I made stock and crypto analysis web site to improve your portfolio

Hacker News

I made this project to help investors cut through the noise and make smarter decisions using clear, data-driven insights. Most stock and crypto tools overwhelm users with raw data — I wanted to create something that simplifies analysis without sacrificing depth. CeFinan lets you audit your portfolio with an AI-powered Health Score based on 8 key criteria, including news sentiment and advanced financial indicators. I also built a Correlation tool that shows how stocks move together, helping users spot hidden risks or diversification opportunities. The Growth section visualizes performance over time, with geographic and sector breakdowns, plus metrics like P/E ratio, Sharpe ratio, and volatility. It’s not just another dashboard. It’s a decision-making assistant — and I’d love feedback from investors, data scientists, or anyone interested in making portfolio analysis more intuitive and actionable. Website: https://cefinan.com

Visit product View on Hacker NewsMay 21, 2025

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

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best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Strong signals: plus, intuitive, users · Missing: platform, reviews, host

65%65% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, smart · Missing: web3, chat, cryptocurrency

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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