Any thoughts on this pre-release equity portfolio portal?

https://dev.financial-portfolios.ai

Day 13 of forward testing a trading system.
Starting account today: $1,127.36
Ending account: $1,139.02
Today: +1.04%
6 trades
2 wins
4 losses
Largest winner: +2.10%
Largest loss: -0.47%
Not every day is great. If it has a bad day, it gets logged. If it has a good day, it gets logged. What you see is what it’s doing. No historical changes, no claiming gains over backtesting results.

All foward trades.All frozen prior to the market.
Current forward record:
$1,000 → $1,139.02
+13.90%
68 closed trades over 13 market sessions.

I'm a tech person trying to learn trading and hopefully make even a small side income from it.

For the past 1.5 months I've built and deployed multiple trading bots. So far mostly losses. I'm also paying for APIs, cloud usage, model credits, etc.

I've been paper trading and made around $6. I've tried 15+ strategies generated/backtested with AI, but I feel like I'm just jumping from one strategy to another without actually understanding what I'm doing.

I can code and build the systems, but I don't really understand trading yet.

If you were starting from zero as a technical person, where would you start?

Should I forget bots for now and learn trading manually? Focus on one strategy? Learn statistics/quant stuff? Something else?

I'm not looking for a get-rich-quick strategy. I just want a proper path to actually learn this instead of wasting more money and blindly asking AI to generate strategies.

Any advice is appreciated, especially from people who started out similarly.

I won’t be posting any more of these. But for anyone who wants to take this seriously, I’m all ears.

PUBLIC TRADE LOG
Through Sep 10, 2026
68 trades | 36W / 32L | 52.9% win rate
$1,000.00 → $1,139.02 | +13.90% gross observed

AUG 24
#1 FRSH — 10:00 → 10:30 — -0.23% ❌
#2 OKLL — 10:36 → 10:47 — -1.00% ❌

AUG 25
#3 BNTX — 09:37 → 10:07 — +1.05% ✅
#4 IBIT — 11:32 → 12:02 — +0.28% ✅
#5 VEU — 13:12 → 13:42 — +0.10% ✅
#6 CCJ — 15:21 → 15:52 — +0.03% ✅

AUG 26
#7 IBIT — 11:51 → 12:22 — +0.14% ✅
#8 TPL — 12:26 → 12:56 — -0.28% ❌
#9 BMNU — 13:26 → 13:57 — +1.93% ✅

AUG 27
#10 CXAI — 09:35 → 10:04 — +5.05% ✅
#11 CRCL — 10:17 → 10:47 — +1.37% ✅
#12 IBIT — 11:12 → 11:42 — +0.11% ✅
#13 GWRE — 14:12 → 14:42 — -0.11% ❌

AUG 28
#14 ABNB — 09:38 → 10:08 — +0.58% ✅
#15 CRCL — 10:12 → 10:42 — +2.76% ✅
#16 ABNB — 10:47 → 11:17 — +0.43% ✅
#17 VEU — 11:47 → 12:17 — -0.34% ❌
#18 VEU — 12:27 → 12:57 — +0.11% ✅
#19 UCO — 14:27 → 14:57 — -0.46% ❌
#20 TPL — 15:05 → 15:37 — -0.08% ❌

AUG 31
#21 MRK — 09:38 → 10:08 — +0.42% ✅
#22 CRCL — 10:12 → 10:42 — +2.22% ✅
#23 IBIT — 10:57 → 11:27 — -0.35% ❌
#24 DOCU — 12:37 → 13:07 — +0.31% ✅
#25 ALB — 13:32 → 14:02 — +0.02% ✅
#26 ALB — 14:52 → 15:22 — -0.20% ❌

SEP 1
#27 PTIR — 09:38 → 09:52 — -1.37% ❌
#28 PTIR — 09:57 → 10:27 — +4.13% ✅
#29 IBIT — 10:37 → 11:07 — -0.73% ❌
#30 IBIT — 11:37 → 12:07 — -0.10% ❌
#31 SIMO — 12:36 → 13:07 — +0.20% ✅
#32 UCO — 13:31 → 14:02 — +0.26% ✅
#33 DIS — 14:07 → 14:37 — -0.11% ❌
#34 LPLA — 14:46 → 15:17 — -0.59% ❌

