Redefining Quantitative Finance

Quant Research, Systematic Investment and AI

Welcome aboard! 🤝🏻

I’m Quant Beckman, a quantitative researcher working with multi-family offices, pod shops and specialised platforms that actually deploy risk. My work is simple to state and hard to copy: turn raw data into durable edge. Models, infrastructure and systematic strategies aimed at one thing: better risk-adjusted returns.

This publication is where I open up part of that pipeline.

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But first, who is this for?

1. Quants.

2. Algorithmic traders.

3. Systematic investors.

If you don't fit into one of these categories, please unsubscribe now.

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What is the content of this newsletter?

• Data engineering and alternative data sources.

• Quant models and trading strategies.

• Infrastructure and technology architecture.

• Optimization, testing and simulation.

• Market intel and global macro research.

• Portfolio construction and asset allocation.

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Not sure where to begin?

Here’s a quick roadmap to guide you through the highlights of this newsletter. 14/11/2025 (updated)

QUANTITATIVE RESEARCH

• Basics:

  • Principles of applied statistics for trading

  • Foundation of statistical inference

• Statistical modeling:

  • Quantitative modeling in finance

  • How to create quant models

  • Estimation and quantifying performance

  • The hypothesis-testing framework

  • Alpha and factor decomposition

DATA

• Basics: Data types and structures

• Get and store: Market data

• Preprocessing:

  • Data cleaning

  • Data preparation

  • Quality standards

• Alternative bars:

  • Tick, Dollar, Volume

  • Range, Renko, Filter, Volatility bars

MODELS

• Basics: What is a model and an algorithm?

• Rule models:

  • FURIA algorithm

  • RIDRA algorithm

  • RIPPER algorithm

• Clustering:

  • Batch models

  • Graph models

  • Online models

• Dependency: Generalized Gumbel copula

• Options:

  • Iron Condor

  • Iron Butterfly

  • Straddles & Strangles

• Parameter Optimization:

  • Walk-Forward

  • CPCV-opt

  • A robust protocol

FEATURES

• Basics: Early feature selection

• Feature selection online: Incremental feature selection

RISK

• Basics: RiskOps paradigm guide

• Allocation: Capital allocation to portfolio of systems

• Position sizing: Contract sizing and leverage

• Closing algorithm: Position manager

• Bailout algorithm: Circuit breaker

• Take profit & stoploss: Optimal targets

TESTING

• Basics: Statistical test for trading

• Strategy evaluation:

  • Historical backtest

  • Testing

  • Validation

• Metrics:

  • Trading metrics

  • Alternative metrics

• Synthetic data: Synthetic scenarios

PORTFOLIO

• Basics: Portfolio of uncorrelated systems

• Portfolio construction: Asset selection

• PM methods: Robust covariance estimation

CAREER

• Roadmap to become a Quant

• FAQs for quant roles

• Interview level

• Change career

• Experience working with quant teams

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Through this newsletter, I’m excited to share the insights, strategies, and behind-the-scenes moments that shape my work. Whether you’re a curious investor or a seasoned quant, I’m here to challenge conventional thinking, inspire bold ideas, and guide you through the complex, ever-evolving world of quantitative finance.

Let’s explore the future together!

For now, buckle up—it’s gonna be a wild ride.

—Quant Beckman

Founder of Trading the Breaking

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Thank you to all the special people who have decided to be part of the project and shared their thoughts: