Algorithmic Trading Foundations

This algorithmic trading course is the first paid rung of the practitioner path. It assumes some Python and no trading experience, and it ends with a backtest you could show a sceptical colleague.

What do you need to know before writing a trading algorithm?

How the market you trade actually works. An algorithm sends orders into an order book, where they wait, fill, partly fill or are skipped. The spread is a cost paid on every round trip. Data from free sources often drops delisted stocks, which makes every long-only strategy look better than it was. The first three modules cover these facts, because every later result depends on them.

Why does the course teach three strategy families instead of one good strategy?

Because the families behave differently, and the differences teach more than any single rule. Trend rules trade rarely and lose in choppy markets; mean-reversion rules trade often and are sensitive to costs; breakouts sit between them. Running all three on the same data, with costs, shows how turnover and holding period drive results.

Who is this course for?

Beginners with some Python, discretionary traders who want to test their rules, and anyone heading for the Certificate in Algorithmic Trading. It counts toward that certificate and the Foundation Certificate in Computational Finance.

What you will be able to do

• Explain how an electronic exchange matches orders and what the bid-ask spread costs.
• Choose between market, limit and stop orders for a given purpose.
• Implement a trend, a mean-reversion and a breakout rule on daily data.
• Include commissions, spread and slippage in a backtest.
• Separate in-sample and out-of-sample data and report both.

Syllabus, module by module

1. Electronic markets

   Exchanges, the order book, matching rules, the bid-ask spread and market hours.

2. Orders

   Market, limit, stop and stop-limit orders, time in force, and what each risks.

3. Data

   Bars, adjustments for splits and dividends, survivorship bias and where free data misleads.

4. Trend rules

   Moving averages and channel breakouts, and why trend rules trade rarely.

5. Mean-reversion rules

   Z-scores, oscillators and short-horizon reversal, and why they trade often.

6. Costs

   Commission, spread, slippage and borrowing, and how they scale with turnover.

7. A first honest backtest

   In-sample and out-of-sample periods, a benchmark, and the questions to ask of any equity curve.

How the certificate is earned

Weekly quizzes and one graded problem set: you implement and test two simple strategies with costs, on in-sample and out-of-sample periods, and explain the difference in results. On a pass you receive the Course certificate in Algorithmic Trading Foundations, issued by the Institute with a verification code. Read how certification works.

Before you start

Basic Python with pandas. The free introduction is recommended but not required.

• Python for Finance