Algorithmic Trading: An Open Introduction

What is algo trading? It means letting a program make some or all of the trading decisions under rules written in advance. Most trading volume on major electronic exchanges is now placed by algorithms, much of it by firms executing large orders for clients rather than by speculators.

What is algo trading, in one paragraph?

An algorithm takes data in, usually prices and sometimes much more, applies fixed rules, and sends orders out. The rules might decide what to buy, when to sell, how large a position to hold, or simply how to split a large order so that it moves the price less. A person still chooses the rules, and is still responsible when they fail.

Why do most beginner algorithms lose money?

Three reasons account for most of it. Costs: a strategy that trades often pays the spread and commission every time. Overfitting: a rule tuned to past data learns its noise. And unrealistic testing: a backtest that assumes every order fills at the last price. This course explains each one in plain terms.

Where does this course lead?

It is the free starting point for the algorithmic trading track. Algorithmic Trading Foundations is the next step, then the practitioner courses and the Certificate in Algorithmic Trading.

What you will be able to do

• Explain the four decisions every algorithm must encode—asset, size, entry, and exit—and translate an informal trading idea into a precise, machine-executable rule.
• Identify the distinct objectives and algorithmic roles of quant funds, investment banks, market makers, and high-frequency firms operating within the same market.
• Assess how data provider choice and bar-level price structure introduce inaccuracies and costs that affect strategy performance before a single live trade is placed.
• Describe the mechanics of trend-following strategies, including moving average crossovers, breakout channels, and the defenses against false breakouts.
• Calculate the complete cost stack of a round-trip trade and determine whether a strategy's edge survives realistic friction across all five cost layers.
• Apply walk-forward analysis and out-of-sample testing to detect look-ahead bias, overfitting, and survivorship bias in a backtest before committing capital.
• Design the position-sizing rules and operational controls—including daily loss limits, order rate limiters, and kill switches—required before deploying a strategy with real capital.

Syllabus, module by module

1. What an Algorithm Actually Decides

   How trading algorithms work as conditional logic systems encoding four decisions—asset selection, position size, entry timing, and exit conditions—executed with mechanical consistency and speed that no human reaction time can match.

2. The Cast of Characters: Who Trades with Algorithms

   The distinct categories of algorithmic market participants—quant hedge funds, investment banks, market makers, high-frequency firms, and retail traders—and the fundamentally different objectives each pursues in the same market.

3. Reading the Market: Price, Time, and Data

   How price and volume data are structured in OHLC bars, where data provider quality and bid-ask spreads introduce inaccuracies and costs that shape strategy performance before live trading begins.

4. Strategy Families: Trend Following

   How trend-following strategies capture directional price moves using moving averages and breakout channels, and the behavioral and statistical mechanisms that sustain momentum across markets and asset classes.

5. Strategy Families: Mean Reversion, Arbitrage, and Market Making

   How mean-reversion, statistical arbitrage, and market-making strategies exploit price deviations and bid-ask spreads rather than directional trends, and the conditions each requires to remain viable.

6. The Hidden Drain: Costs and Slippage

   The five layers of transaction cost—commissions, bid-ask spread, slippage, market impact, and financing—how each accumulates across trade frequency, and why the least visible costs are typically the largest.

7. Risk: What Can Go Wrong and How to Measure It

   The four categories of risk—model, execution, liquidity, and technology—that algorithmic strategies face, examined through documented failures including LTCM, the 2010 Flash Crash, and Knight Capital.

8. Testing an Idea Honestly: Backtesting Without Fooling Yourself

   How to design honest historical tests using out-of-sample splits and walk-forward analysis, and how to recognize and eliminate look-ahead bias, overfitting, and survivorship bias from every test.

9. Live Trading Without Blowing Up

   How to move from a validated backtest to live trading through paper trading, a scaled initial allocation, position-sizing discipline, and automated operational controls that prevent catastrophic loss.

What every course contains

Every paid course comes with the first seven and the certificate, whichever level it sits at. The proctored exam and the credential come when the course is taken as part of a Certificate, Diploma or Fellowship. Everything is self-paced: the material is yours to study in any order, at any hour, for the whole of the license.

1. Workbooks. Written to train the thinking patterns and the important concepts of the course, with worked problems and the reasoning behind each answer, so that you learn to think the way the subject is thought.
2. Audio edition. Focused, well-presented recordings with explainers and examples of the material, made to be interesting, relevant and entertaining, so that the general subject can be learned away from the desk.
3. Notes. Pre-produced notes with every fact the course relies on, written out in full, so that nothing has to be transcribed from the films or the audio.
4. Cheat sheet. One sheet with every important learning concept of the course on it, to keep beside you during the work and to revise from before the exam.
5. Named sources. Every fact in the notes names its source, the paper, the book or the dataset, for anyone who wants to dig in further.
6. Explainer films. Focused films, in the style of the sample films on the catalog page, that walk through the most difficult concepts of the course with visual explanations of a high standard.
7. Transcript. A full transcript of every film and every audio recording, searchable and quotable.
8. Proctored exam. Taken as part of a Certificate, Diploma or Fellowship, the course ends in a proctored multiple-choice questionnaire, with a pass mark of 60% and three retakes included. A course taken on its own is assessed by its coursework and has no exam.
9. Verifiable certificate. A certificate of completion that a third party can verify: an employer sends the code on it to the credentials office and receives written confirmation of the course, the date and the result.
10. Credential of the program. The Certificate, Diploma or Fellowship of the program, track or path the course belongs to, awarded when every course in it is passed. Which one depends on the program you choose.

Assessment

Not assessed. Study notes, a cheat sheet and a workbook come with every lesson. Open courses are free, have no exam and award no certificate. Read how certification works.