Taunusstar is an application designed to help investors manage their asset portfolios through a market stress signal-based approach. It uses an asset allocation model that updates daily, allowing users to stay informed about the best investment strategy based on market conditions. The tool focuses on three main assets: SPY (S&P 500 stocks), LQD (investment-grade bonds), and GLD (gold). The allocation of these assets is automatically adjusted according to six stress signals that indicate the market's state. Under normal conditions, the allocation is 50% in SPY, 30% in LQD, and 20% in GLD. However, if any of the stress signals are triggered, the strategy shifts to a more defensive allocation, prioritizing capital safety. This flexibility allows users to adapt to different market scenarios, minimizing losses during periods of high volatility. Additionally, Taunusstar offers an email alert service that notifies users of allocation changes, ensuring they are always aware of investment decisions. The application is ideal for those seeking an automated, data-driven solution for portfolio management. With over 22 years of historical data and a rules-based approach, Taunusstar provides a reliable way to navigate market ups and downs. The tool also allows users to see the performance of their strategy compared to a simple buy-and-hold strategy, offering a clear perspective on the effectiveness of their investment approach. In summary, Taunusstar is a valuable option for investors looking to optimize their asset allocation and protect their capital in an uncertain market environment.


Asset allocation tool based on market stress signals.
Main use case
Optimize asset allocation based on market signals.
Ideal for
Investors seeking an automated asset allocation strategy.
Review
Pro
- ✓ Daily allocation updates
- ✓ Data-driven approach
- ✓ Email alerts
- ✓ Defensive strategy in volatile markets
- ✓ Comparison with buy-and-hold strategies
Con
- ✗ Limited mobile access
- ✗ Unconfirmed API access
- ✗ Dependence on stress signals
Access
Web
Languages
English, Spanish