Stochastics, Optimization, and Algorithms
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Statistical Methods
- Regularized principal component analysis
- Inference for point processes and jump-diffusion
- Risk measure estimation
- Affine modeling calibration theory
- Robust large-dimensional factor modeling State-varying factor models of large dimension
- High-frequency factor modeling
Monte Carlo Simulation
- Efficient rare-event algorithms
- Exact sampling schemes for stochastic differential equations
- Discretization methods
- Sampling algorithms for point processes
- Multi-level methods
Optimization
- Stochastic Programming
- Optimization tools for machine learning
- Numerical optimization methods
- Warm starting approaches
High Performance Computing
- Parallel structures
- GPU computing
- Quantum computing