Review: Algorithmic trading

Automated trading systems play an increasingly important role in equity markets. The challenge of trading large order volumes and baskets is often met today with automated trading algorithms. An investment decision generally leads to orders with specifications such as security, size, and urgency but also specifications (e.g., expected profit), and constraints (e.g., dollar neutrality) may be given. The trader has to choose a trading strategy ensuring best execution under given marginal constraints. This review provides an overview of how such trading algorithms work. The ideas behind some standard strategies are presented, as well as approaches to enhance them. For developing automated trading strategies for stock markets, a deep understanding in market microstructure is necessary, so we review this topic as well. We have a look on the issue how market quality is affected by market designs of trading platforms and fragmentation of the market. Trading costs are the main attribute of market quality. Trading strategies are implemented to optimize trading costs and execution risk by taking market microstructure aspects into account. Empirical analyses of trading volume and order book characteristics help to adjust the trading strategies.