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He has worked for several years as a quantitative analyst for the company Thomson Reuters and for the banking group Unicredit Group in London and Milan. His area of specialty is mathematical finance, particularly mathematical models for calculating the price of financial derivatives. He has achieved his doctorate at the University of Cambridge in the UK, with a thesis on the numerical solution of partial differential equations as well as a degree in Physics at ITESM Campus Monterrey. He holds the Certificate in Quantitative Finance (CQF) of 7city Fitch Learning (London). He has taught at the graduate level and MBA Cambride universities, Oxford, Bocconi, Bergamo, Castellanza, the European School of Economics and the Indian Institute of Quantitative Finance (Mumbai). Alonso has published in the fields of quantitative finance, applied mathematics, neuroscience and the history of science. He has been awarded the Robert J. Melosh Medal (first place) of Duke University, USA, for the best work on finite element analysis; and the Rouse Ball Travelling Studentship in Mathematics, Trinity College, Cambridge. Dr. Peña as a researcher visited the Santa Fe Institute, USA, to study complex systems in the social sciences. His publications include: • He One Factor Libor Market Model Using Monte Carlo Simulation:An Empirical Investigation. • On the Role of Behavioral Finance in the Pricing of Financial Derivatives: The Case of the S&P 500. • Option Pricing With Radial Basis Functions: A Tutorial. • Application of extrapolation Processes to the finite element method. • On the Role of Mathematical Biology in Contemporary Historiography. • Enhanced visualization and quantification of diffusion tensor magnetic resonance imaging using the p:q tensor decomposition. • --Advanced Quantitative Finance with C ++¨”, Packt Publishing, 2014.

ALONSO PEÑA University of Cambridge


PART 1: 1. Credit Risk 1.1. Credit as an asset class 1.2. Some history of credit 1.3. Modelling credit risk 1.4. Structural & Intensity Models 1.5. Lab: Risk-free and risky cash Flows

2. Credit Derivatives 2.1. The credit derivatives markets 2.2. Single name & Multi name contracts 2.3. Example: The Credit Default Swap 2.4. Multi name contracts 2.5. Lab: Credit Default Swaps

3. Counterparty Risk: a primer 3.1. Exposure: definition 3.2. Instrument and Portfolio exposure 3.3. Netting and Collateral 3.4. Wrong Way Risk, Right Way Risk 3.5. Mark-to-market as a function of time 3.6. Exposure Profiles 3.7. Expected Loss Computation 3.8. Credit Valuation Adjustment (CVA) 3.9. Lab: Computing CVA by hand

4. Basic implementation 4.1. Interest rate swap CVA (static) 4.2. Spot Rates and Forward Rates 4.3. EURIBOR and LIBOR 4.4. Plain Vanilla IRS 4.5. IRS Exposure Profile 4.6. EXCEL Workshop: IRS mark-to-market (static) 4.7. EXCEL Workshop: IRS CVA (static)


5. Interest rate Modelling 5.1. The need for dynamic models 5.2. Modelling interest rates: short rate and market models 5.3. Hull-White model 5.4. LIBOR market model 5.5. Monte Carlo Simulation 5.6. C++ Workshop: Hull-White model 5.7. C++ Workshop: LIBOR market model

6. Interest rate swap CVA (dynamic) 6.1. IRS Exposure Profile (dynamic) 6.2. Plain Vanilla IRS using Monte Carlo Simulation 6.3. C++ Workshop: IRS mark-to-market (dynamic) 6.4. C++ Workshop: IRS CVA (dynamic)

Dr Jon Gregory is a partner at Solum Financial Partners LLP and specialises in counterparty risk and CVA related consulting and advisory projects. He has worked on many aspects of credit risk in his career, being previously with Barclays Capital, BNP Paribas and Citigroup.

JON GREGORY

Solum Financial Partners LLP

He is author of the book “Counterparty Credit Risk: The new challenge for global financial markets”, now in its second edition. Jon holds a PhD from Cambridge University. En 2001, fue co-autor del libro “Credit: The Complete Guide to Pricing, Hedging and Risk Management”, el cual fue pre-seleccionado para el Kulp-Wright Book Award por ser el texto más significativo en el campo de administración de riesgos y seguros. Jon tiene un Doctorado de Cambridge University.


PART 2: 1. Background Example: Analysis of a transaction executed precrisis • Historical overview • The OTC derivatives market • IFRS 13 and Basel 3 • xVA definitions • Setups 2. Exposure • Credit exposure and credit limits • EE, PFE and EPE • Quantification of exposure • Impact of nettingt • Funding exposure Example: Exposure simulation

5. Collateral • Credit support annex and terms • Variation and initial margins • Collateral calculation • Haircuts • Impact of collateral on credit exposure Example: Simulating the impact of collateral on exposure 6. Capital • Regulatory capital requirements • Review of capital methodologies • Capital value adjustment (KVA) • KVA examples Example: EAD and KVA calculations 7. Central Counterparties

3. CVA and DVA • Default probability calculation • CVA formula and examples • Bilateral CVA and DVA • The problems with DVA Example: CVA and DVA calculations 4. Funding and FVA • The source of funding costs • Defining FVA • FVA examples • Arguments over FVA • Market approach to FVA Example: CVA/DVA/FVA calculations

• The basics of central clearing • CCP mechanics • Direct and indirect clearing • CCP risk management • CCP risks 8. Initial Margin • Bilateral margin rules • Initial margin methodologies • The impact of initial margin on CVA and KVA • MVA Example: MVA calculations


REQUIREMENTS • Graduated from an economic and/or administrative career. • Preferably working in Financial Institutions. • Participants should bring a laptop.

Venue: JW MARRIOTT SANTAFE HOTEL. Av. Santa Fe 160 Col. La Fe Santa Fe, CDMX. Duration: 32 Hours (4 Sessions) Price: $35,000 MXN + TAX LIMITED OPENINGS

AGENDA: JUNE 20: 10:00 AM - 6:00 PM JUNE 21: 10:00 AM - 5:00 PM JUNE 22: 10:00 AM - 6:00 PM JUNE 23: 8:00 AM - 6:00 PM


REGISTRATION E-mail: derivatives@riskmathics.com Telephone: +52 (55) 5638 0367 +52 (55) 5669 4729

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IMPORTANT NOTICE: There will be no reimbursements.

Counterparty Risk CVA-xVA 2018 Ing  
Counterparty Risk CVA-xVA 2018 Ing