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RiskLab research

Financial intelligence

MIF

Machine Intelligence for Finance

Statistical learning, validation, portfolio construction, and numerical methods for financial decisions.

Notebooks
Part IMathematical and Computational Foundations
Chapter 1The Mathematical Language of Financial LearningChapter 2Synthetic Financial EnvironmentsChapter 3Generative Models for Financial Time SeriesChapter 4Measuring Ambiguity in Probability Laws
Part IISampling and Statistical Representation
Chapter 5Event-Based Measures of Financial TimeChapter 6From Event Detection to Financial LabelsChapter 7Weighting Samples with Overlapping InformationChapter 8Fractional DifferentiationChapter 9Measuring Dependence with Geometry and InformationChapter 10Denoising High-Dimensional Covariance Matrices
Part IIIMarket Structure and Learning
Chapter 11Market Microstructure from PricesChapter 12Detecting Structural Breaks and Explosive DynamicsChapter 13Adapting to Regime ChangeChapter 14Feature Importance under DependenceChapter 15Clustering Predictors for Ensemble Learning
Part IVValidation and Statistical Evidence
Chapter 16Temporal Cross-ValidationChapter 17Combinatorial Purged Cross-ValidationChapter 18Hyperparameter Selection under DependenceChapter 19Probability of Backtest OverfittingChapter 20Adjusting Sharpe Inference for Multiple TestingChapter 21Measuring Tail Risk from Extreme EventsChapter 22Managing Position Size under Performance Risk
Part VPortfolios and Financial Systems
Chapter 23Portfolio Geometry under Covariance UncertaintyChapter 24Portfolio Concentration through MajorizationChapter 25Hierarchical Risk ParityChapter 26Nested Cluster Methods for Portfolio Construction
Part VINumerical Finance and Decisions
Chapter 27Decision-Focused Learning for Robust Portfolio ChoiceChapter 28Proportional Clearing in Financial NetworksChapter 29Solving High-Dimensional PDEs with Deep BSDE MethodsChapter 31Deep HedgingChapter 32From Faster Calculations to a Complete Research Study
AppendixSoftware Design
Appendix AHow RiskLabAI Is Built

CIM

Causal Investment Management

Causal questions, identification, estimation, policy choice, and portfolio decisions under explicit assumptions.

Notebooks
Part IIdentification and Evidence
Chapter 1Reading Causal Roles from GraphsChapter 2Graphical IdentificationChapter 3Structural Models and Treatment EffectsChapter 4The Factor MirageChapter 5Sensitivity Analysis under Partial IdentificationChapter 6Transporting Effects across PopulationsChapter 7Causal Effects with Network Interference
Part IIInvestment Decisions
Chapter 8Portfolio Choice after Model SearchChapter 9Off-Policy Evaluation and Policy SelectionChapter 10A Research Protocol for Causal Factor Investing