Financial Risk Management
This new Financial Risk Management lecture series on YouTube completely replaces my earlier 2021 playlists on the same topic. The videos are still on YouTube if you have the link, but not listed. The old series required viewers to work through a long sequence of prerequisite mathematics videos before reaching the core FRM material.
In December 2025 I uploaded this new lecture course on YouTube, with 49 videos covering a coherent, end-to-end preparation for advanced undergraduate, postgraduate, and professional learners seeking a rigorous, industry-aligned understanding of financial risk management today. The 2025 series is rebuilt from the ground up to be accessible from almost any background — whether viewers come from mathematics, economics, finance, or none of these. I introduce all the required mathematics, statistics, and modelling ideas within each topic at the moment they are needed, so learners begin the real subject matter immediately and build the technical tools progressively.
Across eight fully updated topics, the series takes viewers from near-zero starting knowledge to interview-ready mastery of modern market-risk management, with complete coverage of banks and other financial institutions and the type of portfolios they need to risk manage, how to measure and hedge or mitigate market and credit risks from different types of instruments, including equities, forex, commodities and derivatives, Value-at-Risk and Expected Shortfall modelling, risk factor identification and mappings, systematic risk concepts, risk aggregation, backtesting internal models and stress testing portfolios, and a detailed treatment of the Basel Accords and the Fundamental Review of the Trading book.
In the following you will find a list contents with a link each of the eight playlists from its title. All playlists have six videos. Each topic (from Topic 3 onwards) has an interactive practical Excel-based workbook to illustrate the videos, and these are available to download from this website by clicking the link Excel Workbook # at the end of the contents list for each topic.
Hope you enjoy, and don’t forget to subscribe to my channel on YouTube!
TOPIC 1 — Introduction to Financial Risk Management
Part 1: What is Financial Risk Management?
Introduces financial risk management as the discipline of identifying, analysing and mitigating risks in financial markets, covering core motivations, typical sources of uncertainty and the overarching goal of protecting financial health while enabling opportunity.
Part 2: Financial Assets and Instruments
Explains the structure and purpose of key financial assets and instruments, highlighting their roles in markets, the types of exposures they create and how they contribute to overall portfolio risk.
Part 3: Companies and Institutions in Financial Markets
Describes the major players in financial markets, including banks, asset managers and other institutions, and outlines how their activities generate and transfer financial risks.
TOPIC 2 — Credit Risk Management
Part 1: Fixed Income Products
Provides an overview of loans, bonds, notes, swaps and structured products, explaining their cash-flow structures and how credit exposure arises across OTC and traded markets.
Part 2: Cash Flows and Net Present Value (NPV)
Introduces discounting, present value and cash-flow representation, showing how fixed and floating payments are valued and why forward curves matter for credit-risk modelling.
Part 3: Credit Risk: Spreads, Rating and Value-at-Risk (VaR)
Explains how credit spreads, ratings and probability of default link to valuation and risk measurement, and how credit VaR quantifies loss uncertainty arising from credit deterioration.
Part 4: What Drives the Interest Rate Swap (IRS) Market?
Discusses the structure of the IRS market, its reliance on forward-rate curves, liquidity channels and the economic motivations behind fixed–floating interest-rate exchanges.
Part 5: Credit Derivatives and the Banking Crisis
Reviews key credit derivatives and how their misuse contributed to systemic fragility in the banking crisis, illustrating the interaction between leverage, complexity and counterparty risk.
TOPIC 3 — Portfolios Returns and their Distributions
Part 1: Profit and Loss (P&L) and Returns
Defines P&L and returns, distinguishes realised and forward-looking measures and explains their role in modelling market risk at a chosen risk horizon.
Part 2: Normal Distributions
Introduces the normal distribution as a modelling tool for returns, covering key parameters, probability density and intuition for modelling uncertainty.
Part 3: Matrix Algebra
Reviews essential matrix tools for portfolio analysis, including vectors, matrices, transposes, products and how these support multivariate return modelling.
Part 4: Statistical Operators
Summarises expectation, variance, covariance and correlation, explaining their relevance for summarising and forecasting return behaviour.
Part 5: Portfolio Holdings and Weights
Explains how portfolios are constructed from holdings and weights, linking valuation, rebalancing and aggregation of individual asset exposures.
Part 6: Portfolio Volatility
Shows how portfolio volatility is computed using covariances and weights, highlighting diversification effects and the quantitative structure of portfolio-level market risk.
