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Basel Credit Regulatory Capital for Banking and Trading Books

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Chapter 4 ends where bank capital rules meet the models you just read about. Expected loss is for provisions and pricing. Tail unexpected loss is what regulators want capital for. Basel turned that idea into formulas banks run every reporting cycle.

Hedging Credit Risk With CDS and Index Products

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Banks do not just measure credit risk. They hedge it. Credit derivatives turned issuer risk into something you can buy and sell like any other market exposure. Chapter 4 closes the modeling sections with how these instruments work and what drives their prices.

What New Generation Portfolio Credit Models Need

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Many bank credit portfolio models date to the Basel II era around 2005 to 2010. They were built for one-year economic capital, concentration measurement, and comparing internal capital to summable RWA. That was enough then. CCAR, EBA, and multi-year stress requirements changed the job description.

Credit Risk Stress Testing for Banking Portfolios

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Market risk stress tests got plenty of airtime in Chapter 3. Credit stress testing is at least as important for most banks. CCAR and EBA firmwide exercises live or die on what happens to the loan book under bad macro scenarios.

Firmwide Portfolio Credit Risk and Dependence Structures

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

By this point in Chapter 4 you have two parallel worlds: Merton-style models for bonds and large corporates, and scorecard models for retail pools. Banks do not run them in silos forever. They need a firmwide credit risk view. This section explains how the pieces fit together.

Banking Book Credit Models: Binomial Loss and Scorecards (Part 1)

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

After wholesale bonds and loans, Chapter 4 turns to the banking book: mortgages, credit cards, consumer loans, and small business exposures. These borrowers do not have traded equity or public debt. But the portfolios are huge, so pool behavior is statistically stable even when each loan is small.

Portfolio Credit Risk: Issuer Credit in the Trading Book (Part 1)

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Chapter 4 is where the book stops talking mostly about market risk and starts on credit risk. For most banks, credit in the banking and trading books is the biggest risk they carry. The 2007 crisis made that painfully obvious, and Basel III tightened the rules that followed.

Portfolio Optimization and Market Risk Regulation

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Markowitz gave us the efficient frontier in variance. Skoglund and Chen ask a harder question: what does the frontier look like when returns are not normal, the book has options, and regulators are switching from VaR to CVaR with liquidity buckets?

Scenario Analysis and Stress Testing

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

VaR looks backward. Stress testing looks forward. Skoglund and Chen treat them as partners, not rivals, and lay out a four-part program every serious market risk desk should recognize.

VaR Time Scaling and Market Liquidity Risk

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Your desk reports 1-day VaR. Regulators want 10-day VaR. Someone multiplies by √10 and calls it a day. Skoglund and Chen explain why that shortcut fails, and why how you exit a book matters as much as how you model it.

Coherent Risk, Distortion Measures, and Spectral Risk

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

The first half of Chapter 3’s risk-measure section is about counting and splitting risk. This stretch is about choosing how much weight to put on different parts of the loss distribution, and using information theory to find the scenarios that actually matter.

Simulation-Based Market Risk: Monte Carlo, Barriers, PCA, and Grid Pricing

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Linear and quadratic models are fast. But some positions laugh at Taylor expansions. Barrier options, exotics, and a thin slice of complex trades can drive most of the tail risk even when the rest of the book is plain vanilla. This section is where Skoglund and Chen say: stop approximating, reprice under scenarios.

Market Risk Linear Portfolios: Delta Method and VaR Under Normality

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Chapter 2 opens with a honest disclaimer: assuming multivariate normal risk factor returns is wrong for daily financial data. Fat tails and volatility clustering are real. But the normal linear model is still the baseline because it is fast, interpretable, and most of the machinery (covariance, Euler decomposition, time scaling) carries over to harder models later.

Banks and Risk Management: Skoglund & Chen Chapter 1 Explained

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

Chapter 1 is the on-ramp. Skoglund and Chen do not jump straight into VaR formulas. They ask a harder question first: why does risk management exist in banks at all, and why did regulators and shareholders both decide it was worth billions in systems and headcount?

Starting the Skoglund & Chen Financial Risk Management Book Series

Financial Risk Management by Jimmy Skoglund and Wei Chen (ISBN 978-1-119-13551-7)

I picked up this book because most risk texts either go deep on one topic or stay abstract. Skoglund and Chen wrote something different: a full-stack practitioner guide that walks from bank foundations through market and credit models, liquidity and transfer pricing, and firmwide aggregation. They built it from years inside banks and risk tech vendors, not from a lecture hall.