r/ai_trading

Most bots fire signals based on a crossing of lines or a threshold hit. They don't know *why* they entered — they just did.

I took a different approach. Every trade starts with a written thesis from the AI agent:

> *"MARKET CONTEXT: BIP-20DEC30-CDE is trading at $68,700 in clear price discovery above Macro POC ($63,994.60); 6H Macro Tide (+575,192.53) and 1H Macro Trend (+501,316.74) demonstrate dominant institutional spot and futures buyer aggression; order book reflects sustained bullish asymmetry (3,362 immediate / 39,404 deep bids vs 2,658 / 25,213 asks) reinforced by primary bid wall at $68,550 (3,034 contracts); Open Interest is expanding robustly at 220,248 with balanced 8.76% annualized funding.

| ALPHA THESIS: Uncontested multi-timeframe CVD momentum combined with thick passive bid absorption provides high-velocity continuation setup; executing momentum market buy with 2.5x 1H ATR ($523.93) downside insulation and targeting 4.5x 1H ATR expansion into overhead liquidity voids.

| EXIT CONDITIONS: Hard invalidation stop at $67,390.17; take profit target at $71,057.69 (R:R 1.80:1); trailing stop tripwire activated upon +0.8% advance with 0.25% trail step."*

Original Working Thesis

That thesis is attached to the trade. It's not just a log entry — it's the framework WATCHDOG uses to manage the position.

**Here's what happens while the trade is open:**

The AI that manages risk (WATCHDOG) reads the original thesis and checks: *"Is the market still behaving the way the thesis predicted?"*

Gemini 3.7 Flash analyzing current open trade and thesis

If BTC drops but the macro structure is intact → WATCHDOG holds position.

Active trade that the agent decides to HOLD

If the regime flips from expansion to distribution → WATCHDOG exits regardless of price.

**When the trade closes:**

The system runs an autopsy. Did the thesis predict correctly? Was the lesson learned worth remembering? The result gets scored across 6 factors — recency, PnL impact, regime match, and crucially, a **+50% loss bonus** so bad trades are weighted heavier in memory.

Post Mortem after every closed trade dissected and saved to core memory on next signal

**The loop:**

Signal → AI writes thesis → Trade executes with thesis →

WATCHDOG manages against thesis → Trade closes →

Autopsy grades thesis → Core memory stores lesson →

Next signal: AI reads past lessons before writing new thesis

| Feature | Most bots | This system |

| Entry reason | Lines crossed | Written thesis from AI |

| Trade management | Hard TP/SL | Thesis-aware risk management |

| Post-trade | Nothing | Autopsy + scored memory |

| Next trade | Same as last | Informed by past lessons |

Most platforms do ONE piece of this. This does the whole loop.

Okay so context: I'm a second-year CS student, and a few weeks ago at a hackathon I got annoyed that every "AI stock bot" I tried was either a glorified ChatGPT wrapper that hallucinated prices, or a dashboard nobody actually opens. So I built Finley instead — no dashboard, no commands, you just... talk to it in Telegram like you'd talk to an analyst friend who never sleeps.

Send it a ticker, a voice note, a PDF of an earnings report, a screenshot of a chart — it pulls live data from Finnhub/yfinance/SEC EDGAR, remembers what you've asked before (actual vector memory, not just chat history), and can proactively DM you a morning briefing or a price alert without you asking.

The part I'm genuinely proud of: it runs on 100% free tiers. Gemini with multi-key rotation across accounts (auto-detects rate limits, rotates keys, retries — never just dies), MongoDB + Qdrant free clusters, zero paid APIs. I wanted to prove you could build something that doesn't feel like a toy without spending a dollar.

I'm posting this half-nervous, honestly — I know finance-bot posts get torn apart here (rightfully, most of them are trash), and I fully expect someone to poke a hole in the alert latency or ask why I didn't just use LangGraph. Go for it, that's kind of why I'm here. Would rather find out now than after more people are relying on it.

It's open source, MIT licensed.

What would you actually want out of something like this before you'd trust it with a real watchlist?

Repo's here: github.com/Skull-boy/Finley

As you can see the repo is private now

I got tired of signal sellers with screenshot track records. Winners posted, losers deleted.

