Charles-Albert Lehalle – författare

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 over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory.

Financial Markets in Practice: From Post-Crisis Intermediation to FinTechs delivers an overview of the development of risk-transformation undertaken by the financial services industry from the perspective of quantitative finance. It provides an instructional and comprehensive explanation of the structure of the financial system as a network of risk suppliers and risk consumers, where different categories of market participants buy, transform, net, and re-sell different kinds of risks. This risk-transformation oriented view is supported by the changes that followed the last global financial crisis: consumers of financial products asked for less complex risk transformations, regulators demanded limiting risks inside financial institutions to the maximum extent possible, and market participants turned to run mass market-like businesses and away from bespoke "haute couture"-like businesses.This book portrays the network of intermediaries that compose the financial system, describes their most common business models, explains the exact role of each kind of market participant, and underlines the interaction between them. It seeks to reveal the potential disintermediation that could occur inside the financial sector, led by FinTechs and Artificial Intelligence-based innovations.Readers are invited to reconsider the role of market participants in the post-crisis world and are prepared for the next wave of changes driven by data science, AI, and blockchain. Amid these innovations, quantitative finance will be increasingly involved in all aspects of the financial system. This handy resource helps practitioners from both the buy-side and sell-side gain insights to, and provides an overview of, business models in the financial system from an intermediation perspective, and guides students to comprehensively understand the complex ecosystem in which they will evolve.

This book exposes and comments on the consequences of Reg NMS and MiFID on market microstructure. It covers changes in market design, electronic trading, and investor and trader behaviors. The emergence of high frequency trading and critical events like the"Flash Crash" of 2010 are also analyzed in depth.Using a quantitative viewpoint, this book explains how an attrition of liquidity and regulatory changes can impact the whole microstructure of financial markets. A mathematical Appendix details the quantitative tools and indicators used through the book, allowing the reader to go further independently.This book is written by practitioners and theoretical experts and covers practical aspects (like the optimal infrastructure needed to trade electronically in modern markets) and abstract analyses (like the use on entropy measurements to understand the progress of market fragmentation).As market microstructure is a recent academic field, students will benefit from the book's overview of the current state of microstructure and will use the Appendix to understand important methodologies. Policy makers and regulators will use this book to access theoretical analyses on real cases. For readers who are practitioners, this book delivers data analysis and basic processes like the designs of Smart Order Routing and trade scheduling algorithms.In this second edition, the authors have added a large section on orderbook dynamics, showing how liquidity can predict future price moves, and how High Frequency Traders can profit from it. The section on market impact has also been updated to show how buying or selling pressure moves prices not only for a few hours, but even for days, and how prices relax (or not) after a period of intense pressure.Further, this edition includes pages on Dark Pools, Circuit Breakers and added information outside of Equity Trading, because MiFID 2 is likely to push fixed income markets towards more electronification. The authors explore what is to be expected from this change in microstructure. The appendix has also been augmented to include the propagator models (for intraday price impact), a simple version of Kyle's model (1985) for daily market impact, and a more sophisticated optimal trading framework, to support the design of trading algorithms.