Fi

Finding insider stock transactions in real time.

Hacker News

Finding insider stock transactions in real time.

ShareSEER is a research tool for investors. We are excited to announce the launch V 1.3 of ShareSEER. We now have: - A real time insider filing dashboard - https://shareseer.com/today/insiders . View live sales and purchases of stocks by company insiders! Get information one day faster than in major brokerages. Filter by existing companies. - A risk extractor which highlights unique risks for S & P 500 companies. e.g - https://shareseer.com/analysis/risks?tick=MOS -We augment the existing feature of searching for 10-k/10-Q's for a given company with a.) Recent Insider filing information when available b.) Extracted risks for S & P 500 companies. E.g https://shareseer.com/search?q=KLAC - Super fast infrastructure. We have rewritten the previous generation infrastructure to a blazing fast go server. We are still learning what investors want to know. This tool is born from the pain we faced as individual investors. We want to level the playing field between what the big investors know and what we know. We would love to hear your feedback to make ShareSEER even better. Please check it out. One more thing. For now- ShareSEER is free!

Visit product View on Hacker NewsJun 20, 2018

Actual performance

34points

12comments

Made the leaderboard

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

84%84% 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: excited, exist, existing · Missing: https docs, just released, lua

69%69% 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

48%48% 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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

23%23% 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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real time · 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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