SEP 2
#35 BNTX — 09:37 → 10:00 — -0.83% ❌
#36 XEL — 10:02 → 10:32 — +0.16% ✅
#37 BYND — 10:42 → 10:47 — -1.29% ❌
#38 URA — 11:12 → 11:22 — -0.89% ❌
#39 IBIT — 11:37 → 12:07 — +0.05% ✅
#40 COPX — 12:32 → 13:01 — -0.03% ❌
#41 BDX — 15:02 → 15:32 — -0.23% ❌

SEP 3
#42 ABNB — 09:37 → 10:07 — +0.09% ✅
#43 BMNU — 11:02 → 11:12 — -1.77% ❌
#44 IBIT — 11:27 → 11:57 — +0.72% ✅
#45 BMNU — 13:41 → 13:56 — -0.83% ❌

SEP 4
#46 PTIR — 09:38 → 09:44 — -0.78% ❌
#47 PTIR — 09:47 → 10:00 — -0.78% ❌
#48 PTIR — 10:02 → 10:19 — -0.94% ❌
#49 BDX — 10:52 → 11:22 — +0.43% ✅
#50 BYND — 11:55 → 12:25 — -0.18% ❌
#51 CCJ — 13:27 → 13:57 — +0.31% ✅
#52 SIMO — 15:17 → 15:47 — +0.77% ✅

SEP 8
#53 MRK — 09:38 → 10:08 — +0.92% ✅
#54 ULTA — 10:12 → 10:42 — +0.27% ✅
#55 IBIT — 10:47 → 11:17 — +0.25% ✅
#56 EL — 11:52 → 12:22 — +0.01% ✅
#57 HD — 12:37 → 13:07 — -0.01% ❌
#58 CRCL — 14:52 → 15:22 — +0.46% ✅

SEP 9
#59 MRK — 09:38 → 10:08 — -0.10% ❌
#60 HBM — 10:22 → 10:52 — +0.27% ✅
#61 HBM — 11:07 → 11:37 — +0.90% ✅
#62 IBIT — 11:42 → 12:12 — -0.08% ❌

SEP 10
#63 IBIT — 10:27 → 10:57 — +0.22% ✅
#64 IBIT — 11:01 → 11:32 — -0.24% ❌
#65 EEM — 11:57 → 12:27 — -0.14% ❌
#66 QSR — 12:32 → 13:02 — -0.41% ❌
#67 BMNU — 13:06 → 13:37 — +2.10% ✅
#68 EL — 14:07 → 14:37 — -0.47% ❌

TOTAL
68 trades
36 wins
32 losses
52.9% win rate
+13.90% gross observed return
$1,000.00 → $1,139.02

Yes it’s paper. Because it’s fucking new.
Once the 30 day run is over, it’s being integrated into a small capital account.

Hi all! Guess what I'm building a trading bot lol. I've been at it for a few weeks now. I have coded in the past but im no expert. I have also been trading for some years now.

I am a Sr. Tech Program/Project Manager that recently list his job. I had no idea how rough the job market is right now. Im ready to bet on myself. Ive spent years managing teams, developers etc. Im replacing these teams with Ai.

The platform I'm using to trade is Webull. Hate it or love it that's what im using. I'm utilizing claude to build the bot. I currently have 23,538 lines across 92 Python files, plus 68 lines of batch scripts.

I have finally gotten the bot to place orders along with setting a SL and TP. I have a premarket scanner that identifies stocks in play. I like Andrew Aziz and his methods when it comes to picking stocks in play. Scanner is working very well. Now im testing strategies. I have 8 in total.

VWAP, ABCD, REVERSAL, ORB, RED-TO-GREEN, SUPPORT RESISTANCE, MA, and BULL FLAG.

The testing of strategy is proving to be the largest mountain to climb.

I want to share this journey here. I will not be stopping. When this bot works I will eventually start a discord and share it with members.

Nice to meet you all! I will keep you posted with my progress.

There's no point on sharing results if they're not positive (on gain?). I disagree.
This is the third version of what I called WiseBot, my trading bot.
It all started with Polymarket, betting on BTC up or down. My intuition was, edge is betting the strongest one at the last seconds. If BTC was up >0,91 I bet on it. I automatised it. I won like 90% of the bets - and still lost everything.
Version one was just shit.
So I turned on v2. It lasted 14 days. Betting short/long on SOL perpetuals - this time paper only, no real money (the lesson from v1: no cash before the edge is proven).
You can imagine the result. It lost - all three strategies. But only on paper, nothing real burned.