So I built the opposite. You post a prediction before the open. It gets hash-locked — no backdating. The market settles it automatically. Everything stays: wins, losses, even the entries that never filled. No accounts. Free. Open source.

Almost called it StockOverflow. Went with QuantRank500 — felt more like a race than homework. Everyone gets the same simulated $500. My own bot is user #1.

Two questions for this crowd: what would it take for you to actually trust a record like this? And what's the first way someone will try to game it?

demo.quantrank500.com if you want to poke it. Code's on GitHub.

Been building and throwing away strategies on MNQ for a while. Most die in testing. I tried retest entries, divergence entries, basic buy and sell one contract hold, New york ORB, and some others, I have all pine scripts saved. Ive taken about 2 automated payouts. one for 500 and one for 1000. Fully automated fully passed the account and taken payout(2-3 weeks). But then also blew my accounts right after. These two survived and are the only ones I have wired up live right now, so here's the whole thing including the numbers I don't love. Im trying to have a running strategy that can hold multiple funded accounts without risking blowing them.

The pipeline

TradingView (Pine v5) -> alert with {{strategy.order.alert_message}} -> TradersPost webhook -> prop account.

A third alert forks to a Google Apps Script -> Sheet -> my own journaling app so every fill is logged independent of the broker. This journaling file is more so a TradingHub idea I had also thought up. Having a dedicated area of space for prop firm trading, with a news calender, whatever the average trader would need to be omnipresent with the market as well as add any of their sites, not needing to scroll through many tabs. that was the idea. Still building upon this and would love some insight.

---

**1. EMA Pullback Structure Strategy

MNQ 5m, long and short. Enters once at full size, exits in three sized legs: a quick TP, a runner, and a bigger target. Force-flat at 12:50 PT so nothing is held overnight.

2. Stik MR(Stochastic Mean Reversion)

MNQ daily, long only, mean reversion. Scales into as many as 4 units on successively deeper dips. Holds overnight and over weekends, which is exactly why it can never run on a funded prop account - Topstep force-flats at 3:10pm CT and an overnight position is an instant violation. It runs on a dead account as a signal target only. Would need a live account with 5-10K drawdown to safely run. This scales up though, compounding interest.

There is one issue I ran into. I could only run backtesting on tradingview 5min for 7 weeks back. So I built a backtesting engine with Claude, primarily for pine scripts. Has some issues here and there with running some concepts but its easily fixable.

Me and some friends also set up a little discord for a community dedicated for prop firm algo trading help. We also set up a discord News Bot that delivers real time important news dedicated for MNQ,MGC,ES and other futures indexes.

This post is simply a reach out and share of my work so far. Would love to hear feedback and speak on this concept further! If you wanna interact with all the things in this post join this discord or just reply here.

https://discord.gg/qBgTQcxDu

Quick update: the current Fynca Trading Challenge is officially underway.

A huge thank you to everyone who signed up and is now competing for a share of $1,000 in real cash prizes. The leaderboard is already getting competitive.

The response exceeded our expectations, so registration is now open for the next challenge.

This time, $2,500 in real cash prizes will be split among the top five finishers.

All trades are simulated using demo capital, so none of your own money is at risk.

Spots will be limited again, and registration will close once they’re filled. If you’re interested in joining, leave a comment below, and I’ll share the details.

I was tired of hunting for long-tail events; and creating bootstrapped event-generators was a hassle. If I'm focusing on a project, why would I want to maintain a sub-project? So I built a once-and-for-all market simulator with events on demand (completely free & open-source, available to everyone)

It's a fake market data API — realistic OHLCV for any ticker, a tick stream that runs 24/7, and reserved tickers (CRASH, GAP, HALT) that action on command. Point your existing client at it to test code paths that only fire on market edge-cases.

This is a testing tool, to test long-tail events like run-ups, halts, SSE loss, and intraday flash events.

