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 statistics. Time-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.
- 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 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.