
Econometrics, Portfolio Construction, and Risk
Estimate financial relationships, construct portfolios, measure performance, and manage market, credit, counterparty, liquidity, operational, and model risk.
Part of Quantitative Finance. The online chapters are free to read; the PDF edition is yours to keep, with future updates included.
Build the judgment to work confidently in quantitative finance.
Understand the assumptions behind a pricing model, the evidence behind a strategy, and the limits of a result. The book connects mathematical foundations to practical quantitative work so you can explain your choices and investigate what needs to change.
See what you’ll learnWhat you will learn
- Fit time-series, volatility, regression, factor, and calibration models without losing sight of estimation error and stability.
- Turn forecasts and views into portfolios using mean-variance optimization, factor models, Black-Litterman, robust optimization, and risk parity.
- Measure and control market, credit, counterparty, liquidity, operational, and model risk within a practical governance framework.
Who this volume is for
- Portfolio managers, risk professionals, researchers, and analysts who want to connect statistical models with allocation and risk decisions.
Prerequisites: A working knowledge of statistics is useful. The probability, statistics, and linear algebra chapters in Volume 1 provide a suitable refresher.
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Meet the community“I am enjoying reading your writings. I appreciate the effort you put into it. I want to drop a note of thanks. Thank you!”
“I would like to thank you for your work. Specifically, the chapter: 'LIME Explainability: Complete Guide to Local Interpretable Model-Agnostic Explanations' was extremely helpful for me in understanding LIME and communicating to colleagues. Your work is inspiring and valuable. Thank you for doing it.”
“I just came across your website where your books are available for free to read. Thank you so much for making this available to the public. This will help a lot of people.”
“I found your book Language AI Handbook's explanations of Transformer architectures and production deployment strategies to be exceptionally clear and insightful”
“Your writing feels like a treasure trove of great material. So, thank you for compiling everything on your website!”
“Really appreciate the way you have explained the concepts. Simple to understand, yet builds up knowledge exponentially, all while reinforcing it with examples repeatedly. I've read the last two chapters `74.Self-attention & 75.Q,K,V` and I've to admit, my concepts have never been clearer. You really are doing an amazing job breaking down maths and complex concepts like a story!”
“Thank you Michael. It's top!”
“I read a few of your blogs on NLP and oh WOW, they really are something, now I exactly know how all of the terms Entropy, Cross-entropy and how it is connected to Perplexity, will definitely read more of your blogs.”
“I came across your collection of online handbooks covering quantitative finance, AI, and machine learning. I wanted to reach out and thank you for making such high-quality material openly available. They are incredibly helpful for my CFA Level II review and for brushing up ahead of ML interviews.”
“Thanks so much for establishing such an amazing community. I appreciate the opportunity to be a learner and a contributor to the community.”
“Thanks for putting cool stuff out into the world.”
“I came across one of your books, Language AI Handbook, and man, I'm loving it. I've read many books but have never found such a comprehensive book on large models that covers everything from start to finish with such depth.”
Read all 12 reader reviews
“I would like to thank you for your work. Specifically, the chapter: 'LIME Explainability: Complete Guide to Local Interpretable Model-Agnostic Explanations' was extremely helpful for me in understanding LIME and communicating to colleagues. Your work is inspiring and valuable. Thank you for doing it.”
“Really appreciate the way you have explained the concepts. Simple to understand, yet builds up knowledge exponentially, all while reinforcing it with examples repeatedly. I've read the last two chapters `74.Self-attention & 75.Q,K,V` and I've to admit, my concepts have never been clearer. You really are doing an amazing job breaking down maths and complex concepts like a story!”
“Thanks so much for establishing such an amazing community. I appreciate the opportunity to be a learner and a contributor to the community.”
“I just came across your website where your books are available for free to read. Thank you so much for making this available to the public. This will help a lot of people.”
“I am enjoying reading your writings. I appreciate the effort you put into it. I want to drop a note of thanks. Thank you!”
“Thank you Michael. It's top!”
“Thanks for putting cool stuff out into the world.”
“I found your book Language AI Handbook's explanations of Transformer architectures and production deployment strategies to be exceptionally clear and insightful”
“Your writing feels like a treasure trove of great material. So, thank you for compiling everything on your website!”
