The design of trading algorithms requires sophisticated
mathematical models backed up by reliable data. In this textbook,
the authors develop models for algorithmic trading in contexts such
as executing large orders, market making, targeting VWAP and other
schedules, trading pairs or collection of assets, and executing in
dark pools. These models are grounded on how the exchanges work,
whether the algorithm is trading with better informed traders
(adverse selection), and the type of information available to
market participants at both ultra-high and low frequency.
Algorithmic and High-Frequency Trading is the first book that
combines sophisticated mathematical modelling, empirical facts and
financial economics, taking the reader from basic ideas to
cutting-edge research and practice. If you need to understand how
modern electronic markets operate, what information provides a
trading edge, and how other market participants may affect the
profitability of the algorithms, then this is the book for you.