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Indicator Insights – Do they even work?

Hacker News

Indicator Insights – Do they even work?

Hi everyone, This is not a finished product or anything, but I decided to not to take this side project too seriously. The main deal is: I was mostly losing money on the stock market, so I decided to look into finance forums and sites. There, I found out about indicators, but I find them a bit hard to grasp. All I wanted to know was whether they actually work or not, especially in bulk-analysis setting. For instance, if you just look at Relative Strength Index (RSI), would that make you profit or lose money on a given period? What would be the Total profit if you use RSI for all stocks? Maybe this exists. I don't know tbh. Still, I convinced myself that this should exist. Therefore, I had a reason to learn more about React, Vite, authentication etc. so... I started coding a bit and one thing led to another and I found myself buying a domain for 7 euros, again. The site is pretty crude as it is but I like using it daily. So why not share it, right?

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
68%68% 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: using, coding · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide, io · Missing: https docs, excited, just released
45%45% 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
45%45% 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
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: profit · Missing: arr, mrr, revenue
20%20% 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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