Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance...

Market fragmentation : monitoring and history -- Smart order routing -- Tick size; -- Information seeking and price discovery -- Dark pools and broker crossing networks -- Liquidity : the viewpoint of trading venues -- The agenda of high frequency traders -- The link between fragmentation and...

on the basis of their commonly known strength levels, and privately observed strengthshocks

Because of their tractability and their natural interpretations in term of market quantities, Hawkes processes are nowadays widely used in high-frequency finance. However, in practice, the statistical estimation results seem to show that very often, only nearly unstable Hawkes processes are able...

Estimating volatility from recent high frequency data, we revisit the question of the smoothness of the volatility process. Our main result is that log-volatility behaves essentially as a fractional Brownian motion with Hurst exponent H of order 0.1, at any reasonable time scale. This leads us...