No API Keys needed. Simple curl to test:
curl 'https://cuckootrade.com/api/v1/alpaca/v2/stocks/bars?symbols=AAPL,CRASH'

• Completely free, no API key, nothing to sign up for.
• Historical bars : OHLCV for any symbol, 1-minute through yearly, back to 1970, on the real NYSE calendar — no bars on weekends or holidays. (https://cuckootrade.com/docs#bars)
• Live SSE stream : SSE ticks that don't stop — nights, weekends, holidays included.
• Scenario tickers : Reserved symbols that misbehave on demand (https://cuckootrade.com/docs#magic)
  • CRASH drops ~25% mid-month
  • GAPPY gaps overnight
  • HALTS drops bars mid-session,
  • SPIKEY wicks and reverts
  • FLAT sits at exactly $100.00.
• Drop-in replacement for endpoints (switch alpaca.com/api -> cuckootrade.com/api)
  • Currently supports Alpaca, Polygon, & Alpha Vantage
• Deterministic & Reproducible: Every bar is a pure function of (symbol, timestamp, seed), computed per request, no database. Same request, same bytes, forever — results are consistent between local host, CI container, and hosted service.
• Live Sandbox to try it in a web browser ( https://cuckootrade.com/playground )

Worth saying: it's for testing, not backtesting. Synthetic data will make almost any strategy look profitable.

It's a portfolio project I'm still polishing, so feedback actually helps me. Tell me what's broken, or what provider or scenario you want next and I'll build it. Or you're welcome to contribute to the repository:

Open source Github: https://github.com/tj-miller-dev/stock_simulator

No paywalls. No fees. No login. Just the data.

D*mn, it’s really not easy to build this thing, man.

I’m a long-time ICT trader ,profitable sometimes, losses many times 😂. I am super passionate and fell in love with the idea of Agentic Trading. My progress looks beautiful so far for me but its not working.hahahaha

I’ve done a lot of research using agents to scrape/fetch information from Reddit, X, YouTube, GitHub and the web while trying to build this thing and understand how algo trading can improve my trading edge.

So far, these are some of the projects/tools that have inspired or influenced what I’m building.

1. Backtesting (opensource)

- backtesting.py

- mementum/backtrader.git

2. Visual UI / Charting Inspiration

- Kahtaf/OpenCandle.git (opensource i think)

- LuxAlgo

- DeepSeek Harness desktop for simplicity

- Plotly (don’t know much about this yet, haven’t done a deep dive,to improve some on openchart

-dylanpersonguy/OpenCharts.git

3)Features I Want to Build (and may add more till unlimited technical debt):

- MCP / broker integrations — Robinhood and others

- Ability to connect/fetch from your own market-data provider easily

- Support for FX, futures, commodities, etc.

- Live execution

- MT4 + MT5 integration — haven’t researched this deeply yet, but for me it’s a must

- Ability to do your own quantitative research

- Self-debugging Python scripts or whatever it is

- Backtesting and strategy experimentation

- Easier connection between AI, charts, data and execution.

4)Plugins

- Something that can convert Pine Script into Python, similar to PyneSys/pynecore.git" (

- More plugins later and still exploring what is actually useful

5)Skills

There are already a lot of Claude/AI trading-related skills and workflows out there, so I’m also studying those and will probably take inspiration from some of them.

6)News / Sentiment

- Inspired partly by the OpenCandle app

- I’m sure there are many other good projects in this space that I haven’t discovered yet

Btw, I really don’t care if somebody is already building the same thing or has the same idea.

I’m sure there are many senior/experienced developers, quant traders and algo traders here who are already way ahead and probably done the same

So I’d genuinely appreciate any advice, criticism, tips, architecture suggestions, useful repos, libraries, APIs or things you think I should avoid.

If you’ve built something similar before, I’d especially love to hear what became difficult once you went beyond the prototype stage.

This is a live account, all trades are done by the LLMs on my platform. Those are my top 10 bots, I am running 20 bots total right now (10 on Gemma and 10 on 5.6 Sol).

It was a good week last week, these bots are trading stuff like Sandisk, Samsung, Micron, DRAM ETF, and NBIS.

These are new settings I'm trying out so I don't have more history for it yet.

Let me know if you have any questions or want to run your own bot. It is free.

In a few posts here I've replied mentioning a bots app I built with Claude. Along the way I ended up pulling a few tabs out of that app and turning them into a standalone screener, mostly so my friends could see what my bots were trading — plus top gainers and a few other lists. Honestly, I usually don't pay much attention to the screener or the lists myself; I watch the bots, and the screener exists for my friends to use.

