Algorithmic Trading Certificate (ATC): A Practitioner’s Guide Self Study Pack (coming soon)
Duration:
📅 Self-Paced: 22+ lecture hours
Format:
💻 Online
Evaluation:
✔ Final Project + Certificate
📆 Time Commitment:
Recorded lectures accessible any time. Take the ATC at your own pace.
🕛 Self-paced Online:
Students will have the opportunity to apply what they learn in hands-on projects throughout the course.
📊 Certificate:
“Students are awarded the prestigious ATC Certificate from WBS Training.”
💳 Cost: £1695.00
Level up your career: Understanding advanced trading strategies, Impact of Machine Learning and methods for research into new alpha sources.
Goals of Class
- Provide a strong foundation in the tools and techniques used in algorithmic trading.
- Cover everything from basic programming concepts to advanced trading strategies and
methods for research into new alpha sources. - Apply everything in hands-on projects throughout the course.
About the programme
This course has been designed to empower individuals who work in or are seeking a career in quantitative finance. Throughout our unique ATC programme, we provide a strong foundation in the tools and techniques used in algorithmic trading. Covering everything from basic programming concepts to advanced trading strategies and methods for research into new alpha sources. Applying everything in hands-on projects throughout the course. The ATC is a career-enhancing professional certificate, that can be taken worldwide.
Summary
- Key takeaways
- Designing your own strategies
- Doing active research
- Sourcing and cleaning data
- Algorithmic Trading Certificate (ATC): A Practitioner’s Guide
- Keeping tech stack up-to-date
- Maintenance and Improvement
- Next steps
Assessments
One written assessment at the end (PDF + Python Notebook), describing a strategy in detail: its behaviour, its rationale (with quoted references if applicable), implementation and performance and limitations and room for improvements. Marks for sensibility of coverage and exposition, for following the methodology, etc. (i.e., good performance only is not sufficient – you have to display it and explain it).
Final Project
The ATC concludes with a practical final project that gives you the opportunity to implement the knowledge and skills you have acquired during the course of the programme. Self Study Pack students get an option three times per year to join the live cohort (when ready) to discuss the final project with the faculty.
Modules:
Module 1: Intro and Industry Overview - 1 hour
• Video 1: Introduction
• Video 2: Quant Finance in the Financial Services Sector
• Video 3: Tracking Quant Performance
• Video 4: The Quant Finance Landscape
• Introduction & The Industry - Slides
Module 2: Data and Features - 1 hour 15 minutes
• Video 1: Data Sources
• Video 2: Features
• Video 3: Signals - Overview
• Data & Features - Slides
Module 3: Statistics and Time Series - 3 hours
• Video 1: Introduction to Statistics
• Video 2: Motivation - Asset Prices
• Video 3: Types of Distribution
• Video 4: Maximum Likelihood Estimation
• Video 5: Multivariate Distributions
• Video 6: Statistical Inference
• Video 7: What Have We Learned?
