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Counterparty Credit Risk and CVA

Study counterparty credit exposure, CVA, DVA, collateral and Monte Carlo exposure simulation.

Why study Counterparty Credit Risk and CVA?

A derivative’s value depends on whether the promised future payments will be made. Exposure, default dependence and collateral connect pricing to counterparty risk, and require care about the timing and legal scope of a trade.

Who this is for

For derivatives and risk learners who understand risk-neutral pricing, credit risk and Monte Carlo simulation.

What you should be able to do

  • Connect exposure profiles and bilateral default to CVA and DVA.
  • Analyse wrong-way risk, netting and collateral.
  • Study simulation, sensitivity and validation of exposure models.

An example of the work this prepares you for

An exposure and bilateral valuation study that explains netting assumptions, default dependence and simulation uncertainty.

Prerequisites and suggested preparation

You should be comfortable with the background covered in these programmes. Equivalent knowledge from university study or independent learning is also suitable.

The goal is to use the foundations in context: explain the assumptions, carry out a calculation and interpret the result. If one of those steps feels unfamiliar, review the linked preparation first.

A preview of the learning journey

The lessons build towards these kinds of reasoning and practical work.

Understand future exposure

Distinguish today’s value from possible amounts at risk later.

Connect exposure and default

Explain how dependence changes a credit adjustment.

Assess a mitigation assumption

Recognise how netting and collateral change residual risk.

Members work through the detailed lessons, derivations, worked examples and solutions inside the learning dashboard.

Explore lesson previews by topic

Open a topic preview to see its introduction, learning objectives and prerequisites. Previous and next links let you explore the lessons in study order. Full lessons are available in the member dashboard; selected samples are free to read in full.

Topic previewExposure and Default2 lessonsTopic previewCVA, DVA and Wrong-Way Risk3 lessonsTopic previewNetting and Collateral2 lessonsTopic previewCVA Computation and Validation2 lessons

Free resources to start learning

Use these alongside the programme or to prepare independently. Start with the introductory material, work through an example, then return to the research papers when the underlying ideas are familiar.

  1. Research paper · Free

    Counterparty Risk FAQ

    Damiano Brigo

    Start with the terminology and conceptual distinctions; some sections extend beyond this programme’s bilateral scope.

  2. Research paper · Free

    Bilateral counterparty risk valuation for interest-rate products

    Damiano Brigo, Andrea Pallavicini and Vasileios Papatheodorou

    Study bilateral default and rates dependence; this paper does not provide a complete collateral treatment.

  3. University course · Free

    Foundations of Financial Engineering

    Columbia · Martin Haugh

    Review credit modelling and term-structure foundations.

  4. University course · Free

    Topics in Mathematics with Applications in Finance

    MIT OpenCourseWare · 18.S096

    Review stochastic processes before implementing exposure simulations.

Optional textbook reference

These books are paid references. Check your university or public library for access.

  1. Textbook · Paid / library

    Options, Futures, and Other Derivatives

    John C. Hull · Pearson

    Optional textbook for derivatives and counterparty-risk background.

Links reviewed 14 October 2026. Free refers to the linked reading, notes or videos; printed books and certificates may cost extra.

Find more papers and learning materials in the SelfMadeQuant Directory.

Where this programme fits

  • Derivatives Pricing and Model Quant · required programme
  • Risk and Model Validation Quant · required programme

Ready to study Counterparty Credit Risk and CVA? Explore membership for access to the complete lessons.

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