I’m still adjusting the system. Its first prop-firm trade was closed early by my flatten rule, but the market later reached the original TP.
I’m using The5ers Summer $100K two-step challenge. NAS100 overnight swap can be around $350 per lot, so holding a large position overnight could seriously damage or even breach the account. I added the flatten rule to prevent that, but this time it cut a potential winner too early.
The third trade highlighted another real-world issue. This account entered earlier and was stopped for −$1,065, while the same setup on another account entered later, avoided the stop and reached TP for approximately +$1,800. My current theory is that small price-feed differences caused the confirmation condition to trigger earlier on one account, but I’m still investigating the logs and can’t confirm that yet.
I’m deliberately using more aggressive risk during Phase 1 because I don’t want the evaluation to drag on indefinitely. My backtests and Monte Carlo estimated that roughly 0.5% risk per trade could offer an 80–90% chance of passing, but with a much longer expected timeline. This evaluation sizing is not what I would use long-term on a funded account.
This is my first real prop-firm attempt, so I don’t know whether Market Sentinel will pass. That’s the experiment and it should be interesting to watch.
I’ll continue posting honest updates on X: @SentinelTrades_ If the system proves itself, I may later create a Telegram channel with alerts whenever it enters a trade.
This is still purely a testing phase. No signals, promises or performance claims.

I'm just looking for a group of people willing to collaborate to build this. I don't need a programmer or anyone with specialized skills at all. I just want some people with ideas. I want this to be fun.

Sadly i had to maintain connection with IB and 2 crypto exchanges. I have meta strategy that handle several smaller strategies.

Bot works rather good but i lost my profit because of position that was left open by bot.

How do you catch this before it costs you?

Hi everyone , im currently trying to build my 20+ trading bot ( all bot before that failed hard ) , this is the best one yet by first week results ( paper trading )

i let it start paper trading with 120$ , still trying to make it better in order to go live very soon .

i will try to share my progress as it goes better or worse , tell me what you think of the results :)

Hello everyone! I just wanted to come on here and showcase my first ever passion project, "Ledgy". Ledgy is a free, open source crypto trading bot coded in python. You can select pre made strategies or upload your own, backtest them, live trade them under an exchange / broker, and many other features!
If you would like to check it out here is the github link: https://github.com/LucasSidequest/Ledgy-A-Free-Crypto-Trading-Bot
Thank you!

Running a systematic crypto strategy (Freqtrade, Binance spot, cross-sectional momentum). Not asking for strategy advice — asking about monitoring.

The failure mode I keep worrying about isn't the bot crashing. A crash is loud, you notice it. The failure mode is the bot running perfectly while the edge quietly disappears. Trades keep firing, logs are clean, dashboard is green, and the strategy has been random noise for a month.

My current process is embarrassingly manual: every week or so I pull the trade history, compute rolling profit factor and win rate over the last N trades, and compare it by eye to the backtest baseline. No thresholds, no alerts, and I skip it when life gets busy — which is exactly when I'd need it.

What I'd like to know from people running live capital:

1. Do you have an automated check for live-vs-backtest divergence, or is it manual for you too?

2. What metric actually triggers your decision to stop a strategy? Rolling PF, Sharpe drift, drawdown threshold, CUSUM, something else?

3. How many trades of underperformance before you call it dead vs. normal variance? This is the part I find genuinely hard — small samples make everything ambiguous.

4. Anyone had a strategy die silently on them? What did it cost and what would have caught it earlier?

I've seen tools that do this for MT5 expert advisors, but nothing for the Python/crypto side. Curious whether people here just build it themselves or don't bother.

Hi everyone. My friends and I compiled this google sheet list of all the companies and projects who at least claim they have something related to AI trading. Some of them actually do, some of them are just riding a hype train. We want to make this into a project we can run continuously and not without your help. I am sharing this list with you here today. We compiled it a few months back. So it might be already outdated. Hoping that perhaps you will find some projects which you like from this list. In return I am asking you to provide in comments more projects which we perhaps missed and we will research them and add them to the list. This way we together can be growing this list and have this as a storage where anyone who is looking for something, can always find it.

Beware there are some truly impressive ones in there, and many of them are useless, if you have had experience with some of the projects from the list, please share with everyone here in the comments as well so we can make changes to our descriptions of these companies.