• Video 8: Introduction to Time Series
• Video 9: Time Series
• Video 10: General Framework
• Video 11: Autoregressive Policies
• Video 12: Moving Average Processes
• Video 13: Identifying p & q
• Video 14: ARMA(p, q) Process
• Video 15: Maximum Likelihood Estimation
• Video 16: What Have We Learned
• Statistics and Time Series - Slides
Module 4: Machine Learning - 2 hours
• Video 1: Introduction to Machine Learning
• Video 2: Introduction to Classification
• Video 3: Regression
• Video 4: Support Vector Machines
• Video 5: Kernels
• Video 6: Decision Trees
• Video 7: Random Forests
• Video 8: Neural Networks
• Video 9: Reinforcement Learning
• Machine Learning - Slides
Module 5: Trend Following – 2 hours
• Video 1: Trading Strategies
• Video 2: Trend Following
• Video 3: Momentum and Skewness
• Video 4: Momentum and Responsiveness
• Video 5: Cross-Sectional Momentum
• Video 6: Other Topics In Momentum
• Video 7: Trading Futures
• Video 8: An Exercise
• Video 9: References
• Trend Following - Slides
Module 6: Carry and Volatility – 2 hours
• Video 1: Foreign Exchange
• Video 2: The Carry Trade
• Video 3: Physical and Risk-Neutral Measures
• Video 4: Margin
• Video 5: Volatility Strategies
• Carry & Volatility - Slides
Module 7: Mean Reversion – 2 hours 15 minutes
• Video 1: Mean Reversion
• Video 2: Cointegration
• Video 3: Implementing Mean Reverting Strategies
• Video 4: Pairs Trading
• Video 5: Statistical Arbitrage
• Video 6: Factor Models and PCA
• Video 7: Mean Reversion As Liquidity Provision
• Video 8: Change Point Detection and Regime Switching - Part 1
• Video 9: Change Point Detection and Regime Switching - Part 2
• Mean Reversion - Slides
Module 8: Forecasting Models and Factor Investing – 1 hour 45 minutes
• Video 1: Intro
• Video 2: Signals
• Video 3: Factor Trading Part 1 - CAPM
• Video 4: Factor Trading Part 2 - APT
• Video 5: Factor Trading Part 3 - Factor Portfolios
• Video 6: Factor Trading Part 4 - MHT
• Video 7: Combining Signals/Forecasting
• Video 8: Regularization
• Video 9: Dimension Reduction
• Video 10: Adaptive Models
• Video 11: WHWL
• Forecasting Models and Factor Investing - Slides
Module 9: Order Execution and Market Making – 2 hours 15 minutes
• Video 0: Intro
• Video 1: Market Microstructure
• Video 2: Market Structure
• Video 3: Price Formation and Price Discovery
• Video 4: Liquidity
• Video 5: Algorithmic Trading
• Video 6: Order Types
• Video 7: Market Impact
• Video 8: Minimising Market Impact
• Video 9: Market Making
• Video 10: Order Book Dynamics
• Video 11: Markov Decision Process
• Order Execution and Market Making - Slides
Module 10: Portfolio Theory and Allocation – 1 hour 30 minutes
• Video 0: Introduction
• Video 1: Asset Pricing Models
• Video 2: Portfolio Theory
• Video 3: Two Asset Portfolios
• Video 4: N Asset Portfolios
• Video 5: Adding Transaction Costs
• Video 6: Quadratic Problems
• Video 7: Tactical Asset Allocation
• Video 8: Optimal Scaling for Strategies
• Portfolio Theory and Allocation - Slides
Module 11: Back-testing and Performance – 1 hour 45 minutes
• 0: Introduction
• 1: Performance Indicators
• 2: Illustrating Drawdowns
• 3: Python for Analysis
• 4: Performance Indicator Comparisons
• 5: A Realistic Backtest
• 6: Optimizing Parameters
• 7: Multi-Objective Optimization
• 8: What Have We Learned?
• Performance Repot Class - Python
• Backtesting and Performance Measurement - Slides
Module 12: Risk Management – 1 hour 45 minutes
• Video 1: Risk Management
• Video 2: Linear Market-Risk
• Video 3: Non-Linear Market-Risk
• Video 4: The Impact of Time
• Video 5: Operational Risk
• Video 6: Optimal Scaling for Strategies
• Video 7: Value at Risk and Related Approaches
• Video 8: Factor Models
• Risk Management and Portfolio Theory - Slides
Real World Project
ATC Final Assignment
Final project submission
Testimonials:
"The comprehensive coverage of various topics provided me with a solid understanding of the intricacies of algorithmic trading. Now I have a clear direction on where to begin and how to approach each strategy effectively. I now feel equipped with the knowledge and confidence to navigate the complexities of algorithmic trading with ease. I highly recommend this training to anyone looking to dive into the world of algorithmic trading.”
Dr Abdallah Rahal
”ATC covers a vast panel of topics structured around building trading strategies and leveraging modern infrastructures. From time series theory to risk management, the authors of the course tried to give a wide overview on the field, and provided the students with valuable references/ books/ resources. I have enjoyed this course and would recommend it.”
Imen al Samarai
Introduction: Algorithmic Trading Certificate (ATC): A Practitioner’s Guide