Algorithmic Trading & DMA

This book provides a detailed introduction into algorithmic trading and direct market access (DMA). It caters for any investors, traders, quants or software developers who want to know more about these techniques.

Note the aim is to take the reader from the ground up, so very little knowledge of the markets or trading is assumed. Similarly there are no requirements for any programming knowledge: the basis of most algorithms is tackled graphically, though there is some maths.

Although this is not an advanced text even experienced traders may benefit. The coverage encompasses all the major asset classes, from stocks to bonds, FX and derivatives. Also it covers more cutting edge topics, such as portfolio and multi-asset trading and news handling and artificial intelligence.

Another aim of this book is to try and highlight the phenomenal amount of research has been carried out into trading and markets, and help to bridge some of the gaps between the practice of trading and the theory. So throughout reviews of relevant empirical research are provided.


Part I provides a broad overview of algorithmic trading and direct market access, highlighting their roles as core execution methods for institutional trading. Market microstructure is introduced to show the key differences between leading market structures and trading mechanisms. This then leads to a review the world’s major asset classes and their respective markets. More detailed asset-class reviews are also provided in the appendices.

Part II concentrates on the specifics of algorithmic trading and DMA.
We start with orders since these are the basic building block for all trading strategies. Coverage is provided for the whole range of different order types and conditions which are available on the world’s markets.
Detailed examples are given throughout illustrating the mechanism of each order type.

Next we consider trading algorithms. They are classified using three main types, namely impact-driven (e.g. VWAP), cost-driven (e.g. implementation shortfall) and opportunistic (e.g. liquidity seeking). For each algorithm we examine their basic mechanism, as well as discussing common variations. To allow more comparison a standard example order is used throughout. This, combined with charts showing the potential trading patterns,
helps highlights both the differences and similarities between the various algorithms.

Finally we move on to see how transaction cost analysis may be applied and consider how to find the optimal trading strategy.

Part III focuses more on the details for implementing algorithmic trading and DMA strategies. Starting with order placement we then progress to see how common tactics may be used to achieve the goals of algorithms, as well as reviewing methods for enhancing the performance of these strategies, such as short-term forecasting, cost estimation and handling specific events such as witching days or trading halts. The technological aspects of implementing these strategies are also considered.

Part IV looks at the techniques which are still at the cutting edge of algorithmic trading, namely portfolio and multi-asset trading, handling news and artificial intelligence. For each topic we review the basic theory and then see how best to tailor trading algorithms for this.