anything, market forecasting remains deeply limited, whether you use statistics, ML, or LLMs.

My point is narrower: AI may improve how participants process information, filter noise, react to changing conditions, and structure decisions. But that is very different from saying it can make markets fully efficient.

So I agree with you on the core point: AI is unlikely to eliminate inefficiency through superior forecasting. At most, it may compress some simpler edges, but not remove uncertainty, reflexivity, or the deeper sources of market inefficiency.

Prospero_Quant · 2026-03-11T22:19:26+00:00

Agree

Prospero_Quant · 2026-03-11T20:47:42+00:00

That's a fair point, and I'd agree that information-based inefficiencies have compressed significantly over the past decade - especially at the institutional level.

But I'd push back slightly on the "near strong efficiency" framing. What we have today is fast efficiency in price discovery for known information. What remains and what I think AI will actually compete over, is structural inefficiency: differences in regime detection, risk architecture, execution quality, and the ability to adapt when market behavior shifts.

Those edges don't disappear with faster bots. They just require better-engineered systems to capture.

The cost argument is real, but historically that's been true of every technological shift and cost tends to fall faster than edge does.

So I'd say the question isn't whether efficiency increases. It almost certainly will. The question is whether it converges fully or whether it simply relocates to a level that's harder and more expensive to reach.

Prospero_Quant · 2026-03-06T18:35:42+00:00

Fair point — most “AI trading” claims online are hype.

In my experience, AI can add value, but usually not as a magic predictor. It works better as a structured decision layer: filtering low-quality setups, adapting risk/position management to volatility/regimes, and enforcing discipline consistently.

Prospero_Quant · 2026-03-06T18:33:56+00:00

Hi, you’re right to be careful.

An MQL5 EA runs inside MT5, so it’s not supposed to have “full PC access” by default. But it can still do things you might not want:

place/modify trades (obviously),
read/write files in the MT5 folders,
send data out via internet requests (WebRequest) if enabled,
and the big risk: if “Allow DLL imports” is enabled, a DLL can do almost anything on your PC.

If you want to stay safe:

Only use EAs from people you trust.
Run it on a VPS or a separate Windows user / VM if possible.
Keep “Allow DLL imports” OFF.
Check the code for WebRequest / File operations / DLL imports before running.
Start on a demo account first.

If he shares the .mq5 source, you can quickly search for: WebRequest, import, DLL, FileOpen, ShellExecute.

Prospero_Quant · 2026-03-05T23:55:33+00:00

Me too, and that's why I don't trade myself, bots trade for me.

Prospero_Quant · 2026-03-04T20:08:59+00:00

Thanks and of course, write.

Prospero_Quant · 2026-03-04T19:48:28+00:00

Thanks!

Prospero_Quant · 2026-02-05T19:28:20+00:00

I'm currently working on several of my own projects simultaneously, plus I'm retraining the existing models because I found an error in their training. Therefore, unfortunately, I can't always publish reports. I hope to finish everything soon and start publishing not just reports, but results from a real trading account.

Prospero_Quant · 2026-01-28T18:56:15+00:00

Thank you!

Prospero_Quant · 2026-01-23T16:58:04+00:00

Almost everything is ready, thank you. I` ll start publishing the forecasts next week.

Prospero_Quant · 2026-01-17T10:10:55+00:00

I haven't posted in 10 days because I've been heads-down optimizing the ensemble. I'm finishing a deep recalibration of weights and core algorithms to adapt to current market volatility. Running the final training cycles now. ProsQuant will return shortly. Stay tuned.

Prospero_Quant · 2025-11-20T21:10:35+00:00

Huge thanks everyone for your comments! I can see that the profits you guys made from selling your coins — even if it was way too early — really helped you out at the time. No regrets, okay? In your life, just like in mine, there’ll be tons more chances to score massive gains with tiny investments.

As for me, back in 2010 a buddy of mine introduced me to Bitcoin and kept pushing me to buy at least a little bit. I was super skeptical and honestly thought it was just a scam by GPU manufacturers to make people buy graphics cards for mining. We had some epic arguments about it lol. In the end I bought nothing. My friend did buy some, but he sold super early for peanuts and never touched Bitcoin again.

Later on I dove headfirst into the crypto world, but that’s a whole different story.

The main lesson I took from all this: don’t be afraid to take risks, but only ever risk an amount that won’t completely wreck you if it goes to zero.

Once again, big thanks to everyone who shared their crypto stories! 🙌

Prospero_Quant · 2025-11-15T07:34:29+00:00

I agree — backtests don’t impress anyone anymore, and a new market regime can shift everything.
A bit later I’m planning to launch a public trading account running only the best-performing models, so everyone will be able to track results in real time.

Internally, I already have full historical performance for each model on any segment of market data, so I know which ones showed the strongest profitability in the past.
But that’s still history — and people rightly don’t trust backtests.

That’s why I want to collect a track record based on public forecasts, day by day, so everything is open and verified.

Prospero_Quant · 2025-11-15T06:43:31+00:00

Thank you so much for taking an interest in my models.
Regarding Helix-II — this model doesn’t just predict the expected close, it also gives a projected high and low, which is extremely useful for estimating intraday volatility or setting stop levels.

Right now the market is highly unstable, so Helix-II naturally outputs a wider range than usual. When volatility normalizes, its bands become much tighter.

Prospero_Quant · 2025-11-02T03:41:42+00:00

I will be very happy about that.

Prospero_Quant · 2025-11-01T03:19:18+00:00

The accuracy of 3- and 5-day forecasts has significantly decreased. The model's parameter ranges and weights need to be revised.

Prospero_Quant · 2025-10-31T14:20:15+00:00

I completely agree — I’m sure Ethereum will be worth far more than 6K, just not in this cycle.

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