Today I was feeling good, stayed home, and decided to actually log my trades through the screener for once. Ended up around +$1,300 by end of day.

A few people have asked where to find the app. I'm not planning to put it on the Play Store or sell it or anything like that, so I figured I'd just post how the scanner works, what makes it profitable, and drop a link for anyone interested.

Yes, I know — you should be suspicious of a random dude on Reddit handing out an app. Fair. Test it on a spare phone or any Android device you don't care about. There's no iPhone version because Apple wants hundreds of dollars a year for the privilege, and I'm already paying for Expo plus overages since I update the app almost daily off requests from my friends in a WhatsApp group.

How I actually use it: when I get a trend notification, I confirm it visually on the chart first. If I buy, I put the trade on AUTO, which tracks it by 5-minute candles — and once I'm up over 5%, I tighten it to 1-minute candles. That's the whole routine.

Below is a brief on how the scanner reads trends. You're welcome to try it — log paper trades or your real ones, however you like. im gonna attache few screen shots and videos as proof.

# THE LEDGER — how it works, what it's worth, how to run it for $500–1k days

*(written 2026-08-17 night, receipts current through today. Saved in Bake_Off

so it survives the session; the same brief lives in the portable zip's world.)*

## What it is, one sentence

The LEDGER is **your hand plus machine discipline**: you pick the ticker and

pull the trigger, the machine journals it and runs the exits — so your edge

(picking) is never diluted by your weakness (holding losers too long, watching

too many things at once).

## The division of labor

| job | who does it | receipt |

|---|---|---|

| find candidates | the scanner lists + 🎯 STALK sirens | 27/29 of 08-17's monsters fired early |

| decide + buy | **you** | 08-17: +$1,457 while all three bots were red |

| cut losers | AUTO (the machine) | JFU −$53 in 10 min, IVF −$77 — IVF later fell to −29%; the floor saved $290 |

| ride winners | AUTO trail (HAG) | AXTX +16%, WETO +57% — still riding while reds were long gone |

## How it works, step by step

1. **Scanner tab** — four boards, all fed live by the PC scanner: MOVERS (B'sscreen), WILD (relvol-10 rockets), GRINDER (steady climbers), RADAR.
2. **Open the chart**, check the chips (below), decide.
3. **LOG BUY** — writes the trade into your journal (`manual_trades`). In thebots app the LEDGER tab can also fire real paper orders; the Logger app isjournal-only by design (its only key is a data key).
4. **AUTO ON** (the pill) — from that second the PC watcher (`ledger_watch`)owns the exit on the 5m law (1m if you flip the toggle):- **floor −5%**: straight down from your entry = out, no debate- **breakeven**: once the name has been up +5%, the floor rises to your entry- **HAG trail**: a red 5-minute HA candle arms a stop 5% under the last

GREEN candle's close; one green candle cancels it. Greens and dojis ride.

5. Exits stamp the row (`AUTO-FLOOR / AUTO-BE / AUTO-HAGTRAIL`) — the journal

is its own receipt trail. WINS/LOSSES tabs score you; ECHO shows what the

bots did with the same tape for the week-end compare.

## How it reads trends (all one source — the app-read chain, Fidelity parity)

- **Chips per timeframe (5m → 1D)** light on the OP trigger: ADX ≥ 20 and

above its recent average, +DI over −DI, MACD line above its last four values,

histogram improving, RSI > 50. Five confirmations — when a chip is lit the

trend is REAL but already moving (it's a confirmation stack, late by design).

- **1m chip** (new, 08-17): your SMA law — SMA50 above SMA200 and SMA20 broken

above SMA50. The fast regime read.

- **🎯 STALK sirens** (new, 08-17): the EARLY read — pushes the moment a

dip-recovery completes or a flat base ignites, single-digit % into moves.

The chips tell you it's a trend; the siren tells you it's starting.

- **HA candles** on every chart: green/doji = trend alive, red = the only

warning the exit law needs.