TOPIC 4 — Volatility and Value-at-Risk
Part 1: Defining Value-at-Risk (VaR)
Introduces VaR as a quantile-based loss measure, clarifying the role of the confidence level, risk horizon and keeping portfolio positions unchanged.
Part 2: Introducing VaR Models
Presents normal, historical and Monte Carlo VaR models, explaining key assumptions and how each constructs a predictive loss distribution.
Part 3: Building VaR Models
Describes the full VaR estimation workflow from selecting h and α to building return distributions and extracting quantiles for risk measurement.
Part 4: Comparison of VaR Models
Compares strengths and weaknesses of the main VaR models, focusing on responsiveness, data requirements and model risk.
Part 5: Creating Time Series of Volatility
Explains methods for estimating evolving volatility, including historical windows and volatility forecasting for use within VaR.
Part 6: Scaling VaR to Different Time Horizons
Shows how VaR scales with horizon under different assumptions, contrasting square-root-of-time scaling with more realistic alternatives.
TOPIC 5 — Fixed Income Portfolios
Part 1: Cash-Flow Portfolios and their Risk Factors
Introduces cash-flow portfolios, interest rate risk and the role of discounting in valuing future payments under changing yield curves.
Part 2: Mapping Cash Flows
Describes how cash flows are mapped onto risk-factor buckets using forward-rate curves to capture interest-rate sensitivity.
Part 3: Value at Risk for Cash-Flow Portfolios
Explains how VaR is computed for portfolios defined by future cash flows, including discounting and sensitivity to yield-curve movements.
Part 4: Example: VaR for a Gilts Portfolio
Walks through a complete gilt-portfolio VaR example using Bank of England yield-curve data and mapping techniques for rate sensitivities.
TOPIC 6 — International Equity and Commodity Portfolios
Part 1: Single Index Model
Introduces the single-index regression model, beta estimation and interpretation of systematic equity risk.
Part 2: VaR with One Equity Risk Factor
Shows how VaR is constructed when portfolio exposure is captured through a single market index and an estimated beta.
Part 3: Equity VaR with Multiple Risk Factors
Extends the VaR framework to multiple equity-sector factors, illustrating diversification and risk attribution.
Part 4: VaR for International Equity Portfolios
Adds exchange-rate risk as an additional factor, explaining cross-currency exposure and risk-factor construction.
Part 5: VaR for Commodity Portfolios
Explains how futures-based commodity portfolios are mapped to risk factors and how VaR captures price and curve risk.
TOPIC 7 — Risk Management for Options Portfolios
Part 1: Introduction to Options
Introduces calls and puts, moneyness, pay-offs and the economic role of options as leveraged, asymmetric instruments.
Part 2: The Black-Scholes Model
Presents the assumptions of the Black–Scholes model and explains how lognormal returns support option valuation.
Part 3: The Greeks
Describes delta, gamma, vega, theta and net position greeks and how they quantify sensitivity of option portfolio to underlying parameters.
Part 4: Mathematical Background
Reviews the essential calculus, probability and lognormal results that underpin the Black–Scholes formula.
Part 5: Hedging Options
Shows how Greeks are used to construct hedging strategies that neutralise different dimensions of option risk.
Part 6: Measuring VaR for an Options Portfolio
Explains how to compute VaR for nonlinear portfolios, comparing delta, delta–gamma and full-revaluation approaches.
TOPIC 8 — Capital Reserves for Market Risk
Part 1: Balance Sheets and Capital Reserves for Banks
Describes accounting and regulatory balance sheets, explaining why banks hold capital and how losses are absorbed during stress.
Part 2: Minimum Capital Ratios for Banks
Summarises Basel I–IV capital requirements and how risk-weighted assets determine the minimum capital ratio.
Part 3: Fundamental Review of the Trading Book
Explains FRTB’s trading-book boundary, sensitivities-based charges and the shift from VaR to Expected Shortfall.
Part 4: Validation of Internal Risk Models
Covers the regulatory standards for approving bank internal models, including tests of accuracy and stability.
Part 5: Statistical Backtests
Presents backtesting tools for assessing predictive accuracy of VaR and ES models, including exceptions and traffic-light rules.
Part 6: Scenario Analysis and Stress Testing Portfolios
Discusses stress testing frameworks that apply extreme but plausible market scenarios to assess portfolio resilience.