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Show HN: Upticker – financial analysis workflow tool orchestrated by LLMs

upticker.ai

4 points by ahmedhawas123 5 months ago · 7 comments · 1 min read

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Hey HN!

We're building UpTicker, an agentic platform that ingests loads of financial data (e.g., SEC filings, stock data, factor models) to allow you to automate much of your financial analytics. We support a broad range of cases across fundamental research, quantitative analytics, portfolio creation and backtesting and much more.

We’re building this because we think there’s a real gap in day to day financial insights and productivity today. So much time is spent downloading and cleaning the same data, calculating the same metrics and creating reports.

We differentiate by building the proprietary models underlying all this analysis - we ingest the data, we build time indexed metrics, and we create all our agents in Python to ensure reliable outputs.

We're early and would love to get some feedback on our work so far. Appreciate you taking the time!

ihabselmi84 5 months ago

I have spent the last few days playing with the app and it is very impressive how fast and thorough the analysis are provided by the agents. Would be nice to have an agent that read the headlines form FT and WS and generate trade ideas on a daily basis

Louay1998 5 months ago

Really cool! The app is intuitive, user-friendly, and brings everything I need into one place. One suggestion I’d make is, it would be great to have the ability to create and save a list of stocks I'm interested in, and then run all my analyses on them at once.

ihabselmi84 5 months ago

That sounds impressive. Is it free access? Would be great if I can get a demo and that way I can give you live feedback.

andsoitis 5 months ago

What is your team’s experience with financial analysis?

  • ahmedhawas123OP 5 months ago

    Thank you! My cofounder and I are both financial engineers/quants who have worked for large banks and asset managers. We're also working with a lot of industry experts and peers to help ideate on the most useful use cases.

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