Conditional Probability of Exceedance (CPE): a nonparametric, live-deployed cross-asset tail co-movement signal framework across 161 instruments, plus multifractal predictability-limit research.
Applied quantitative financial risk management projects covering VaR/ES estimation, model validation, PCA/FA, copulas, and EVT-based tail-risk analysis.
End-to-End Python implementation of Regime-Weighted Conformal (RWC) prediction for sequential VaR control in nonstationary financial markets (Schmitt, 2026). Combines kernel-based regime similarity with exponential time decay to calibrate distribution-free risk bounds. CRSP data validation, GBDT quantile forecasting, and rigorous backtesting.
Code and data for "When Volatility Masquerades as Fragility". Hourly DeFi liquidation panel and quantile local projections of ETH returns, 2021-2025.
Simulation of tail risk noise and asset price
Evaluation of the impact of stale model calibrations on tail risk estimates from the perspective of statistical backtesting.
Extreme value analysis for insurance losses: POT/GPD, GEV with uncertainty, threshold diagnostics, return levels, body-tail splicing.
Portfolio risk an AI agent can drive and a person can read. Historical VaR and Expected Shortfall, signed linear exposure, explicit stress scenarios, counterparty exposure and XVA through a local ORE project. 4 MCP tools, 5 skills, a local dashboard and a hosted service. Research software, not investment advice. Noncommercial licence.
BlackRock group project: point-in-time macro tail-risk signals from public news.
Actuarial tail risk quantile/expectile regression for insurance pricing - TVaR, large loss loading, ILF curves, CatBoost
Does richer tail-risk feedback help a language model write a better trading reward? A pre-registered study across 11 models, five feedback arms and 568 seeds per comparison unit. MSc dissertation, UCL Institute of Finance and Technology.
Analyze cryptocurrency return dynamics, volatility, and risk from 2010–2025.
Predicting the probability of equity market crash events using historical return-based features, with a fixed crash definition and a focus on tail risk. The model is evaluated using the SPDR S&P 500 ETF (SPY) as a proxy for the S&P 500 Index, with data sourced via the yfinance API.
Option-implied tail-risk connectedness factor research pipeline
Size the 1-in-200 aggregate loss of two reinsurance books. A hard, programmatically verified agent-evaluation task where a Gaussian copula reproduces every marginal and every correlation and still misses by 57%.
Certified tail-risk abstraction for finite controller libraries (code-only release)
Correlation-network features that improve systemic tail-loss attribution beyond downside beta and conditional MES
Neural D-vine scenarios, mixed historical/synthetic training, and scenario-CVaR recurrent TD3 for constrained portfolio control.
Tail-robust multi-asset portfolio optimization using Gaussian/t-Copula scenarios and CVaR.
This toolbox contains a collection of skewed, and split parametric probability distributions often used in tail-risk applications.
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