World Business StrategiesServing the Global Financial Community since 2000

Professionals – Understand the mechanics of standard implementations of the single asset and portfolio based risk-premia trading strategies, the basis for CTAs and Quant funds, Equities Quant funds, position taking by e-traders/market-makers and a standard set of strategies in HFT. Recognize pros and cons of various approaches to designing strategies and the common pitfalls encountered by algorithmic traders. Be able to devise new and improved algorithmic strategies.

Algorithmic Traders – Recognize the reasons commonly-used strategies work, the basis for why they should, and when they don’t. Understand the statistical properties of strategies and discern the mathematically-proven from the empirical.  Acquire and improve methods to prevent overfitting.

Academics/students – Gain familiarity with the broad area of algorithmic trading strategies. Master the underlying theory and mechanics behind the most common strategies. Acquire the understanding of principals and the context necessary for new academic research into the large number of open questions in the area.

Students will be expected to have a strong grounding in statisticsTime-series statistics (e.g., as taught in signal processing, econometrics) will be very useful but not mandatory. The course will be directed towards those with some finance experience (i.e., those working in finance or actively studying financial markets). Financial markets knowledge of the basics of equities, fixed income, fx and futures, and mean-variance optimisation is assumed, although we will cover some of the background material and provide more as and if requested.

Educational Background

  • Bachelors or Masters degree (or equivalent) in
    • Hard Sciences and Engineering
    • Computer Science (with a firm understanding of mathematics)
    • Economics or Finance (with a firm knowledge of econometrics)


These are a few of the standard readings for each topic area. More in-depth readings will be provided during the course, and are available on the Zotero Group Library (shared library) Algo Trading Library.


The class will have a forum Slack channel which will serve as a means of ongoing communication during and in-between sessions.


There will be several short assignments given at the end of every class to be turned in on or before the next session, all in Python, Matlab, or R, with the goal of attaining proficiency in coding the standard strategies

This workshop is available Globally Online.

Start Time: 17.30 – 21.00 BST

Week 1: Thursday 5th July

Topic: Overview, Math Background, Trend Following, Mean-Reversion

Week 2: Thursday 12th July

Topic: More Mean-Reversion: Pairs/RV trading, Carry and Value

Week 3: Thursday 19th July

Topic: Portfolio Allocation, Equities Quant, Styles Investing and ML

Week 4: Thursday 26th July

Topic: Overfitting, Multiple testing, Covariance Penalties, Robustness and Rehash

Final Project

Summer Break

Final Project Hand-In: Thursday 30th August

Week 5: Thursday 6th September (Start Time: 17.30 BST) 
Final Project Review, Catch-up & Feedback Webinar Week

You will be able to receive 26 CPD points (18 hours of structured CPD and 8 hours of self-directed CPD) for taking this course.

The CPD Certification Service was established in 1996 as the independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies. The CPD Certification Service provides recognised independent CPD accreditation compatible with global CPD principles.

  • Discount Structure
  • Special Offer
    When two colleagues attend the 3rd goes free!

  • 50% Academic Discount
    (FULL-TIME Students Only)

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