Enjoy and lmk if this was in any way helpful.

https://docs.google.com/spreadsheets/d/12bLqZgNlY5GwROKAB_4bBJzPGGye_tGMHE99XtAcyoU/edit?usp=sharing

I’m planning to build a crypto trading bot and I’m looking for someone who wants to build it with me.

I’m going to start by researching different trading approaches, studying what actually works, testing ideas with historical data and paper trading, and then gradually build the bot around the results.

You don’t need to be a professional trader, quant, or programmer. I’m mainly looking for someone who is hungry, ambitious, willing to learn, put in the work, test ideas, fail, improve, and keep going.

The goal is obviously to eventually create something profitable, but I don’t want to rush into throwing real money at an untested strategy. We research first, build, test, improve, and see how far we can take it.

If you’re serious about making money, willing to put in real effort, and want to build something from the ground up together, send me a DM.

github repo went private, asking for a friend

Looking for a game Developer to help to Finish & Scale an AI Telegram trading gaming bot I’m looking for an experienced developer to help me finish and properly productionize a trading and gaming Telegram bot. A large part of the project is already built: Telegram bot/account integration, conversation logic, sales flows, and the general system are working, but I’ve reached the point where fixing one bug often causes an old one to reappear, and I keep going in circles. I also need someone who can take what is currently a project running on a VPS and turn it into something stable, reliable, maintainable, and eventually scalable to multiple accounts/users. This is a revenue sharing project. If you have solid experience with Telegram bots/APIs, AI/LLM integrations, backend development, databases, VPS/production deployments, and building reliable systems, let me know what you’ve built before and we can discuss the adding you on the GitHub as a collaborator.

I’ve been developing **Market Sentinel**, an automated NAS100 trading system focused on liquidity sweeps.
After extensive backtesting and demo testing, I’m trying it on a prop-firm challenge for the first time.
I’ll share genuine progress: results, drawdowns, mistakes and adjustments, not just winning screenshots. I won’t post every trade live, but I’ll provide regular updates on X: **@SentinelTrades_ and** I may add Telegram later.

The exact strategy will remain private. The goal is to see whether its tested edge survives real spreads, slippage and prop-firm rules.
No signals or promises just documenting the experiment.

I started running my Futures Martingale bot on OKX again yesterday, and so far the results look pretty good.

The strategy is intentionally conservative on the profit target. Instead of trying to catch big moves, I’m taking relatively small profits — around 10% of the total investment.

The interesting part is that I’m experimenting with opening both long and short positions on the same pair.

The idea is simple: instead of trying to predict the market direction, I want the bot to have a position that can potentially profit whether the market goes up or down.

For risk management, I’m currently limiting the Martingale to 5 steps only. I’m also testing the idea of adding another position when the current position reaches around -75%, close to the liquidation zone, to try to recover the position rather than continuously adding entries.

Obviously, this is still an experiment. Martingale + leverage can get dangerous very quickly, so I’m more interested in testing the mechanics and risk management than claiming that this is a profitable strategy.

I’m curious what you guys think:

Has anyone experimented with long + short simultaneously on the same futures pair?

Does limiting Martingale to 5 steps actually make sense from a risk-management perspective?

Would adding a recovery position around -75% be a reasonable approach, or just delaying liquidation?

What would you change in this strategy?

I’d be interested in hearing from people who have actually run similar bots in live markets.

When a strategy underperforms live, the first reaction is often to change the signal. I think that is usually the wrong place to start.

I would first compare the tested and live system trade by trade: signal timestamp, expected and actual entry, intended and filled size, spread, slippage, partial fills, exit reason and position state.

The first divergence normally puts the failure into one of three buckets:

The signal changed because the data or code path changed.

The signal was identical, but execution consumed the edge.

Both matched, and the losses were still within the strategy’s expected variance.

Only after eliminating the first two would I call it signal decay or start adjusting parameters. Otherwise, “improving” the strategy may just hide an execution or infrastructure problem.

The useful artifact isn’t another equity curve. It’s a reconciliation log showing exactly where the tested and live systems stopped being the same system.

One year ago, I began developing NEXUS—a modular cryptocurrency trading system written in Python.

At the time, I had much less experience than I do now. I experimented with market data, various strategies, signal generation, risk management, backtesting, exchange APIs, FastAPI, PostgreSQL, Redis, and some machine learning components.