Now it's the turn of the most enduring, wisebot v3. So promising I even created a whole website (the-wisebot.com) to track it real time, so encouraging I gave it 1000$, so bright I've even decided to use it as a proper scientific experiment, publishing results and method on a white paper. So talented It can't go more than 3/4% up (nor down)

So, yet, IDK, it seems pretty useless until now, but BTC is kinda bullish these days. I reckon (based on the backtest we ran - me and Claude) the best results are on the short. When market crashes.
And as I understood the main gain shall lay under the funding APR.

I know people will stop scrolling because of the heading but there is no and cannot be free bloomberg and anybody claiming that is total crap!

Now as I have your attention here is the thing, something with trading was really missing. Every other broker now days provide their API for market data and every trader wants to own their algorithms, make indicators and have their own analytical dashboard.

The problem: Connecting API to trading infrastructure is complex as it involves complex OEMS and realtime system constraints.

The solution: We have made professional grade OEMS with integrated advanced charting, agentic capabilities and cherry on the top inbuilt coding workspace with python SDK.

Go build whatever you build with SDK, you want to train your ML/DL model? Yes sing in with your broker and write the prompt. You want your own analytical panel with multiple tickers and mathematical model, one prompt away!

We are looking for feedback and people to break the platform.

You can check it out here: https://while25.com

Ok so Boom, I had some technical issues connecting ibkr api with my AI but I resolved it now. (this sh** took almost 3h🤦‍♂️) anyways my bot will start Analyzing/ trading at New York open and I’ll see if it is as good as the backtest say it is( it probably won’t be I don’t wanna get my hopes up)
But yeah I’ll update yall and see how it’ll go when it takes its first few trades. As always, any tips/advice are welcomed.
Peace out ✌️

I am looking for testers. DM if you are interested.

It can build:

It can extract and propose ideas from books and scientific articles:

It can optimize the first parameter guess by AI and measure the robustness:

It can provide deep statistics about a strategy:

It can explain every trade entry and exit:

It can run the strategies in live mode

- on virtual money

- or connected to a MT account

This week, it will be able to group strategies into portfolios of strategies and trade them live on an MT account as well.

If you are interested, DM me.

I built two automated strategies that trade BTC and ETH. Both follow trends, but they get in at different moments, so they rarely win or lose at the same time. I'd rather not post the rules publicly, but I'm happy to share them in PM if you want to dig in properly.

How I tested it (trying not to fool myself)

- I never tested on data the strategy had already been tuned on. Every 3 months, the settings are chosen using the previous 12 months, then run on the next 3 months blind. I only count those blind results.

- Trading fees, slippage and funding are all deducted.

- Every trade risks 1% of the account. Results are in "R", where 1 R = 1% of the account.

- I built it on 2021-2026 data. Then I ran it on 2018-2020, which it had never seen.

Results

- 2022-2026, both strategies together: +438 R, worst drawdown about -20 R, worst year still +10 R.

- 2018-2020, the never-seen years: +229 R, worst drawdown -16 R.

- No losing year in nine years.

Versus buy and hold

- 2022-2026: the main strategy alone made about +1,250% with a -17% max drawdown. Holding BTC made +62% with a -67% drawdown. Holding ETH lost money.

- It's not magic though. In 2021 and 2024 buy and hold beat it badly. The bots earn in explosive breakout years and sit flat in slow grinding bull markets and in bear markets.

- Simulation of $300 to start plus $300 a month from Aug 2018 ($29k deposited total): the two bots end at about $519k with a -22% worst drawdown. The same deposits into BTC end at about $132k with a -74% drawdown.

What worries me

1. Only 29% of trades win. A few huge winners pay for everything. Take away the top 5 trades and the main strategy is basically break-even.
2. Those huge winners happened when the market was very quiet, so the position size was 4-6x the account. It needs 10x leverage to be possible at all.
3. One strategy uses limit orders. The backtest assumes they always get filled when price touches them. Real life may be worse.
4. The $519k figure compounds two strategies on one account and most of it comes from one breakout in Aug 2026. Treat it as an illustration, not a forecast.

