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The Science Of Algorithmic Trading And Portfolio Management 1st Edition Robert Kissell

  • SKU: BELL-4556562
The Science Of Algorithmic Trading And Portfolio Management 1st Edition Robert Kissell
$ 31.00 $ 45.00 (-31%)

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The Science Of Algorithmic Trading And Portfolio Management 1st Edition Robert Kissell instant download after payment.

Publisher: Academic Press
File Extension: PDF
File size: 5.35 MB
Pages: 474
Author: Robert Kissell
ISBN: 9780124016897, 0124016898
Language: English
Year: 2013
Edition: 1

Product desciption

The Science Of Algorithmic Trading And Portfolio Management 1st Edition Robert Kissell by Robert Kissell 9780124016897, 0124016898 instant download after payment.

The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems.

This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects.

  • Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers.

  • Helps readers design systems to manage algorithmic risk and dark pool uncertainty.
  • Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.

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