Content from the Quantitative Finance book, covering pricing models, portfolio construction, execution strategies, model calibration, backtesting, and deployment of quantitative trading systems.
Master Black-Litterman models, robust optimization, practical constraints, and risk parity for institutional portfolio management.
Learn Brinson attribution for sector allocation and selection effects, plus factor-based methods to separate investment alpha from systematic beta exposures.
Master Sharpe ratio, Sortino ratio, information ratio, and maximum drawdown metrics. Learn to evaluate portfolios with Python implementations.
Learn Arbitrage Pricing Theory and multi-factor models. Master Fama-French factors, estimate factor loadings via regression, and decompose portfolio risk.
Master the Capital Asset Pricing Model: systematic risk, beta estimation, Security Market Line, and alpha. Essential foundations for asset pricing.
Learn model calibration techniques for quantitative finance. Master SABR, Heston, GARCH, and Vasicek parameter estimation with practical Python examples.
Learn Modern Portfolio Theory and mean-variance optimization. Master the efficient frontier, diversification mathematics, and optimal portfolio construction.
Learn PCA for extracting factors from yield curves and equity returns. Master dimension reduction, eigendecomposition, and risk decomposition techniques.
Master regression analysis for finance: estimate market beta, test alpha significance, diagnose heteroskedasticity, and apply multi-factor models with robust standard errors.
Learn GARCH and ARCH models for time-varying volatility forecasting. Master estimation, persistence analysis, and dynamic VaR with Python examples.
Master autoregressive and moving average models for financial time-series. Learn stationarity, ACF/PACF diagnostics, ARIMA estimation, and forecasting.
Master Black's model for pricing interest rate options. Learn to value caps, floors, and swaptions with Python implementations and risk measures.
Master the Heath-Jarrow-Morton framework and LIBOR Market Model for pricing caps, floors, and swaptions. Implement forward rate dynamics in Python.
Learn Vasicek and CIR short-rate models for interest rate dynamics. Master mean reversion, bond pricing formulas, and derivative valuation techniques.
Master exotic options pricing including Asian, barrier, lookback, and digital options. Learn closed-form solutions and Monte Carlo simulation methods.
Learn finite difference methods for option pricing. Master explicit, implicit, and Crank-Nicolson schemes to solve the Black-Scholes PDE numerically.
Learn antithetic variates, control variates, and stratified sampling to reduce Monte Carlo simulation variance by 10x or more for derivatives pricing.
Master Monte Carlo simulation for derivative pricing. Learn risk-neutral valuation, path-dependent options like Asian and barrier options, and convergence.
Learn binomial tree option pricing with the Cox-Ross-Rubinstein model. Price American and European options using backward induction and risk-neutral valuation.
Learn to compute implied volatility using Newton-Raphson and bisection methods. Explore volatility smile, skew patterns, and the VIX index with Python code.
Master option Greeks: delta, gamma, theta, vega, and rho. Learn sensitivity analysis, delta hedging, and portfolio risk management techniques.
Learn the Black-Scholes formula for European options with Python implementation. Covers derivation, the Greeks, put-call parity, and dividend adjustments.
Derive the Black-Scholes-Merton PDE using Itô's lemma, delta hedging, and no-arbitrage principles. Complete step-by-step mathematical derivation.
Learn the no-arbitrage principle, replicating portfolios, and risk-neutral probabilities. Master derivative pricing foundations used in quantitative finance.
Master Itô's Lemma with complete derivations and Python simulations. Learn stochastic calculus, geometric Brownian motion, and derivative pricing foundations.
Build mathematical models for random price movements. Learn simple random walks, Brownian motion properties, and Geometric Brownian Motion for asset pricing.
Explore the empirical properties of financial returns: heavy tails, volatility clustering, and the leverage effect. Essential patterns for risk modeling.
Master convertible bond valuation and analysis. Learn conversion ratios, pricing models, warrants, preferred stock, and hybrid security structures.
Master CDO mechanics, cash flow waterfalls, and correlation risk. Learn tranche valuation, the Gaussian copula model, and lessons from the 2008 crisis.
Learn CDS pricing using hazard rates and survival probabilities. Master credit risk valuation, implied default probabilities, and spread calculations.
Learn interest rate swap fundamentals: cash flow mechanics, day count conventions, LIBOR to SOFR transition, hedging strategies, and market structure.
Master option fundamentals including calls, puts, intrinsic value, time value, and put-call parity. Learn payoff diagrams and basic trading strategies.
Master forward and futures pricing with cost-of-carry models. Learn no-arbitrage strategies, basis risk, minimum variance hedge ratios, and portfolio hedging.
Learn FX market structure, currency forward pricing via covered interest rate parity, and hedging strategies. Master cross rates and forward valuation.
Master option strategies by combining basic building blocks. Learn to construct spreads, straddles, and iron condors to visualize payoffs and manage risk.
Learn commodity futures pricing with cost of carry models, convenience yield, contango and backwardation analysis, and optimal hedging strategies.
Master forward and futures contracts: learn payoff structures, margin requirements, daily settlement, and hedging strategies for effective risk management.
Learn to measure and manage bond interest rate risk using duration, convexity, and immunization. Master portfolio hedging and liability-driven investing.
Master yield curve construction through zero rates, forward rates, and bootstrapping. Learn to interpret curve shapes and build production-quality curves.
Master financial data handling with pandas, NumPy, and Numba. Learn time series operations, return calculations, and visualization for quant finance.
Learn bond pricing through present value calculations, yield to maturity analysis, and price-yield relationships. Master fixed income fundamentals.
Master equity market fundamentals including stock ownership, order book mechanics, trading execution, and key valuation metrics for quantitative finance.
Master root-finding, interpolation, and numerical integration for finance. Learn to compute implied volatility, build yield curves, and price derivatives.
Master continuous compounding, present value calculations, and differential equations. Essential tools for derivative pricing and financial modeling.
Master derivatives, gradients, and optimization techniques essential for quantitative finance. Learn Greeks, portfolio optimization, and Lagrange multipliers.
Master vectors, matrices, and decompositions for portfolio optimization, risk analysis, and factor models. Essential math foundations for quant finance.
Master moments of returns, hypothesis testing, and confidence intervals. Essential statistical techniques for analyzing financial data and quantifying risk.
Master probability distributions essential for quantitative finance: normal, lognormal, binomial, Poisson, and fat-tailed distributions with Python examples.
Master probability distributions, expected values, Bayes' theorem, and risk measures. Essential foundations for portfolio theory and derivatives pricing.
Master time value of money concepts: compounding, discounting, present value, annuities, and interest rate conventions essential for quantitative finance.
Master interest rate swap valuation through bond portfolio and FRA methods. Learn curve bootstrapping, DV01 risk measures, and hedging applications.
Learn how to translate risk analytics into actionable controls through risk limits, hedging strategies, organizational governance, and regulatory frameworks.
Master credit risk measurement through Probability of Default, Loss Given Default, and Exposure at Default. Learn loan pricing and portfolio analysis.
Master liquidity risk measurement including market depth, funding liquidity, operational risk, and model validation. Covers LVaR and historical crises.
Master market, credit, liquidity, operational, and model risk. Learn Basel III capital requirements and risk management governance structures.
Learn VaR calculation using parametric, historical, and Monte Carlo methods. Explore Expected Shortfall and stress testing for market risk management.
Master Credit Valuation Adjustment for derivatives pricing. Learn exposure profiles, default probability modeling, and the complete XVA framework.
Master credit risk modeling from Merton's structural framework to reduced-form hazard rates and Gaussian copula portfolio models with Python implementations.
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