I made an app that ranks the most profitable traders on the internet

Hacker News

TLDR: I built a Social-Finance app after paying lots of money for discord signals from traders who don't even make any money. So I decided to rank top-performing traders on a leaderboard so I could tell who was worthy of learning from/copying. Figured people here may find it interesting (or not, up to you) but felt it was worth sharing. Here's the link, use it, would love to know if it's helpful: https://visibull.trade Long post: Last year I got sucked into the world of trading, but I wasn't having much success with it. To put it bluntly, I sucked... and lost a LOT of money. So to try and learn the ropes and recover some of my losses, I joined many paid discord groups. These groups promoted investment advice and trading signals from "successful traders", but I quickly realized that many of these traders were not actually successful. But there was no way to know this before joining their paid group. So that's why I created Visibull a membership platform where you can discover top-performing traders and verify their performance before joining their paid group. Basically it's an app that lets you follow and copy the most profitable retail traders. Traders can paywall their content, offering subscribers exclusive access to a wide range of benefits, such as: - real-time trade alerts that you can one-click copy - viewing of a trader's entire portfolio and - a social experience similar to Twitter But the heart of the platform is the Leaderboard, which is the trust signal that sets it apart. This unique feature ranks traders based on their performance in the financial markets using real account data via integrations with major financial companies such as Plaid and Coinbase. It empowers you to confidently subscribe to traders with proven track records, enhancing your trading experience and knowledge. It helped me so much that I shared it with others... it got out of hand kind of quick. Feel free to use it, it's built with love. Or not idc.

Visit product View on Hacker NewsOct 18, 2023

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Actual performance

1points

Did not reach leaderboard

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

92%92% 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.

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

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

45%45% 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: ide, io · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: profit, profitable, subscribers · 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 · Strong signals: paid · 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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