Content from the Quantitative Finance book, covering pricing models, portfolio construction, execution strategies, model calibration, backtesting, and deployment of quantitative trading systems.
Master ethical quantitative trading by learning to detect spoofing, navigate Reg NMS and MiFID II, implement kill switches, and ensure data privacy compliance.
Master optimal position sizing using the Kelly Criterion, risk budgeting, and volatility targeting. Learn how leverage impacts drawdowns and long-term growth.
Build a robust quantitative research pipeline. From hypothesis formulation and backtesting to paper trading and live production deployment strategies.
Explore the architecture of quantitative trading systems. Learn to build robust data pipelines, strategy engines, risk controls, and execution infrastructure.
Explore market microstructure mechanics including order book architecture, matching algorithms, and order types. Master liquidity analysis and execution logic.
Master transaction cost analysis and market impact modeling. Estimate spread, slippage, and liquidity to build realistic backtests and execution strategies.
Master backtesting frameworks to validate trading strategies. Avoid look-ahead bias, measure risk-adjusted returns, and use walk-forward analysis for reliability.
Master event-driven trading strategies including merger arbitrage, earnings plays, and fixed income relative value. Learn deal probability modeling and risk management.
Explore cryptocurrency market microstructure, adjust quantitative strategies for extreme volatility, and manage unique risks in 24/7 decentralized trading.
Learn to extract trading signals from alternative data using NLP. Covers sentiment analysis, text processing, and building news-based trading systems.
Build ML-driven trading strategies covering return prediction, sentiment analysis, alternative data integration, and reinforcement learning for execution.
Learn supervised ML algorithms for trading: linear models, random forests, gradient boosting. Master feature engineering and cross-validation to avoid overfitting.
Master HFT strategies: cross-market arbitrage, latency exploitation, and electronic market making. Learn the tech infrastructure behind microsecond trading.
Learn how market makers profit from bid-ask spreads while managing inventory risk. Explore the Avellaneda-Stoikov model for optimal quote placement.
Master volatility as an asset class. Learn delta hedging, variance swaps, dispersion trading, and VIX strategies to exploit implied versus realized volatility.
Learn how to build long-short factor portfolios using quintile rankings. Covers value, momentum, quality, and volatility factors with exposure analysis.
Learn time-series and cross-sectional momentum strategies. Implement moving average crossovers, breakout systems, and CTA approaches with Python code.
Master mean reversion trading with cointegration tests, pairs trading, and factor-neutral statistical arbitrage portfolios. Includes regime risk management.
Learn quantitative trading fundamentals: alpha generation, strategy categories, backtesting workflows, and performance metrics for systematic investing.
Learn how to translate risk analytics into actionable controls through risk limits, hedging strategies, organizational governance, and regulatory frameworks.
Master liquidity risk measurement including market depth, funding liquidity, operational risk, and model validation. Covers LVaR and historical crises.
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.
Master credit risk measurement through Probability of Default, Loss Given Default, and Exposure at Default. Learn loan pricing and portfolio analysis.
Learn VaR calculation using parametric, historical, and Monte Carlo methods. Explore Expected Shortfall and stress testing for market risk management.
Master market, credit, liquidity, operational, and model risk. Learn Basel III capital requirements and risk management governance structures.
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.
Walk through the complete lifecycle of a quantitative trading strategy. Build a pairs trading system from scratch with rigorous backtesting and risk management.
Master execution algorithms from TWAP and VWAP to Almgren-Chriss optimal trading. Learn to balance market impact against timing risk for superior results.
Master interest rate swap valuation through bond portfolio and FRA methods. Learn curve bootstrapping, DV01 risk measures, and hedging applications.
Get notified when I publish new articles on data and AI, private equity, technology, and more.
No spam, unsubscribe anytime.
Create a free account to unlock exclusive features, track your progress, and join the conversation.