We built a new investment tracker

Hacker News

There is many portfolio and dividend trackers out there for investors. Lots of different kinds with different features. However we felt like something is missing. The trackers do their job yes, but not as well as they could. Most of them lack even the most basic information while still adding features that have a very little to do with actual investment tracking. So what every engineer does at this point? Builds a new one of course! What separates Stockle from other investment trackers? Here's a few key points. - We don't aim to do everything. We focus on the necessary core features and we do them well, covering every little detail without missing any critical information. While you are not able to add your house or boat as an investment in Stockle, what you can analyse is your stocks, funds and ETFs. - Portfolio aggregation in Stockle is actually aggregation. We don't just aggregate one chart or few numbers. If you choose to view the the aggregated total of all portfolios, we literally take every piece of data and cover every single detail similarly as in individual portfolios. - We've put enormous effort into logic, UI/UX of Stockle. Every view, window, button and piece of information is laid out so that user understands quickly where the numbers are coming from. Single command menu handles adding transactions, dividends and portfolios and much more.

Visit product View on Hacker NewsOct 21, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, single · Missing: mac, agents, macos

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

TrustMRRLess likely to generate early MRR · Strong signals: ios, para · Missing: mobile apps, personal, entrepreneurs

47%47% 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

46%46% predicted probability of success on AppSumo, 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

33%33% 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 · 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 · 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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