“I came across your collection of online handbooks covering quantitative finance, AI, and machine learning. I wanted to reach out and thank you for making such high-quality material openly available. They are incredibly helpful for my CFA Level II review and for brushing up ahead of ML interviews.”
“I read a few of your blogs on NLP and oh WOW, they really are something, now I exactly know how all of the terms Entropy, Cross-entropy and how it is connected to Perplexity, will definitely read more of your blogs.”
“I came across one of your books, Language AI Handbook, and man, I'm loving it. I've read many books but have never found such a comprehensive book on large models that covers everything from start to finish with such depth.”
Exact contents
18 chapters across 3 parts
Every linked chapter is free to read online.
Part VIII: Econometrics and Statistical Modeling
- 01Time-Series Models for Financial Data
AR, MA, ARMA, ARIMA models for stationary and non-stationary financial time series.
- 02Modeling Volatility and GARCH Family
ARCH, GARCH models for time-varying volatility, volatility clustering, and forecasting.
- 03Regression Analysis for Financial Relationships
OLS regression, factor exposures, hypothesis testing, and addressing time-series regression issues.
- 04Principal Component Analysis and Factor Extraction
Dimension reduction, identifying principal components in yield curves and equity returns.
- 05Calibration and Parameter Estimation in Models
Fitting models to market data, optimization techniques, overfitting concerns, and model stability.
Part IX: Portfolio Theory and Investment Analysis
- 01Modern Portfolio Theory and Mean-Variance Optimization
Markowitz framework, efficient frontier, diversification benefits, and portfolio optimization.
- 02Capital Market Theory - CAPM and the Efficient Frontier
CAPM equilibrium, market portfolio, Security Market Line, beta, alpha, and model limitations.
- 03Arbitrage Pricing Theory and Multi-Factor Models
APT framework, multi-factor models, Fama-French factors, and factor risk premia.
- 04Portfolio Performance Measurement
Sharpe ratio, information ratio, maximum drawdown, benchmarking, and risk-adjusted returns.
- 05Performance Attribution and Investment Alpha
Brinson attribution, factor-based attribution, separating alpha from beta exposures.
- 06Advanced Portfolio Construction Techniques
Black-Litterman model, robust optimization, risk parity, and practical constraints.
Part X: Risk Management and Financial Risk Controls
- 01Overview of Financial Risks and Regulatory Frameworks
Market, credit, liquidity, operational, model risk; regulatory standards and risk management objectives.
- 02Market Risk Measurement - VaR and Beyond
Value-at-Risk calculation methods, Expected Shortfall, stress testing, and scenario analysis.
- 03Credit Risk Fundamentals
Probability of Default, Loss Given Default, Exposure at Default, and expected loss calculations.
- 04Credit Risk Modeling Approaches
Structural models (Merton), reduced-form models, credit scoring, and portfolio credit risk.
- 05Counterparty Risk and CVA
Counterparty default risk, Credit Valuation Adjustment, exposure profiles, and CVA hedging.
- 06Liquidity Risk and Other Non-Market Risks
Market and funding liquidity risk, operational risk, model risk, and qualitative assessments.
- 07Risk Management Practices and Policies
Risk limits, hedging strategies, CRO role, risk committees, and firm-wide risk culture.
Choose the edition that fits your next step
Volume 3: Econometrics, Portfolio Construction, and Risk
770 pages focused on this subject, with future updates included.
$29
Choose this volumeThe complete Quantitative Finance library
All-volume access with separate volume PDFs and future updates. No combined PDF.
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Get all-volume accessExplore the other volumes

Volume 1 · 883 pages
Foundations and Financial Instruments
Mathematics · Equity and Fixed Income · Forwards, Futures, Options, Swaps, and Credit

Volume 2 · 664 pages
Derivative Pricing and Interest Rate Models
Stochastic Calculus · Options · Numerical Pricing · Rate Models

Volume 4 · 1011 pages
Quant Trading, Execution, and Deployment
Trading Strategies · Market Microstructure · Backtesting · Production Systems
Author and edition details
About the author and this edition

Michael Brenndoerfer
Michael has spent more than a decade working across software engineering, data, AI, and business. He writes to understand difficult ideas more deeply and to share what he learns in a clear, practical way.
Important: This book is for education and research. It does not provide investment, trading, legal, tax, or other professional advice, and examples are not recommendations.
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- First edition
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Version history
Kept current, not frozen in time
Library access includes every future volume and update. When a volume changes, its updated PDF appears in My books at no extra cost.
Current release
Edition 2026.08.1
Editorial improvements.
Earlier releases2
2026.08.0
Editorial improvements throughout the book, with clearer explanations, refined presentation, improved plots and visualizations, and refreshed companion code.
2026.07.0
Initial complete-book and four-volume PDF release with companion notebooks.