Financial Engineering Course

Lesson 1 • Programming and Data Environments

Introduces scripting languages and data-handling libraries used in quantitative finance. Prepares students to implement models computationally from chapter two onward.

Lesson 2 • Core Concepts in Finance

Introduces time value of money, risk-return tradeoffs, and market efficiency. Provides the economic intuition behind every pricing and hedging technique.

Lesson 3 • Statistical Tools for Finance

Applies regression, hypothesis testing, and time-series analysis to financial data. Connects statistical inference to model validation and risk estimation.

Lesson 1 • Yield Curve Construction

Teaches bootstrapping and interpolation methods to extract zero and forward rates. Connects market quotes to the term structure used in derivative pricing.

Lesson 2 • Bond Valuation Fundamentals

Derives bond prices from discounted cash flows and explains yield-to-maturity. Anchors fixed income pricing within the no-arbitrage framework from chapter one.

Lesson 3 • Structured Fixed Income Products

Examines securitization mechanics and cash flow waterfalls in structured products. Extends bond pricing skills to more complex multi-tranche instruments.

Lesson 4 • Duration, Convexity, and Sensitivity

Quantifies price sensitivity to interest rate changes using duration and convexity. Builds the hedging intuition applied in later chapters on derivatives.

Lesson 1 • Forwards and Futures Mechanics

Derives forward prices via cost-of-carry and explains futures margining. Introduces the first class of derivative instruments built on no-arbitrage pricing.

Lesson 2 • Introduction to Option Pricing

Presents the binomial tree model and risk-neutral valuation for European options. Lays the conceptual groundwork for the Black-Scholes model in the next chapter.

Lesson 3 • Options Payoffs and Strategies

Defines call and put payoffs, intrinsic value, and time value. Introduces spread and combination strategies as building blocks for structured products.

Lesson 1 • Extensions of the Black-Scholes Model

Adapts the framework for dividends, foreign exchange, and commodity underlyings. Broadens the model's applicability across asset classes covered in later chapters.

Lesson 2 • Black-Scholes-Merton Derivation

Derives the Black-Scholes PDE via delta hedging and solves it for European options. Connects the continuous-time framework to the binomial model from chapter three.

Lesson 3 • Implied Volatility and the Smile

Extracts implied volatility from market prices and analyses the volatility surface. Reveals model limitations and motivates stochastic volatility extensions.

Lesson 4 • The Greeks and Sensitivity Analysis

Computes delta, gamma, vega, theta, and rho for vanilla options. Enables dynamic hedging and risk management of option portfolios.

Lesson 1 • Exotic Interest Rate Products

Prices Bermudan swaptions, range accruals, and CMS products using numerical methods. Extends calibrated models to path-dependent and early-exercise rate derivatives.

Lesson 2 • Caps, Floors, and Swaptions

Values interest rate caps, floors, and swaptions using Black's formula and market models. Applies calibrated models to real hedging and structuring problems.

Lesson 3 • Short-Rate Models

Presents Vasicek, Cox-Ingersoll-Ross, and Hull-White models for the short rate. Connects stochastic calculus from chapter four to term structure dynamics.

Lesson 4 • LIBOR Market Model

Derives the BGM model for discrete forward rates and calibrates it to caplet prices. Enables direct pricing of caps, floors, and swaptions from market data.

Lesson 1 • Portfolio Credit Risk and Correlation

Quantifies joint default risk using copula functions and factor models. Introduces the correlation sensitivity central to CDO tranche pricing.

Lesson 2 • Credit Default Swap Mechanics

Explains CDS cash flows, premium and protection legs, and par spread calculation. Builds on risky bond pricing from chapter two to introduce the CDS market.

Lesson 3 • Intensity-Based Credit Models

Models default as a Poisson arrival process with stochastic intensity. Provides the continuous-time credit framework analogous to short-rate models.

Lesson 4 • Counterparty Credit Risk

Measures CVA, DVA, and FVA for OTC derivative portfolios. Connects credit modelling to the valuation adjustments required under modern accounting standards.

Lesson 1 • Liquidity Risk Measurement

Quantifies market liquidity risk through bid-ask spreads, market impact, and liquidity-adjusted VaR. Addresses funding liquidity and its interaction with market risk.

Lesson 2 • Expected Shortfall and Coherent Measures

Introduces expected shortfall as a coherent alternative to VaR and its regulatory role. Connects tail risk measurement to capital allocation and stress testing.

Lesson 3 • Stress Testing and Scenario Analysis

Designs historical and hypothetical stress scenarios to assess portfolio resilience. Provides the forward-looking risk assessment required by supervisory frameworks.

Lesson 4 • Value at Risk Methodologies

Derives VaR using historical simulation, variance-covariance, and Monte Carlo methods. Establishes the primary risk metric used across trading desks and regulatory reports.

Lesson 1 • Mean-Variance Optimization

Derives the efficient frontier and optimal portfolios using Markowitz's framework. Connects return and covariance estimation to practical portfolio construction.

Lesson 2 • Derivative Overlays and Hedging Programmes

Integrates options, futures, and swaps into portfolio management for risk reduction and return enhancement. Synthesizes derivative pricing skills from earlier chapters into a portfolio context.

Lesson 3 • Factor Models for Portfolio Management

Decomposes portfolio risk into systematic and idiosyncratic components using factor models. Enables risk attribution and factor-based portfolio construction.

Lesson 4 • Transaction Costs and Rebalancing

Incorporates transaction costs and turnover constraints into the optimization problem. Bridges theoretical optimal portfolios with implementable trading strategies.