Algorithmic Trading with Zorro

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We have designed Algorithmic Trading with Zorro to get you from novice onto the path to becoming a skilled trading systems researcher in as little as 11 weeks. Even if you’ve never coded before.

A fundamental prerequisite of algorithmic trading success is the ability to put your trading ideas into computer code and design scientifically robust, statistically sound experiments to test them. That means that if you can’t already, you are going to have to learn to code, and you’re going to need an accurate simulation (backtesting) tool. You’ll also need to learn the basics of experimentation. In particular, you’ll need to learn how to recognise and deal with the common pitfalls of trading systems research, such as data mining bias and over-optimisation.

In Algorithmic Trading with Zorro, you’ll learn the essentials of programming via the Lite-C scripting language as well as the foundations of scientifically robust experimentation and design. By the end of the course, you’ll be able to code trading ideas based on technical analysis, price action, seasonal volatility and multiple time frames. We’ll even introduce some quant-style techniques like digital signal processing and machine learning. You’ll get loads of coded examples, including ten fully coded example strategies to get you started. But more importantly than putting such ideas into code, you’ll learn how to optimize and test them in a scientifically robust manner, which is crucial if any strategy you develop in the future is to perform in live trading as it did in simulation.

Setting the right expectations

If you’re a new coder, the progress you’ll make in the 11 weeks of this course will probably blow your mind (at least that’s what our past students tell us). But this course really does just provide the foundations for algorithmic trading success – there is whole wide world to explore once you’ve got the fundamentals under control (but don’t worry, we’ve got you covered there too).

We’ll talk more about this in the introductory lessons, but I want to be clear from the outset that the example strategies in Lesson 4 (and any other example strategies throughout the course) are intended as a teaching aid. Please don’t regard them as complete strategies. In fact, we’re not even implying that the signals and trade logic are sensible – they’re just examples to show you how the different pieces fit together.

Learning to work the tools of the trade (pun intended) is the first step in the process; once you’ve got that under control, the much bigger world of straegy research and development is within your grasp. In this course, we’re focused firmly on that first step.

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