Lab

4,000-page e-textbook+AI tutor on
Machine Learning for Quantitative Finance

E-Textbook

Theory

Mathematical formalism, for faster learning

Case studies

Applications, for deeper learning

Complementary Learning Resources

AI tutor

Your personal tutor, for personalized learning

Code

Learn by doing, no installation

Animations

Intuition in motion

Proofs

Don't believe, verify

Exercises

Code based and analytical

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Lab - Overview

The Lab is a multi-channel e-textbook, designed to be the complete study resource for the ARPM curriculum:

Machine Learning

Quantitative Finance

Mathematical Statistics for Finance

Mathematical Statistics for Finance Linear/probabilistic statistics and decision theory for estimation/sequential decisions

Mean-Covariance Learning

Mean-Covariance Learning Analytically tractable foundations of AI

Financial Engineering

Financial Engineering Present value and future random payoff of individual instruments

Probabilistic Machine Learning

Probabilistic Machine Learning Static, causal, advanced AI modeling

Portfolio and Enterprise Risk Management

Portfolio and Enterprise Risk Management Risk measures, performance attribution, (stochastic) stress-testing

Time Series and Reinforcement Learning

Time Series and Reinforcement Learning Dynamic, causal, advanced AI modeling

Portfolio Construction and Trading

Portfolio Construction and Trading Static and dynamic strategies with optimal trade execution

Primers

Mathematics Primer

Mathematics Primer Functional analysis, optimization theory, probability

Finance Primer

Finance Primer Asset classes fundamentals, performance definitions

Python Primer

Python Primer Syntax, data types, structures, functions

The Lab comprises Theory and Case Studies, supported by Code, Animations, Proofs, and Exercises, cross-referenced and mutually integrated, presented in unified, succinct mathematical notation.

Theory

An encyclopedia of Modern Quantitative Finance
Your resource to learn by abstract principles
2,068 pages of explanations with formulas.

Case studies

Applications to practice beyond the Theory
Your tool to learn by real-world examples
10 large scale analytics with real data.

AI tutor

An interactive chatbot to search, summarize, and explain all the Lab
Your channel to ask and be answered in real time
10 million vectors of proprietary content.

Code

Python coding language, no installation
Your environment to learn by doing
66,711 lines of Python code.

Animations

Simulations from data using code
Your device to learn by visualization
99 visualizations of complex models in motion.

Proofs

Proofs to support the analytical results
Your guide to learn by induction
1,751 analytical derivations to support the Theory.

Exercises

Exercises pen & paper and codes
Your test to verify your knowledge
200 analytical exercises to verify the Theory.