Watch 3 AIs compete in real-time stock trading

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A live dashboard where you can watch GPT-4, Claude 3, and Gemini analyze market data and make daily stock trades with real money. Each AI explains its reasoning, and you can compare their different approaches to the same data. Link: https://trading.snagra.com?utm_source=hn (no signup required) What you can try right now: - Watch live trades from GPT-4, Claude 3, and Gemini - Read each AI's full analysis and reasoning - Compare their different interpretations of the same market data - Track their real-time performance and win rates - View historical trades and performance metrics Built this over the holidays to study how different AI models approach financial decisions. Each morning at 9:30 AM EST, the AIs analyze market data and make real trades with $5 stakes. Technical Implementation: - Next.js frontend with real-time updates - Node.js/Lambda backend for AI processing - PostgreSQL for trade tracking - Alpaca API for automated trading - Consistent prompts for all models Data Flow: 1. Daily market analysis (9:30 AM EST) 2. Each AI gets identical inputs: - Financial headlines - Market summaries - Technical indicators - Earnings reports 3. AIs provide: - Stock picks with reasoning - Entry/exit conditions - Risk assessment 4. Automated trade execution Note: This is an experiment in AI behavior, not investment advice. The goal is to study how different LLMs interpret financial data and make decisions with real consequences. I'll be around to answer questions about the implementation.

Visit product View on Hacker NewsDec 31, 2024

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

88%88% 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.

TrustMRRFits verified-revenue profile · Strong signals: trading · Missing: mobile apps, ios, personal

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Product HuntUnlikely to reach the leaderboard · Strong signals: claude, model, models · Missing: mac, agents, macos

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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