Algorithmic and High-Frequency Trading (Mathematics, Finance and Risk)

Cartea, Álvaro; Jaimungal, Sebastian; Penalva, José

ISBN 10: 1107091144 / ISBN 13: 9781107091146

Verlag: Cambridge University Press, 2015

Beschreibung

Print on Demand pp. 356 This item is printed on demand. Bestandsnummer des Verkäufers 372570815

Bibliografische Details

Titel: Algorithmic and High-Frequency Trading (...

Verlag: Cambridge University Press

Erscheinungsdatum: 2015

Einband: Hardcover

Zustand: New

Über diesen Titel

Inhaltsangabe:

This cutting-edge textbook shows how to build the advanced mathematical models that underpin modern trading algorithms. 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 book is for you.

Über die Autorinnen und Autoren:

Álvaro Cartea is a Reader in Financial Mathematics at University College London. Before joining UCL, he was Associate Professor of Finance at Universidad Carlos III, Madrid (2009–2012) and from 2002 to 2009 he was a Lecturer (with tenure) in the School of Economics, Mathematics and Statistics at Birkbeck, University of London. He was previously JP Morgan Lecturer in Financial Mathematics at Exeter College, Oxford.

Sebastian Jaimungal is an Associate Professor and Chair of Graduate Studies in the Department of Statistical Sciences, University of Toronto, where he teaches in the PhD and Masters in Mathematical Finance programs. He consults for major banks and hedge funds focusing on implementing advance derivative valuation engines and algorithmic trading strategies. He is also an associate editor for the SIAM Journal on Financial Mathematics, the International Journal of Theoretical and Applied Finance, the journal Risks and the Argo newsletter. Jaimungal is Vice Chair for the SIAM activity group on Financial Engineering and Mathematics, and his research has been widely published in academic and practitioner journals. His recent interests include high-frequency and algorithmic trading, applied stochastic control, mean-field games, real options, and commodity models and derivative pricing.

José Penalva is an Associate Professor at the Universidad Carlos III de Madrid, where he teaches in the PhD and Masters in Finance programs, as well as at the undergraduate level. He is currently working on information models and market microstructure and his research has been published in Econometrica and other top academic journals.