Problem solved

Retail investors often lack the time, tools, or expertise to perform sophisticated stock analysis, relying on intuition or incomplete data. Stocker solves this by automating technical and sentiment analysis with AI, providing accurate price predictions and clear trade rationales. It enables data-driven investment decisions without the need for complex software or financial background.

Use cases

• Running daily ML-based price predictions and pattern detection for individual stocks.
• Building a watchlist and receiving automated alerts on forecast changes and news sentiment.
• Using the AI Trade Thesis to get a summarized investment rationale before making a trade.
• Comparing a stock's performance and valuation against its industry peers.
• Generating an AI-powered summary of a company's latest earnings report.
• Receiving portfolio-wide advice from the AI Portfolio Advisor for rebalancing or optimization.

Audience

• Business Users
• Hobbyists
• Researchers

Pros

• Employs ensemble ML models (XGBoost, LightGBM) for accurate predictions.
• All-in-one platform combining technical analysis, sentiment, and trade theses.
• Affordable pricing with a generous free tier (5 analyses/day).
• User-friendly interface suitable for non-technical investors.
• Real-time data and live analysis for timely decision-making.

Cons

• Free tier limited to 5 analyses per day, which may be restrictive for active traders.
• Market predictions are inherently uncertain and may not capture sudden events.
• Currently appears to cover only US and Turkish stock markets, limiting global applicability.