Algorithmic trading for everyone

Hacker News

Hi there. I built a company that provides algorithmic trading strategies and financial data resources for its users to invest with. --> https://justfor.fund Users can connect multiple brokerage accounts to multiple algorithms created by the community. Advice and feedback are very much welcomed! Disclaimer: New born business with its second beta version (19 users) currently live. Other details : - Fully functional platform - I'm the sole developer and founder - I've been working on the product full-time for 6 months total, iterating based on feedback received This is a follow up to my previous Show HN post, which was published 9 months ago: https://news.ycombinator.com/item?id=31117255 Thank you

Visit product View on Hacker NewsJan 24, 2023

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13points

9comments

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: month, users, trading · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, new · Missing: mac, agents, macos

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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