IB1.1. What Investment Banking Actually Does: A Practical Guide
Investment banking is the business of helping organisations raise, deploy or restructure capital. This post sets out what the industry is and…
Q2.8. Model Validation: What Regulators Actually Ask
A model can be statistically sound and still fail validation, because validation asks whether it survives independent challenge. This post covers the…
Q2.6. Low Default Portfolios: Rating Models With No Data
A low default portfolio is one where defaults are too rare to estimate PD by counting them — and in emerging-market banks…
Q2.5. Through-the-Cycle vs Point-in-Time PD Explained
Through-the-cycle and point-in-time PD are two legitimate answers to what looks like one question, and they can differ by a factor of…
Q2.4. PD, LGD and EAD: The Three Numbers in Credit Risk
Every credit risk model reduces to three numbers: probability of default, loss given default, and exposure at default. This post works through…
Q2.3. Stress Testing: Scenarios That Actually Matter
Statistical risk measures can only describe what their data contains. Stress testing asks what happens when something unprecedented occurs. This post separates…
Q2.2. Expected Shortfall: The Fix for What VaR Misses
Expected shortfall answers the question VaR refuses to: not where the threshold sits, but how bad losses get beyond it. This post…
Q2.1. Value at Risk Explained: What the Number Hides
Value at Risk is a single comparable number across every desk in a bank, which is why it spread so fast —…
Q2.7. IFRS 9 Expected Credit Loss for Vietnamese Banks
IFRS 9 requires provisions from the day a loan is written, and for Vietnamese banks it runs alongside the State Bank's own…
Q1.11. Monte Carlo Option Pricing: 40 Lines of Python Explained
Monte Carlo simulation is the pricing method that scales to payoffs no formula can handle. This post builds a working option pricer…