PortfolioMetrics
Portfolio Backtesting and Portfolio Allocation Optimization
Hey everyone, We built Portfolio Metrics because we genuinely love finance, data, and product development. For anyone less familiar with the term: portfolio backtesting means testing different investment ideas using hi
Share cardActual performance
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Launch Intel predictions
Analyze your own launch →59%59% 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.
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
23%23% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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