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NTHRYS › PhD Assistance › Mathematical Finance

Mathematical Finance

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Mathematical Finance

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Stochastic Volatility Models and Jump Diffusions
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Machine Learning for Option Pricing
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Optimal Execution and Market Microstructure
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High-Frequency Trading Algorithms
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Counterparty Credit Risk and CVA
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Multi-Curve Interest Rate Modeling
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Rough Volatility and Fractional Brownian Motion
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Portfolio Optimization with Transaction Costs
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Systemic Risk and Network Analysis
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Cryptocurrency and Blockchain Finance
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Regime-Switching and Hidden Markov Models
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American Option Pricing via Optimal Stopping
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Calibration and Parameter Inference Methods
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Term Structure of Credit Spreads
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Algorithmic Game Theory in Finance
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Affine Jump-Diffusion Models
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Quasi-Monte Carlo Methods for Finance
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Sentiment Analysis and Alternative Data
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Partial Differential Equations in Derivatives
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Factor Models and Asset Pricing
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Copula Theory and Dependence Modeling
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Reinforcement Learning for Trading
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Variance Reduction and Control Variates
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Leverage Effects and Volatility Clustering
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XVA Frameworks and Multiple Adjustments
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Functional Data Analysis in Finance
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Quantum Computing Applications Finance
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Structural Credit Risk Models
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Statistical Arbitrage and Pairs Trading
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Extreme Value Theory and Tail Risk
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Forward-Start Options and Exotic Derivatives
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Financial Network Models and Contagion
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Fourier Transform Methods in Finance
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Principal Component Analysis and Dimensionality
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Market Making and Inventory Management
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Behavioral Finance and Prospect Theory
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Green Finance and Sustainability Metrics
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Entropy Methods and Information Theory
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Basket Options and Spread Options
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Moment-Based and Spectral Methods
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Commodity Derivatives and Energy Markets
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Pandemic Risk and Epidemic Modeling
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Mortgage-Backed Securities and Prepayment
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Lattice Methods and Tree Models
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Fractional Calculus in Finance
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Regulatory Capital and Basel Framework
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Agent-Based Modeling of Markets
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Volatility Surface and Sticky Strikes
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Poisson and Levy Processes Applications
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Collateral and Rehypothecation Dynamics
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Deep Neural Networks for Volatility Forecasting
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Wasserstein Distance in Distribution Matching
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Causal Inference in Financial Markets
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Signature Methods and Path-Dependent Pricing
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Transformer Models for Sequential Price Data
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Normalizing Flows for Density Estimation
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Graph Neural Networks for Portfolio Analysis
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Variational Autoencoders for Scenario Generation
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Bayesian Non-parametric Methods in Finance
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Martingale Optimal Transport Theory
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Tensor Methods for High-Dimensional Pricing
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Physics-Informed Neural Networks for PDEs
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Market Microstructure and Tick Size Effects
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Information Geometry and Fisher Metric
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Sparsity and Compressed Sensing Methods
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Neural Ordinary Differential Equations Finance
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Optimal Stopping and American Derivatives
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Model-Free Hedging and Consistent Pricing
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Stochastic Control and Portfolio Selection
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Knightian Uncertainty and Ambiguity Aversion
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Kernel Methods and Support Vector Machines
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Time-Varying Correlation and Dynamic Copulas
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Measure Change and Girsanov Theorem Applications
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Anomaly Detection in Financial Data
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Generative Adversarial Networks for Finance
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Catastrophe Bonds and Extreme Risk Pricing
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Volatility Clustering and Long Memory
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Affine Processes and Closed-Form Solutions
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Semiparametric and Nonparametric Option Pricing
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Liquidity Risk and Bid-Ask Spread Modeling
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Stochastic Interest Rate Derivative Pricing
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Jump Clustering and Self-Exciting Models
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Implied Volatility Surface Dynamics
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Differential Privacy in Financial Data
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Stochastic Mesh and Monte Carlo Acceleration
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Meta-Learning for Rapid Model Adaptation
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Causal Forests and Treatment Effects
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Recurrent Neural Networks for Time Series
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Spectral Methods and Fourier Analysis
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Gaussian Processes for Derivative Pricing
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Time-Frequency Analysis and Wavelets
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Gradient Boosting for Risk Prediction
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Singular Spectrum Analysis of Market Data
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Malliavin Calculus and Greeks Computation
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Machine Learning Explainability in Trading
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Convex Optimization in Portfolio Theory
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Stochastic Differential Games and Competition
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Change Point Detection in Financial Series
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Martingale Representation and Risk-Neutral Pricing
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Data-Driven Model Discovery and Surrogate
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Stochastic Control and Mean Field Games
