Python12 min read
Python Fundamentals Every Quant Developer Should Know
The core Python skills you actually need to break into quantitative finance — variables, functions, data structures, and the patterns that matter most.
Resources
Practical Guides for Quant Developers
Free articles covering the tools, techniques, and thinking behind modern quantitative finance — from Python and cloud infrastructure to calculus, probability, derivatives pricing, and portfolio theory.
Python
Python12 min read
Advanced Python Techniques for Financial Applications
Decorators, generators, context managers, and the patterns that separate beginner Python from production-grade quantitative code.
Python11 min read
NumPy for Quantitative Finance: A Practical Introduction
How NumPy array operations power everything from portfolio risk calculations to Monte Carlo simulations — and why it is so much faster than plain Python.
Python12 min read
Pandas for Financial Data Analysis: Getting Started
How to use Pandas DataFrames for real financial workflows — loading market data, calculating returns, handling time series, and avoiding common pitfalls.
Data & Databases
Data & Databases12 min read
SQL for Financial Data: A Developer's Starting Point
Learn the SQL fundamentals that matter for finance — querying trade data, aggregating positions, joining reference data, and understanding relational databases.
Data & Databases11 min read
Advanced SQL Techniques for Financial Systems
CTEs, window functions, query optimisation, and the advanced SQL patterns used in trading platforms and financial data pipelines.
Data & Databases11 min read
Database Design for Trading Systems
How to structure databases for trading platforms — normalisation, schema design, indexing strategies, and the tradeoffs that matter in financial systems.
Data & Databases10 min read
Time Series Databases in Finance: When Relational Is Not Enough
Why financial firms use specialised time series databases for market data, tick storage, and monitoring — and when you should consider one.
Data & Databases10 min read
Data Formats for Financial Systems: CSV, JSON, Parquet, and Beyond
A practical comparison of data formats used in finance — when to use CSV, JSON, Parquet, or columnar storage, and why the choice matters more than you think.
DevOps
DevOps12 min read
Git and Version Control: The Developer's Safety Net
How Git works, why every finance developer needs it, and the workflows that keep trading system code safe and auditable.
DevOps12 min read
CI/CD Pipelines for Trading Systems
How continuous integration and deployment work in finance — automated testing, build pipelines, deployment strategies, and why they matter for trading infrastructure.
DevOps12 min read
Testing Financial Software: Building Confidence in Your Code
Unit tests, integration tests, property-based testing, and the testing strategies that keep financial systems reliable and correct.
Software Engineering
Software Engineering11 min read
Debugging Techniques Every Developer Should Know
Systematic approaches to finding and fixing bugs — from print statements to debuggers, logging strategies, and the mindset that makes debugging efficient.
Software Engineering12 min read
Design Patterns for Financial Software
The software design patterns that matter most in finance — Strategy, Observer, Factory, and others that help build maintainable trading systems.
Software Engineering11 min read
OOP vs Functional Programming: When to Use Which
Object-oriented and functional programming are not rivals — they solve different problems. Here is when each approach shines in financial applications.
Software Engineering12 min read
APIs and REST for Financial Data
How APIs work, RESTful design principles, and practical patterns for building and consuming financial data APIs.
Software Engineering11 min read
SDLC Best Practices for Fintech
How modern software development lifecycle practices apply in finance — code review, environments, release management, and building reliable systems.
Cloud & Infrastructure
Cloud & Infrastructure12 min read
Docker and Containers for Financial Applications
How containerisation works, why finance teams use Docker, and practical patterns for packaging and deploying trading system components.
Cloud & Infrastructure11 min read
Cloud Computing for Finance: Getting Started
What cloud computing means for financial services — the major providers, core services, cost models, and why finance firms are migrating to the cloud.
Cloud & Infrastructure12 min read
AWS Essentials for Financial Services
The core AWS services that matter for finance — EC2, S3, RDS, Lambda, and the architectural patterns used in trading platforms and data pipelines.
Systems Programming
Systems Programming12 min read
Rust for Low-Latency Trading Systems
Why Rust is gaining traction in finance — memory safety without garbage collection, zero-cost abstractions, and the performance characteristics that matter for trading.
Systems Programming12 min read
C++ in Quantitative Finance
Why C++ remains the language of choice for performance-critical finance — low-latency trading, derivatives pricing, and the modern C++ features that matter.
