Jesus

Founder @ @mathematicalco | rocket scientist & QR | prev @fdotinc & @antlerglobal

[Jesus @TheCreatorAbove]

The End of Human trading

Systems fully autonomous and capable of finding alpha and executing on this opportunities.

We are launching our SDK that can be used by builders or user of tools like Claude Code and OpenClaw.

[The Mathematical Company @mathematicalco]

Introducing the end of human trading.

Agents that adapt and evolve with the markets, without human intervention.

[Rob Carver @investingidiocy]

None of these AI slop startups seem to be run by finance people, they are run by LLM people who don't understand that hedge funds don't just run pattern recognition on candlesticks, and don't appreciate the instability of distributions in financial data.

This xkcd is still true

[Jesus @TheCreatorAbove]

@danknight761 @MichaelRoyzen Rentec and citadel don’t publish overfit models

[Jesus @TheCreatorAbove]

@MichaelRoyzen How fo you avoid the look ahead bias being in the weights of the model?

[Jesus @TheCreatorAbove]

The sharpe ratio is a clear overfit

The issue is using the agents for trading.

Even if you retrain, they have look ahead bias inside the weights, you cannot leave it.

Plus their nature of sampling make them unusable for trading

[Michael Royzen @MichaelRoyzen]

We built a hedge fund where every single trade is made by AI.

No human portfolio managers.
No manual research.
No one writing trading code.

Just a reasoning model that reads the world, thinks for itself, and trades before humans can.

Early results in testing: 2.55 Sharpe ratio. 2.79 Sortino ratio. Market neutral. $50M+ capacity.

Here's how we got here 🧵

[Jesus @TheCreatorAbove]

Link to the article:
https://t.co/VBXdRsabN2

[Jesus @TheCreatorAbove]

LLMs cannot be used for trading.

While they can simplify a lot of the work in hypothesis formulation or assist with coding, LLMs introduce risks like lookahead bias and overfitting in backtests.

Some of this issues cannot be avoided, and the newer models are worse at this.

[Jesus @TheCreatorAbove]

If you think the $20k for Bloomberg terminal is the charts and look you should quit finance

[Quant Science @quantscience_]

OpenBB: A free alternative to the $20,000 Bloomberg Terminal

Available 100% free on GitHub:

[Jesus @TheCreatorAbove]

@aiwithjainam At least read the repo before posting it, it's terrible.

https://t.co/unlblwASCZ

[Jesus @TheCreatorAbove]

I read the code. And it's garbage.

Spoiler, they even use gpt-4o as the model.

Let me show you what "high-frequency trading" means to them.

Another repo down

[Jesus @TheCreatorAbove]

This repo has the same relationship to quantitative trading that a horoscope has to astronomy.

Next time, read the code before you post the repo.

[Jesus @TheCreatorAbove]

I read the code. And it's garbage.

Spoiler, they even use gpt-4o as the model.

Let me show you what "high-frequency trading" means to them.

Another repo down

[Jainam Parmar @aiwithjainam]

🚨BREAKING: Researchers from Stony Brook, CMU, Yale, UBC, and Fudan just open-sourced a multi-agent LLM system built specifically for high-frequency trading analysis.

It's called QuantAgent and it runs four specialized AI agents simultaneously each analyzing a different dimension of the market then synthesizes everything into a single actionable trade decision with entry points, exit points, and stop-loss thresholds.

Link in the comments + details about this 👇

[Jesus @TheCreatorAbove]

This is a Flask app that fetches Yahoo Finance data, renders matplotlib charts, and asks GPT-4o to write trading opinions.

12 files. Four LLM prompts in a line. A web UI.

That's QuantAgent.