Stock/Crypto/Forex News Alerts and Watchlist

Hacker News

This is a new hobby project of mine, feedback welcome :) Stack ===== - SvelteKit for the frontend - shadcn-svelte for the UI - Django Ninja for the backend - Postgres for the database - Nginx for the reverse proxy - Deno for SveleteKit server - Ansiible for orchestration and deployment - Hetzner Cloud for hosting

Visit product View on Hacker NewsFeb 14, 2025

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

74%74% 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.

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

48%48% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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