Financial Analytics & Econometrics – Scientific Precision for Your Data
In the financial world, precision is not a luxury, but a necessity. We combine academic rigor with practical implementation competence. From risk models and stress tests to portfolio optimization and automated reporting – we turn complex data into clear bases for decision-making.
Our Expertise
A unique combination of academic background and practical experience in the financial sector.
Academic Excellence
- Quantitative Finance & Econometrics
- Statistical Modeling
- Financial Mathematics
- Research & Publications
Practical Experience
- Risk Management
- Portfolio Optimization
- Algorithmic Trading
- Financial Software Development
Areas of Application
Where our quantitative methods create value.
Risk Management & Stress Testing
Quantification of market, credit, and operational risks. Value-at-Risk (VaR), Expected Shortfall (ES), scenario analysis, and stress tests.
- Historical and Monte Carlo simulations
- Tail risk analysis and extreme value theory
- Stress scenarios according to regulatory requirements
Typical Questions
"What is our maximum loss with 99% probability?"
"What happens to our portfolio in a crash scenario?"
Portfolio Optimization & Asset Allocation
Mean-variance optimization, Black-Litterman approaches, risk parity strategies, and factor-based allocation.
- Efficient portfolios under constraints
- Multi-asset and multi-period optimization
- Rebalancing strategies and transaction costs
Methodological Approaches
• Markowitz Optimization
• Black-Litterman Model
• Risk Parity Approaches
• Factor-based Allocation
Forecasting Models & Time Series Analysis
Statistical and econometric models for forecasting returns, volatilities, and macroeconomic variables.
- ARIMA, GARCH, and State-Space models
- Vector Autoregression (VAR) for multivariate systems
- Machine Learning for forecasting (Random Forest, XGBoost)
Use Cases
• Volatility Forecasting
• Macroeconomic Forecasts
• Trading Signal Generation
• Demand Forecasting
Methods & Tools
We combine classical econometric methods with modern machine learning approaches.
Econometric Methods
- • ARIMA, GARCH, VAR
- • Cointegration & Error Correction
- • Panel Data Models
- • Instrumental Variables
- • Maximum Likelihood
Machine Learning
- • Random Forest, XGBoost
- • Neural Networks
- • Dimensionality Reduction
- • Cross-Validation & Backtesting
- • Feature Engineering
Simulation & Monte Carlo
- • Historical Simulation
- • Monte Carlo Methods
- • Bootstrap & Resampling
- • Stochastic Processes
- • Copula-based Approaches
Who It Is For
Our quantitative services are aimed at organizations with demanding analytical requirements.
Financial Service Providers & Banks
Asset Managers & Family Offices
Consulting Firms
Corporate Finance
Industries
Banken & Kreditinstitute
Versicherungen
Fintech & Neobanken
Pensionsfonds
Asset Manager & Family Offices
Consulting Firms
Corporate Finance
Beispielprojekte
Anforderungen besprechen
Lass uns in einem unverbindlichen Gespräch klären, wie wir dich bei deinen quantitativen Fragestellungen unterstützen können.
Erstberatung buchen