QuantMinds 2020: Modelling Energy Curves for XVA
This on-demand webinar offers insights and commentary across several areas including: Seasonality in volatilities & correlations for energy curves; oil, gas, power, etc. | XVA & the importance of correlations | The Andersen ('10) model, akin to Cheyette ('92) with seasonality in response functions | Estimation via state-space representation and filtering | akin to Dynamic Nelson-Siegel (’06) | Objective measure-vs.-pricing measure implications and handling stochastic volatility.
QuantMinds International showcases the latest expert thinking on the fundamental topics at the core of quant finance including, volatility and option pricing, interest rate modelling and IBOR, FX and commodities, risk, regulation and liquidity, XVA and model risk.
In November 2020, Dr. Andrew McClelland, Senior Vice President of Quantitative Research, Numerix presented his latest research via this digital event.
Fill out the form to review his session which offers insights and commentary across several areas including:
- Seasonality in volatilities & correlations for energy curves; oil, gas, power, etc.
- XVA (valuation adjustments), i.e. CVA, & the importance of correlation
- The Andersen ('10) model, like Cheyette ('92) with seasonality in response functions
- Practical calibration via method-of-moments on empirical covariance matrices
- Maximum likelihood via filtering, extending to stochastic vol & jumps
Featured Speakers
Andrew McClelland, Ph.D.
Andrew McClelland’s quantitative research at Numerix focuses on XVA pricing and hedging, generating counterparty credit risk metrics for structured products, and estimating risk model parameters via time-series estimation. He earned his PhD in finance at the Queensland University of Technology for a thesis on financial econometrics. He considered markets exhibiting crash feedback, option pricing for such markets, and parameter estimation for such markets using particle filtering methods. Dr. McClelland’s work has been published in the Journal of Banking and Finance, the Journal of Econometrics, and the Journal of Business and Economic Statistics.
