Taunusstar
Visit SiteTaunusstar is a free, AI-powered S&P 500 forecasting platform that delivers daily LONG/CASH signals across 3-, 6-, and 12-month horizons using institu

Taunusstar
Visit SiteTaunusstar is a free, AI-powered S&P 500 forecasting platform that delivers daily LONG/CASH signals across 3-, 6-, and 12-month horizons using institu

What is Taunusstar?
Taunusstar democratizes quantitative market analysis by bringing the same machine learning techniques used by top hedge funds directly to individual investors -- for free. The platform runs three independent CatBoost gradient-boosting models, each trained on 100+ engineered features drawn from macroeconomic indicators (FRED), market data (Yahoo Finance), and valuation metrics. Every trading day, these models produce a probability-based LONG or CASH signal for the S&P 500 across three time horizons: 3 months, 6 months, and 12 months. What makes Taunusstar unique is its multi-model consensus engine. Instead of relying on a single forecast, the platform aggregates signals from all three horizon models into a unified Consensus Strategy (invest only when 2+ models agree) and a Position Sizing Strategy (scale market exposure from 0% to 100% based on model agreement). This approach reduces false signals, manages downside risk, and has been stress-tested through every major market crisis in recent history. Full transparency is a core principle. Users can explore complete out-of-sample backtest results -- cumulative returns, drawdown analysis, monthly return heatmaps, calendar-year breakdowns, rolling Sharpe ratios, and crisis-period performance -- all validated using strict walk-forward cross-validation with zero look-ahead bias. Models retrain quarterly to adapt to evolving market conditions without overfitting to short-term noise. The result: an always-on, data-driven market signal that gives everyday investors the informational edge previously reserved for institutional quant desks.
Taunusstar's Core Features
Multi-horizon ML Models
Three independent CatBoost gradient-boosting models produce probability-based forecasts for 3-, 6-, and 12-month horizons, enabling diversified outlooks across timeframes.
Consensus Strategy
Aggregates model outputs and acts only when 2+ models agree to reduce false signals and improve decision reliability.
Position Sizing Engine
Scales market exposure from 0% to 100% based on model agreement (0/1/2/3 LONG models), helping manage risk and capture conviction-driven upside.
Full Transparency & Walk-Forward Backtests
Provides complete out-of-sample backtest metrics (returns, drawdowns, heatmaps, rolling Sharpe) validated with walk-forward cross-validation and quarterly retraining.
Daily Probability Forecasts
Always-on daily forecasts and model confidence metrics let users monitor evolving market probabilities and signal history in real time.