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Curriculum / Phase 2 · Core Quantitative Finance

Quantitative Risk Management

Study quantitative risk management through loss distributions, tail risk, dependence, credit risk and model validation.

Why study Quantitative Risk Management?

A single risk number hides choices about horizons, distributions, dependence and extreme events. Learn to explain those choices and examine what happens when the historical pattern stops being a useful guide.

Who this is for

For aspiring market, credit and model-risk analysts with statistical inference and financial-market foundations.

What you should be able to do

  • Interpret VaR, expected shortfall and risk-measure backtesting.
  • Study volatility, extreme losses and dependence.
  • Connect market and credit risk models to stress testing and governance.

An example of the work this prepares you for

A risk report comparing loss estimates, stress scenarios and backtesting evidence, with clearly documented limitations.

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.

Describe potential losses

Interpret a risk measure in relation to its horizon and assumptions.

Challenge the tail

Assess dependence and severe scenarios beyond an average market day.

Validate a risk model

Translate diagnostics into an explanation a reviewer can act on.

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 previewRisk in Perspective and the Regulatory Framework3 lessonsTopic previewLoss Distributions, VaR, and Coherent Risk Measures7 lessonsTopic previewEmpirical Properties of Financial Data and GARCH Volatility Models4 lessonsTopic previewExtreme Value Theory6 lessonsTopic previewMultivariate Models and Copulas7 lessonsTopic previewMarket Risk4 lessonsTopic previewCredit Risk — Single Name4 lessonsTopic previewPortfolio Credit Risk and Credit Derivatives5 lessonsTopic previewOperational Risk and Insurance Analytics2 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

    Coherent Measures of Risk

    Philippe Artzner, Freddy Delbaen, Jean-Marc Eber and David Heath

    Read the foundational paper on desirable risk-measure properties; find its Directory record alongside the source.

    View research in Directory →

  2. Textbook · Free

    Forecasting: Principles and Practice

    Rob J Hyndman and George Athanasopoulos · third edition

    Strengthen the forecast evaluation skills needed to assess risk estimates.

  3. University course · Free

    Foundations of Financial Engineering

    Columbia · Martin Haugh

    Use the credit-modelling notes as a bridge from default concepts to models.

  4. University course · Free

    Topics in Mathematics with Applications in Finance

    MIT OpenCourseWare · 18.S096

    Review financial probability and simulation through university lectures.

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 the derivative exposures underlying many risk reports.

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

  • Risk and Model Validation Quant · required programme

Ready to study Quantitative Risk Management? Explore membership for access to the complete lessons.

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Phase 2Portfolio Theory and Quantitative InvestmentStudy portfolio optimisation, diversification, factor models and performance evaluation for quantitative investment.Phase 2Derivatives Pricing and Computational FinanceLearn option pricing and hedging through no-arbitrage, Black–Scholes, binomial trees and Monte Carlo methods.Phase 2Fixed Income and Interest-Rate ModelsStudy bond pricing, yield curves, interest-rate risk and no-arbitrage term-structure models.Phase 2Quantitative Research, Data and BacktestingLearn to design financial research with point-in-time data, time-ordered validation and economically realistic backtests.Phase 2Market Microstructure and ExecutionStudy order books, liquidity, market impact and execution analysis from market data to executed positions.Phase 2Professional Quant PracticeDevelop the reproducibility, documentation, validation and communication practices used in quantitative model work.