Systems Programming13 min read
Hardware Acceleration for Quantitative Finance
JIT compilation, SIMD instructions, GPU computing with CUDA, and FPGAs — the hardware acceleration techniques used in high-performance financial systems.
Networking
Networking12 min read
Networking Fundamentals Every Developer Should Understand
How the internet works under the hood — DNS, TCP/IP, HTTP, firewalls, and the networking concepts that matter for building financial applications.
Networking11 min read
Network Speeds and Latency in Financial Systems
Why latency matters in trading, how to measure it, where the bottlenecks are, and what firms do to minimise it — from co-location to kernel bypass.
Networking13 min read
Security and Authentication for Fintech Applications
How to secure financial applications — authentication, authorisation, encryption, common vulnerabilities, and the security mindset every developer needs.
Mathematics
Mathematics11 min read
Mathematical Notation Demystified: A Quant Finance Starter Kit
Sigma notation, function composition, set theory shorthand — the symbolic language you actually need before tackling quant finance maths.
Mathematics12 min read
Exponentials and Logarithms: Why Finance Cannot Live Without Them
Compound interest, log returns, continuous growth — the exponential function and its inverse are everywhere in quantitative finance. Here is why.
Mathematics14 min read
Calculus for Quant Finance: Differentiation, Integration, and Why They Matter
Rates of change, areas under curves, optimisation — calculus is the engine behind derivatives pricing, risk management, and portfolio construction.
Mathematics13 min read
Linear Algebra for Quant Finance: Vectors, Matrices, and Why They Run Everything
Portfolio weights are vectors. Covariance is a matrix. Risk decomposition uses eigenvalues. Here is the linear algebra every quant actually needs.
Mathematics12 min read
Optimisation in Quant Finance: Finding the Best Portfolio (and Everything Else)
From Markowitz to gradient descent — optimisation is how quants find optimal portfolios, calibrate models, and minimise risk. Here is how it works.
Mathematics13 min read
Probability for Quant Finance: From Coin Flips to Option Pricing
Expected values, distributions, Bayes' theorem, the Central Limit Theorem — the probability toolkit every aspiring quant needs.
Mathematics13 min read
Statistics for Quantitative Trading: Estimation, Testing, and Regression
How to estimate volatility, test whether a strategy works, and build factor models — the statistics that actually get used on trading desks.
Mathematics12 min read
Random Walks and Brownian Motion: How Finance Models Uncertainty
From a drunk stumbling home to the Black-Scholes equation — random walks and Brownian motion are the mathematical heartbeat of modern finance.
Finance
Finance13 min read
Understanding Financial Markets: A Practical Guide for Aspiring Quants
Equity, fixed income, FX, derivatives — how financial markets actually work, who the participants are, and where quantitative engineers fit in.
Finance11 min read
Time Value of Money: The Foundation of Every Financial Calculation
Present value, future value, discounting, NPV — the concept that a pound today is worth more than a pound tomorrow underpins all of finance.
Finance12 min read
Bonds and Fixed Income: Pricing, Duration, and Why Quants Care
Bond pricing, yield to maturity, duration and convexity — the fixed income concepts that form the backbone of interest rate modelling.
Finance13 min read
Introduction to Derivatives: Forwards, Futures, Options, and Swaps
What derivatives are, how they work, and why they matter — the contracts at the heart of quantitative finance.
Finance14 min read
Portfolio Theory and CAPM: The Maths Behind Diversification
Mean-variance optimisation, the efficient frontier, and the Capital Asset Pricing Model — how modern finance thinks about building portfolios.
Finance14 min read
Option Pricing Explained: From Binomial Trees to Black-Scholes
The binomial model, Black-Scholes, risk-neutral pricing — how derivatives are valued and why it matters for every quant.
Finance13 min read
The Greeks and Volatility: Sensitivities Every Quant Must Know
Delta, gamma, theta, vega — the partial derivatives that drive options trading, hedging, and risk management. Plus volatility modelling essentials.
Finance14 min read
Risk Management in Quant Finance: VaR, Credit Risk, and Beyond
Value at Risk, expected shortfall, credit risk, and risk-neutral pricing — the quantitative tools that keep the financial system from falling over.
Finance12 min read
Algorithmic Trading: Signals, Backtesting, and What Quants Actually Do
Alpha signals, execution algorithms, backtesting pitfalls — a practical introduction to the world of systematic trading.