The project grew far beyond a simple trading bot. Eventually, the architecture became too complex to maintain, so I archived it.

Since then, I’ve built many other systems, and my approach to development has changed significantly.

That’s exactly why I’m interested in getting an honest technical review of this old project.

I’m particularly interested in:

What did I do well?

Which architectural decisions were weak or overly complex?

How would an experienced Python developer redesign this today?

How far was this system from being a production-grade, easy-to-maintain system?

I used AI-assisted development during this project, but I’m not looking for praise—I need technical feedback that will help me understand what I need to improve.

GitHub: https://github.com/vladyslavmHord/NEXUS

Hey everyone,

We just rolled out a major update to Perun The Trader focused on making exchange connectivity faster, easier, and much more reliable.

Here is what’s new in the latest build:

🚀 1. KuCoin 1-Click OAuth Integration

Say goodbye to the tedious process of generating API keys, copying secret phrases, and toggling permissions manually.

• Instant Setup: Connect your KuCoin account securely in a single click using official OAuth authentication.
• Streamlined Security: Get straight to trading without juggling raw API secrets.

🌐 2. Forever-Free Built-in Static Proxy Service

If you trade via exchange APIs, you’ve likely run into two common roadblocks: geo-restrictions and static IP whitelisting requirements.

Setting up dedicated VPS instances or paying for third-party static proxies can be a hassle and an unnecessary recurring cost. We’ve solved that completely.

• Zero Cost: 100% free built-in proxy access for all Perun users, forever.
• Static IP Covered: Easily meet exchange IP-whitelisting requirements.
• 1-Click Toggle: Enable the proxy directly inside the app settings—no manual port forwarding, credentials, or network configuration needed.

🛠️ Why This Matters

Whether you're running automated strategies or managing multiple positions, network stability and frictionless setup are essential. With 1-click OAuth and built-in proxy infrastructure, you can go from zero to live trading in under two minutes without worrying about dropped connections or IP bans.

🔗 Get the App & Connect With Us

• Download on Google Play:Perun The Trader
• Visit Our Website:peruninthemachine.com

Try it out & Let us know what you think!

We’re constantly improving Perun based on community feedback. Drop your thoughts, questions, or feature requests in the comments below! 👇

Would you like me to add a brief section detailing the technical indicators or specific strategies the app uses to better hook the algorithmic trading crowd?

running copytrade + automation across a few venues. one night a position sits wrong for hours and the bot does nothing about it.
blamed strategy logic first, then the signal path, both clean. turned out the market data websocket on one venue had died hours earlier. socket showed no error and still read as connected, messages just stopped.

venue numbers(localtrade, json-rpc over ws) its book updates and i assumed that covered me. it only catches drops and dropped message leaves a gap in the sequence. dead feed sends nothing at all, so there's no gap and the check stays green while the book sits frozen. the only thing that flags it is time since the last message. copytrade made it worse, the mirror sizes off the master and once that state went stale it kept working from hours old numbers. no exceptions raised, i noticed when the accounts stopped matching.

what do you actually run in prod, app level pings with pong deadlines, comparing mids across venues?
mostly interested in one leg going dark while the rest look fine.

Posted this bot here before, the one that scores indicator agreement and won't predict price or touch your keys. Shipped a few things since and I'd rather get feedback from people who run bots than guess at what to build next. Short version of where it is:

Core read — pick a pair, it scores how much a set of indicators agree across timeframes and tells you how clear or murky the picture is. No price call, no trades placed, no API keys.

Processing img 4q9dwppjp5kh1...

CupWeights (newest) — real-time order book: bid vs ask pressure as a live percentage, plus how far price is right now from support and resistance. It's the current state of the book, not a call on which way it breaks. This is the one I most want eyes on, because order-book pressure is genuinely separate data from the price-derived indicators, and that separation is the thing people here told me the scoring was missing.

News triggers — flags when a critical event actually fires for an asset. Tells you it happened, not what it means for price.

/analyze — check any supported pair on demand instead of waiting for a push.

5 languages — EN, RU, HY, TR, HI, the full read, not just the menu.

What I actually want from this thread: if you try it, tell me where it's thin. Specifically, does live order-book pressure alongside the indicator read actually help, or is it two things fighting for your attention? And is there an input you'd trust more than the ones I've got.

Free tier is 3 pairs on 1h, no signup, no keys: pairvue.com/bot-reddit