## The $500–1k/day playbook (your three plays, from your own receipts)

1. **Morning recovery (9:40–11:30):** never buy the 9:31 spike. Wait for thewash → higher-low → reclaim. Your OSRH: in 9:43, +15%, +$405 on two lots.The siren fires exactly here.
2. **Steady-climber rides:** grinder-board names above their stack — buy therecovery print, let the trail hold them for hours. AAOX +$330, AXTX +16%.
3. **Afternoon continuation (12–15h):** a name already on the day's monsterlist pauses near highs and breaks — WETO in at 13:23, +$989. One or twobullets max; this play misses more than the others but pays multiples.

Sizing that produced +$1,457: roughly $1–2.5k a bullet, 8–10 bullets across

the day, never two wrappers of the same stock, AUTO ON on everything.

## How successful — the honest numbers

- **08-17 (today): +$1,457** — your best receipted day, beating all three bots

combined by ~$2,300 on the same tape.

- **08-14: +$436** on the famstalk day, again beating the fleet.

- Longer history (39 manual trades, pre-AUTO era): **61.5% win rate** but a

payoff ratio near 1.04 — you picked right and gave back on exits. THAT is

what AUTO fixed: today's losers averaged −$56, your winners ran to +$400.

- The machine copies of your plays backtest at **~$582/day (wild lane) +

~$210/day (grind lane)** — the $500–1k band is real on this tape, but it is

a GOOD-TAPE number, not an entitlement. Quiet days pay $100–200; two or

three monster days a week carry the average. The job is being armed and

disciplined when they arrive — the LEDGER exists so you always are.

## The one rule that makes all of it work

**Never override the machine on a loser.** Every receipt says your edge is the

entry and the machine's edge is the exit. The day those swap jobs is the day

the whole thing stops working.

here's the link for the app
https://drive.google.com/file/d/1XL3ojOHTkd_HK-ZEUHrlkdYkU5Pnl8ei/view?usp=sharing

Most traders use AI search or X to check trading news.

But there's 2 main problems with this:

1. AI search: News takes time to appear and can confidently state old news. Still good for getting general trend summaries or big events etc

2. X: Fast but each individual post doesnt tie back into whats actually going on so youre manually connecting dots.

So I went and talked to the Financial Juice team and got their breaking news feed built directly into my app!

My app already gives a market summary from all my data sources, and remembers the current state so each breaking news that comes in updates the memory for context when summarising the market environment for you. (although Ive put a filter to only show headlines in the suummary if it's relevant enough to move the current market)

But if you like seeing all the headlines yourself, you can still browse the raw feed on the side which autotags to relevant assets. E.g. on my screenshot you can see theres a headline of China buying $289B in forex. This autotags to AUD as australian economy is strongly correlated with chinese buying power for Australias metal ores etc. (This doesn't shift the bias though, as current AUDUSD is mostly driven by consecutive US print results)

Its free to use here:
https://echelonedgeai.com/

My app is in free beta but you can still get breaking news for free anyway as famous X accounts like financial juice or walter bloomberg post a lot. FX street also gives great market summaries too that you can look over for context.

The feedback here has been really useful in the past, so let me know what I'm missing this time. Appreciate it!

As a software engineer, I got tired of spending months of my free time on bots that didn't hold up live, so I've built Nodlow.ai: describe a strategy in plain english (or drag blocks), backtest in seconds, deploy the same strat on any cTrader-compatible account (propfirm included).

Been using it myself and shared it with a few close friends but I'd like to mass-test it — so we just opened the beta for free! If you hit your limits, ping us in the platform support chat and we'll bump them..

Honest question: Would you give this a try? And if not, why?

Thanks for reading!

I just released a benchmark for AI trading for free - get started in under a minute on arena.uvlabs.ai

Macrobench allows your agent to trade procedurally generated markets based on data from the '08 financial crisis, dotcom bubble, and COVID crash.

Performance is scored against a well optimized algorithm. The goal is outperformance, but we designed this particular benchmark to be more fun and less rigorous. Just point any agent at it and go.

Our team uses these same generators and similar scoring patterns to evaluate our own models / agents for market making, trading, and risk management

Free and easy to get started - reach out to me on X or at bebis@uvlabs.ai for more :)