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Deep Neural Networks for Derivative Valuation
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Nonparametric Estimation of Volatility Surfaces
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Hawkes Processes and Self-Exciting Dynamics
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Causal Inference in Financial Time Series
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Optimal Stopping and Real Options Valuation
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Wavelets and Time-Frequency Analysis Finance
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Exponential Levy Models and Infinite Activity
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Optimal Transport and Wasserstein Distance
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Machine Learning for Credit Scoring
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Sparse PCA and Portfolio Construction
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Equilibrium Models with Incomplete Markets
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Bayesian Nonparametric Methods in Finance
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Graph Neural Networks for Financial Networks
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Martingale Optimal Transport Problems
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Functional Principal Component Analysis Assets
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Gaussian Processes for Term Structure Models
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Spectral Methods for Pricing Equations
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Signature Methods and Path Analysis
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Temporal Point Processes in Market Microstructure
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Convex Optimization for Risk Management
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Transfer Learning in Quantitative Finance
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Adaptive MCMC for Likelihood-Free Inference
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Stochastic Filtering and Hidden State Recovery
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Jump Risk Premia and Variance Swaps
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Robust Optimization and Uncertainty Sets
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Deep Generative Models for Asset Paths
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Moment Matching and Laguerre Expansions
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Information Geometry in Portfolio Theory
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Machine Learning for Interest Rate Curves
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Particle Methods and Sequential Monte Carlo
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Gromov-Wasserstein Distance for Model Comparison
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Influence Functions and Model Sensitivity
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Quantile Regression for Risk Quantification
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Attention Mechanisms and Transformers Finance
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Fractional Brownian Motion and Long Memory
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Fair Valuation under Model Uncertainty
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Graph Signal Processing in Finance
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Physics-Informed Neural Networks Finance
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Kernel Methods and SVM for Classification
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Nonlinear Dimension Reduction and UMAP
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Synthetic Data Generation for Privacy
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Markov Chain Monte Carlo for Calibration
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Contrastive Learning and Representation
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Copula-Based Dependency and Tail Modeling
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Causal Forests for Treatment Effect Estimation
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Implicit Neural Representations in Finance
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Neural Network Approximation of PDEs
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Stochastic Control and Optimal Stopping Problems
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Martingale Representation and Hedging Completeness
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Information Geometry and Statistical Divergences
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Deep Hedging with Neural Networks
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Volatility Derivatives and Variance Swaps
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Monte Carlo Simulation and Parallel Computing
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Backward Stochastic Differential Equations
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Multivariate Option Pricing under Dependence
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Stochastic Simulation and Model Risk
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Convex Optimization in Portfolio Management
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Numerical Methods for Stochastic Equations
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Interest Rate Swap Pricing and Curve Construction
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Anomaly Detection in Financial Markets
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Stochastic Optimization for Asset Allocation
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Non-Linear Filtering and Hidden State Estimation
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Sparse Portfolio Construction and L1 Regularization
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Spectral Methods and Fourier Analysis Applications
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Wiener Chaos Expansion and Homogenization
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Causal Inference in Financial Data
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Uncertainty Quantification in Model Parameters
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Approximation Theory and Basis Functions
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Graph Neural Networks for Credit Networks
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Nonparametric Density Estimation and Kernel Methods
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Optimal Transport and Wasserstein Geometry
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Functional Ito Calculus and Path-Dependent Derivatives
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Tensor Decomposition for High-Dimensional Problems
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Time-Varying Risk Measures and Dynamic Risk
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Wasserstein Distributionally Robust Optimization
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Kernel Methods and Support Vector Regression
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Measure Change and Numeraire Selection
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Asymptotic Analysis and Large Deviations
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Time Series Forecasting with LSTM Networks
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Energy Markets and Power Derivatives
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Indifference Pricing and Utility Maximization
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Variational Methods and PDE Constraints
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Cluster Analysis and Financial Market Segmentation
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Recombining Trees and Trinomial Models
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Adaptive Sampling and Importance Sampling Techniques
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Portfolio Theory under Market Frictions
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Calibration of Local and Stochastic Vol Models
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Convolutional Neural Networks for Market Prediction
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Game Theory and Competition in Finance
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Generative Adversarial Networks for Synthetic Data
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Rough Paths and Signature Methods
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Exotic and Structured Product Valuation
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Sparse Grids and High-Dimensional Integration
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Attention Mechanisms and Transformer Models
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Filtering and State Space Models in Finance
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Wasserstein Distance and Optimal Transport Finance
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Pathwise Sensitivity Analysis and Malliavin Calculus
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Market Impact Models and Price Prediction
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Optimal Transport and Wasserstein Distance Finance
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