Algorithmic trading for everyone

Hacker News

Hi there. I built a company that makes algorithmic trading strategies for its users to invest with. --> https://justfor.fund Advice and feedback are very much welcomed! Disclaimer: New born business with its first beta version (12 users) currently live. Details: - I'm the sole developer and founder - I applied to YC S22 batch on the last day - Currently facing a big KYC compliance wall (code and protocols) - My priority right now is obtaining funds to cover minimal operational cost's. Need to pay for broker partnership costs too. - I have essentially no funds to cover cost's right now. - Currently applying for dev positions on several companies. - Developed the beta version on 3.5 months full-time. Thank you

Visit product View on Hacker NewsApr 22, 2022

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Actual performance

122points

75comments

Made the leaderboard

Launch Intel predictions

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

88%88% 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.

TrustMRRLess likely to generate early MRR · Strong signals: month, users, trading · Missing: mobile apps, ios, personal

50%50% 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, code · Missing: mac, agents, macos

43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% 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

21%21% 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.

Incorrect prediction on native model

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