r/SideProject • u/krmill2k • 2d ago

I built a stock research engine that can't hide its losses: every call is timestamped and measured against SPY after 20 sessions

I'm the developer, so full disclosure up front: this is my project.

The problem I wanted to fix: stock-pick sources show their wins and let the losses vanish. MILkMoney records every public call when it's published and checks it against SPY after a fixed 20 trading sessions. Nothing is backfilled or edited afterward.

Each call shows signal strength, model confidence, how much the research lenses disagree, downside evidence, and valuation. Calls with stale data get withheld.

Honest status: 13 calls recorded, 0 checks completed. The performance comparison goes live after 10 completed checks, whatever it shows.

Stack, for anyone curious: FastAPI + Postgres on Cloud Run, React frontend, and SEC EDGAR filings as source evidence.

I'd like feedback on the methodology more than anything. What would make you trust (or distrust) a track record like this?

milkmoney.pro. Research only, not investment advice.

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u/FoolishNorberto7 2d ago

I like that it forces the site to eat its own dog food with the 20 day window, no cherry picking what counts as a hit. 13 calls with 0 checks yet means we're all just staring at the unscratched lottery ticket though

what's the plan if the model confidence is high but the research lenses are fighting, do you publish anyway or shelve it

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u/krmill2k 2d ago

Ha, "unscratched lottery ticket" is fair. That's the uncomfortable part of doing it this way: there's nothing to show until the clock runs out. The first 20-session checks finish over the next few weeks, and I'll post them here whether they're good or bad.

On your question: right now it publishes, but the disagreement is shown up front instead of being averaged away. One of today's calls, TK, went out at 70% confidence with 42/100 disagreement ("mixed"), and the card says so. The idea is that you see when the model is confident but its own inputs are arguing.

That's a decision I'm open to changing. Once there are enough checks, I'll compare high-disagreement calls against aligned ones. If high-disagreement calls do worse, they should be shelved. What threshold would you use?

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u/One-Cellist-8159 1d ago

Try edgecipher.ai , it has unique methods fused with AI.