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Outline:

Foundations: CVA, DVA and FVA 

  • CVA & DVA by Replication
  • Credit Mitigants
  • FVA by Replication
  • FVA & DVA (overlaps)
  • FVA in pricing and accounting
  • A brief tour of the XVA Monte Carlo engine

MVA 

  • Initial Margin and XVA
  • MVA by Replication
  • MVA for VaR-type IM (CCPs)
  • MVA for SIMM-IM

KVA 

  • What is Capital?
  • KVA by Replication
  • KVA vs Hurdle Rates
  • Which measure?
  • The Cost of Capital

Introducing Machine Learning 

  • Types of machine learning problem:Motivation I: Multivariate Linear Regression
    • Supervised learning
      • Regression problems
      • Classifier problems
    • Unsupervised learning
  • Motivation II: Logistic Regression
  • Bias and Variance
  • Regularization
  • Neural Networks
    • Activation functions
    • Geometry
    • Forward and backpropagation
    • Initialization
  • Deep Learning 

Credit Curve Mapping as a Machine Learning Problem 

  • Dealing with Illiquid counterparties in XVA
  • Key Requirements of the Map
    • Trading Requirements
    • Regulatory Requirements: Basel III & FRTB-CVA
  • Classical Methods
  • Classifier Approach
  • Regression Approach 

A tour of XVA ML Applications 

  • Optimising MVA
  • Dimension Reduction: PCA & Autoencoders

Tutor Biography

Andrew Green: Managing Director and XVA Lead Quant, ScotiabankImage result for andrew green scotiabank

 

Andrew Green is a Managing Director and lead XVA Quant at Scotiabank in London. Prior to joining Scotiabank, Andrew held roles as a quantitative analysis in several different banks in London. He is the author of XVA: Credit, Funding and Capital Valuation Adjustments, published by Wiley. 


Workshop Schedule: 09:00 – 17:30 

Break: 10:30 – 10:45
Lunch: 12:30 – 13:30
Break: 15:15 – 15:30