Coin Trading Strategies
Indie HackersCryptocurrency trading strategies success rates
Since I've learned about Day Trading, traded my first Cryptos and created my first bots to analyse this market, I've loved the idea to study about Market Forecast, Day/Swing trading and Technical Indicators.
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: trading · Missing: mobile apps, ios, personal54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: crypto, cryptocurrency · Missing: web3, chat, make money14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos8%8% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Incorrect prediction on native model
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