GPT-powered investment portfolio generator

Hacker News

Hi HN, I’m Lefteris! I work a 9-to-5 job, but I love coding and want to become a solopreneur. I'm excited to turn my passion into projects that make a difference and solve some of my friends’ problems. Yes, not mine.. my friends’. I’m excited to announce the launch of PortfolioGPT, an AI-driven tool that leverages OpenAI’s capabilities to help you build your personalised investment portfolio. Unlike typical portfolio generators, PortfolioGPT integrates real-time financial data and insights, ensuring your investments are both informed and adaptive to market changes. Simply enter your desired investment amount, risk level, investment duration, investment goal, and optionally preferred asset class (more to come so the experience will be fully personalised). Aaaand… let the AI handle the rest! PortfolioGPT excels in delivering concise and systematic recommendations, generating step-by-step investment plans over 90% of the time. It will tell you what to invest in and what amount to invest in each ticker I’m particularly focused on helping both novice and seasoned investors navigate the complexities of modern finance, including emerging sectors and innovative financial instruments. I’m committed to continuous improvement and would love to hear your feedback as I refine PortfolioGPT further.

Visit product View on Hacker NewsSep 25, 2024

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

85%85% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: openai, coding, open · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, io, including · Missing: https docs, just released, exist

55%55% 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 · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

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

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

29%29% 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

13%13% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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