Predictive scenario analysis with clear visualization
Models project ranges rather than point forecasts. You can see how allocations might behave under different market assumptions.
Predictive data analysis and backtesting
Building wealth with historically proven strategies. Without daily market study.
Polanatrex is the AI-supported decision-making platform for time-strapped parents and private investors. Predictive data models analyze large amounts of data in real time, test every strategy over real historical market phases and translate results into clear, actionable recommendations for action.
Backtest / Risk Model — SchemaModel active
Historical regimes: sideways / crisis / recoveryRisk corridor
Schematic representation. No forecast and no promise of returns. Historical performance and backtests are not a reliable indicator of future results.
OverviewTime factor and capital discipline
Between family, work and market noise, there is little room for clear decisions.
Anyone who combines family and career knows the dilemma: the long-term one Building assets for reserves and training planning is important, but daily market observation costs time and nerves. Manual analysis of news, forums and charts often leads to reactive trading.
Polanatrex moves this work into a verified decision architecture. The platform bundles scattered portfolio data, continuously assesses risks and delivers decision optimization based on historically tested strategies - structured, comprehensible and without daily effort.
| criterion | Manual market analysis | Polanatrex decision architecture |
|---|---|---|
| Time expenditure | Daily research, charts and news | A decision dashboard with weekly review. Time economy |
| Data basis | Fragmented sources, subjective selection | Real-time data aggregation and cleansing from structured sources |
| Validation | Individual opinions without historical testing | Backtesting over real historical market phases before every recommendation |
| Risk management | Reaction only after the price has fallen | Risk corridors, drawdown limitation and leading indicators |
| Traceability | Difficult to document | Transparent decision protocols instead of black boxes |
01Method
Every recommendation first goes through the history of the market.
Instead of claiming predictions, Polanatrex tests strategies against documented market regimes. Only when a model consistently processes sideways phases, crises and recoveries does it become a scalable recommendation for action.
Step 01
Real-time data aggregation and cleansing
Market, portfolio and risk data are merged, normalized and checked for gaps. Only cleaned data flows into models.
Input → Clean → Validate
Step 02
Historical regime simulation (backtesting)
Strategies are simulated using real historical market phases, including stress scenarios and transaction cost assumptions.
Regime: Crisis / Sideways / Recovery
Step 03
Risk corridor and drawdown limitation
Loss tolerance and fluctuation range are defined for each portfolio. Leading indicators report deviations from the corridor.
Corridor + Limit + Alert
Step 04
Scalable recommendations for action without daily effort
Results are translated into a prioritized recommendation with justification. You decide, the platform does not carry out any transactions.
Protocol → Recommendation → Decision
Data Integrity Note: Backtests use historical price and volatility data with documented time periods and assumptions. Survivorship bias and look-ahead bias are methodically controlled. Historical performance and backtests are not a reliable indicator of future results.
02Modules
Four modules for predictive clarity and risk management.
Reduced to the essentials: analysis, weighting, monitoring and documentation. Without distractions, without technical jargon hurdles.
A — Scenario analysis
B — Risk weighting
Automated risk weighting for family assets
Investment horizon, reserve target and loss tolerance determine the weighting. Adjustments are justified and versioned.
- Horizon and goal based profiles
- Drawdown limits per segment
C — Anomaly detection
Real-time anomaly detection
Atypical volatility, correlation breaks and liquidity changes are flagged before they become visible in the portfolio.
- Leading indicators with thresholds
- Quiet alerts instead of constant noise
D — Protocols
Transparent decision protocols instead of black boxes
Each recommendation contains data, tested market phases, assumptions and limits. You can follow every step and discuss it with your advisor. No unauthorized transactions, no opaque scores.
03Application
Three concrete use cases for everyday family life.
Polanatrex is designed as an AI assistant for strategic, financial and investment decisions - measurable in effort, sober in tone.
Scenario 01
Long-term reserves and training planning
Define your goal, horizon and monthly savings rate. The platform checks suitable allocations based on historical phases and shows ranges and risk corridors.
- Goal and horizon logic
- Regular test bench without daily view
- Protocol for family discussions
Scenario 02
Hedging against market volatility through leading indicators
If there is noticeable volatility or a corridor break, you will receive a classified message with options for action - not as a call for action, but as a basis for decision-making.
- Threshold-based cues
- Classification instead of alarmism
- Options with advantages and disadvantages
Scenario 03
Consolidate complex portfolio data into a decision dashboard
Depots, savings plans and reserves are brought together in one view. Duplicates, cluster risks and cost structures are made visible.
- One view for all positions
- Cluster and cost analysis
- Exportable reports
04Questions and specification
Clear answers about method, effort and safety.
Factual and without fine print. If you have any further questions, please contact our team via the contact page.
How does historical backtesting work exactly? +
Strategies are applied to real historical price trends - including sideways markets, crises and recoveries. Assumptions such as costs, time periods and data statuses are disclosed. The aim is not to predict returns, but to test robustness and drawdown behavior. Historical results do not allow reliable conclusions to be drawn about the future.
How much time do I have to invest weekly? +
The setup requires one-time information about goals, horizons and risk tolerance. During ongoing operations, a short weekly test in the dashboard is usually sufficient. If desired, decision protocols summarize the relevant changes so that daily market studies are not necessary.
Does the AI make transactions on its own initiative? +
No. Polanatrex is an analysis and decision-making platform and does not carry out purchases or sales. You receive data-supported decision models and risk analyzes with justification. The implementation is carried out by you yourself or via your bank or depot.
How is financial data encrypted and processed? +
The transmission is encrypted, access is role-based and logged. Data is processed exclusively to provide the analysis functions and is not passed on to third parties for advertising purposes. Details regulate data protection information and order processing standards for business customers.
For which portfolio sizes and investment strategies is Polanatrex suitable? +
Polanatrex is aimed at private investors with a long-term horizon - for example for reserves, retirement planning components or training planning - as well as at companies for strategic financial analyses. A structured, rule-based approach is required; Short-term trading or leverage strategies are not shown. Polanatrex does not provide investment advice or asset management.
Access/simulationDE · GDPR compliant
Informed decisions without daily market study.
Request access or start with an initial strategy simulation. You will receive a structured evaluation with a historical classification and risk corridor - calm, comprehensible and without obligation.
- ✓ Backtesting over real historical market phases
- ✓ Transparent protocols and assumptions
- ✓ Designed for 15 minutes per week