Introduction: What, why and who

Algorithmic trading is a broad term for trading which uses mathematical models and algorithms. As markets have become more automated over time, banks and retail brokerages increasingly make markets for their clients using algorithms (e-trade). Some quant hedge funds have relied heavily on algorithms from the start, with a notable few enjoying huge success, while others have employed algorithms as one of many elements in their approach. In recent times, high-frequency market-makers and proprietary trading shops have come to dominate the exchange traded (and some OTC) markets, with increased volume and speed leading to higher net returns. Algorithms can be used for all aspects of the business, from trade decisions to portfolio allocations to placing market and limit orders with the time horizons involved being anywhere from a nanosecond to many days.

The rationale is simple – efficient, scalable models with consistent and testable performance. The aim is to use a scientific approach which can generate extremely fast responses to market events.

While some exchange traded markets (liquid futures, equities, ETFs) and some highly liquid OTC markets (FX, US Treasuries) have been dominated by algorithmic trading for some time, more recent developments include increasing algo presence in less liquid markets such as non-liquid energy futures (energy futures outside of WTI, Brent, and standard energy complex), OTC rates markets (USD and EUR swaps), highly illiquid corporate bonds and even in areas once fully dominated by voice-trading such as EUR government bonds. Some of this evolution is the quest for new markets in which to apply what has been successfully developed elsewhere but much of it is just the natural diffusion of talent into areas which are both more risky and possibly more lucrative. Irrespective of whether it be market-making in banks and speciality prop shops or finding and executing on alphas, balancing portfolios and optimising execution in asset managers, today’s traders, quants and managers must know about systematic trading.

The goal of this class is to provide students with a strong foundation in algorithmic trading as well as the tools and techniques used in the industry. The class will cover everything from basic programming concepts to advanced trading strategies and methods for research into new alpha sources. Students will have the opportunity to apply what they learn in hands-on projects throughout the course.