AI

AI summarizes stock news and predict potential stock impact

Hacker News

AI summarizes stock news and predict potential stock impact

Hi Everyone! I was inspired by recent University of Florida research(Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models) using AI analyzing stock news to achieve an outstanding investing return. Additionally, I was also frustrated with the terrible news reading experience we have today so I created an AI that summarizes the latest stock news articles and predict the potential stock impacts. I found it surprisingly useful and want to see what others feel. It's completely free, no ad whatsoever. Please let me know what you think and what can be improved. Thanks!

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Actual performance

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
71%71% 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: io · Missing: https docs, excited, just released
51%51% 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: model, new, models · 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 · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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