AI Equity & Stock Market Forecast

Equity — Quantitative Target Prices

Two models, one public scoreboard. Every asset gets a BUY or SELL side with the odds of finishing higher over the next 5 trading days, the limit price to bid and the stop that protects it — refreshed every trading day.

Loading... Target: — Publicly scored — misses included
Loading today’s answer…
Loading forecast data…

What to do today (5 trading days ahead · two models, one scoreboard)

Strategy — BUY above 50% odds of finishing higher, SELL below. Limit orders only, stop attached, 1% of equity at risk per trade.
No directional edge is proven yet — the odds below are ranked tilts, not promises. Details in What the numbers mean, below. The book that does make money carries no forecast at all: The Portfolio → (Sharpe 1.11, −14% worst drawdown).

What the numbers mean

“Unvalidated” is a status, not boilerplate. This model has not yet beaten a coin flip on a public, scored record: ~48% over 63 calls here, 50.1% over 1,086 Kronos predictions. Every call is booked at its target date, hits and misses alike. If it stays at 50%, the column is worth nothing and this page will keep saying so.

Why nothing here exceeds 55%. The raw model sometimes implies 83% confidence; nothing measured on this site supports that. Every tilt is published on a squashed 45–55% scale — the ranking survives, the overclaim does not. Hover any probability for the uncapped number.

What is genuinely calibrated: the fill odds, the 80% price range and the volatility behind both — 20,000 simulated paths per asset, checked by walk-forward coverage tests. Direction is a forecast; travel is arithmetic on volatility, which is why the orders are built around it. The order geometry on its own still loses net of costs over 8,770 walk-forward trades: it says where to bid, not whether to.

How to trade a row. Place the limit at the entry — never a market order. If price never comes to you, you have no trade that week, and that is a normal outcome. The moment you are filled, set the stop and the take-profit. Risk at most 1% of the account between entry and stop, so every position carries identical risk whatever the asset's volatility.

Model 1 — Swiss Quant (our engine: momentum, volatility, cross-asset and macro features)

Model 2 — Kronos (open-source candlestick foundation model, AAAI 2026, run daily on this server)

Move Probabilities

Chance price ends up at least X%, inside ±X%, or down at least X% — the three add to 100%. Hover a chip for the touch odds, which is what fills a limit order.

See what company insiders are buying
Track SEC Form 4 filings — insider purchases often signal upcoming moves
View Insider Screener →
📈

This Week's Comprehensive Market Analysis

Loading comprehensive market analysis with real-time data provider server data...

Loading real-time market data from data provider server...

Top 15 Stocks with Real-Time Analysis

Explore More

Bloomberg Terminal Crypto Forecast Forex Forecast Commodities Forecast
⚙ How Swiss-Quant AI Generates Stock Market Forecasts

Multi-Factor Equity Prediction Engine

Swiss-Quant equity forecasts combine gradient boosting ensemble models (XGBoost + LightGBM) with walk-forward BayesSearchCV optimization to predict 5-day price targets for 30+ US large-cap stocks. The system analyzes technical, fundamental, and macro factors to generate directional predictions with confidence scores and expected return percentages.

Technical Feature Engineering

Price action features are extracted from intraday OHLCV data at multiple timeframes. The model computes RSI momentum, MACD signal divergence, Bollinger Band squeeze and expansion patterns, volume-weighted average price (VWAP) deviations, support and resistance levels from pivot point analysis, and momentum oscillators across 5, 10, 21, and 50-day windows. Each indicator is converted to a continuous gradient score enabling precise signal strength quantification.

Fundamental and Macro Context

The equity model integrates earnings calendar proximity (pre/post-announcement effects), SEC Form 4 insider trading filings, analyst consensus revisions, and sector ETF fund flow data. Macro features include Federal Reserve rate expectations from Fed Funds futures, VIX volatility regime classification, US Treasury yield curve shape, and ISM manufacturing PMI. These fundamental signals capture catalysts that pure technical analysis cannot detect.

Robust Backtesting Protocol

Every stock prediction undergoes walk-forward validation on 200+ out-of-sample periods with purged cross-validation and a 2-day embargo gap between training and test sets. This prevents look-ahead bias and ensures the model reflects genuine predictive power. The system also performs regime-conditional accuracy analysis, tracking performance across bull, bear, and sideways market conditions separately.

Disclaimer: The information provided on this platform is for educational and informational purposes only and does not constitute financial advice, investment advice, or trading advice. Swiss Quant Capital is not a registered investment advisor, broker-dealer, or financial planner. Past performance does not guarantee future results. All investments involve risk, including the possible loss of principal. You should consult with a qualified financial professional before making any investment decisions. The trade ideas and forecasts presented are generated by AI models and should not be relied upon as the sole basis for any investment decision.