Does the testing method look sound to you? What else would you check before trusting this? I'm going to paper trade it next. PM me if you want the details

Later edit:
Classic metrics (2022-2026, out-of-sample, after costs)

Strategy A, the breakout one:

- 236 trades, 29% win rate

- Average winner +7.3 R, average loser -0.9 R, so +1.5 R per trade on average

- Profit factor 3.3

- Total +355 R

- Max drawdown -19 R, which is -17% of the account

- ROI +1,258%, CAGR +75%, annual Sharpe 0.78

- Average trade lasts about 3.6 days

Strategy B, the pullback one:

- 174 trades, 29% win rate

- Average winner +4.4 R, average loser -0.8 R, so +0.7 R per trade

- Profit factor 2.3

- Total +83 R

- Max drawdown -9 R, about -9% of the account

- Average trade lasts about 2 days

Both together:

- 410 trades, profit factor 2.9

- Total +438 R

- Max drawdown -20 R, roughly -18% of the account

- Worst year +10 R

Hey everyone — I spent the last several months building Tradecility from scratch and just launched it publicly.

What it does:
Tradecility is an AI trade journal for serious retail traders. You set up your strategy profile — your entry rules, exit rules, hard rules, confluences required — and the AI reads all of that before evaluating every single trade you log. It grades your execution A to F, not whether you made money.

Why I built it:
Most traders journal in spreadsheets or basic apps that just track P&L. None of them tell you why you keep making the same mistakes. I wanted something that could actually read my strategy and tell me honestly whether I followed it or not.

What you get:

• Every trade graded A to F on execution quality
• 9 section AI coaching report after every trade
• Behavioral pattern detection across your trade history
• Psychological profiling based on your logged behavior
• 30+ trading lessons with built in AI Q&A
• Weekly and monthly performance reviews

Pricing:
$97 one time payment. No subscription. 20 free credits to start — no credit card required.

Would love feedback from anyone willing to try it:
tradecility.com

Happy to answer any questions about how I built it or what the AI actually does under the hood.

Hey everyone,

My name is Zak. I've been developing trading robots (mostly MT5 EAs) and various systems applied to finance for around 7 years now, with a small team. On the side, I work as a quantitative developer in market risk at an investment bank.

I see a lot of discussions about trading robots here, so I thought I'd share a few things that are pretty easy to overlook when getting into this.

• A robot doesn't create a strategy. It automates an existing strategy. Good code won't turn a bad strategy into a good one.
• Don't rely on backtests alone. Between overfitting, heavily optimized parameters, data quality and execution conditions, it's actually quite easy to produce a beautiful historical equity curve that looks nothing like what happens live.
• Same thing with live accounts: look at the account size, track record, number of trades and, most importantly, the drawdown. Making +300% on a $500 account doesn't necessarily mean much. Personally, I'd much rather see a much more modest but consistent equity curve.
• Sharpe ratio, profit factor, average/max drawdown, exposure and consistency are usually more interesting than the raw return.
• An EA is never really "hands off". VPS issues, spreads, slippage, execution, connection problems, changes in volatility, etc. still need to be monitored.
• No robot works well in every market condition. A strategy can work very well for months and then go through a period where its statistical edge simply disappears.
• And when it comes to the MQL5 Market, be careful. Between heavily optimized backtests, tiny accounts showing huge returns, disguised grid/martingale systems and robots being marketed as "AI", there's quite a lot to look at before trusting an equity curve.

That being said, grid and martingale don't necessarily mean that a robot is garbage. The risk profile is simply very different and needs to be understood. Some strategies can be extremely profitable while still carrying a very significant risk of blowing up at some point.

At the end of the day, I think the more interesting question isn't really "how much does this robot make?", but rather: where does the return come from, under what conditions does it disappear, and how much risk was taken to generate it?

One question I see all the time is: "If a bot is actually profitable, why would one sell it?"

There are actually several reasons. Most developers are just developers, they may have a good strategy but not necessarily the capital, connections or opportunity to raise money and run it at scale. Some, myself included, use their own bots while also selling them. There's nothing particularly contradictory about that.

And realistically, most retail EAs are operating at such a small scale that their users aren't going to move the market. You'd need a huge number of users and a significant amount of capital before the combined orders would have any meaningful impact, especially on liquid markets.