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Listed volatility and variance derivatives : a Python-based guide / Yves J. Hilpisch.

By: Material type: TextTextSeries: Wiley finance seriesPublisher: Chichester, England : Wiley, 2017Copyright date: ©2017Description: 1 online resource (369 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119167921 (e-book)
  • 9781119167938 (e-book)
  • 9781119167945 (e-book)
Subject(s): Genre/Form: Additional physical formats: Print version:: Listed volatility and variance derivatives : a Python-based guide.DDC classification:
  • 332.64/57 23
LOC classification:
  • HG6024.A3 .H557 2017
Online resources:
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Ebrary Online Books Ebrary Online Books Colombo Available CBEBK20002473
Ebrary Online Books Ebrary Online Books Jaffna Available JFEBK20002473
Ebrary Online Books Ebrary Online Books Kandy Available KDEBK20002473
Total holds: 0

Enhanced descriptions from Syndetics:

Leverage Python for expert-level volatility and variance derivative trading

Listed Volatility and Variance Derivatives is a comprehensive treatment of all aspects of these increasingly popular derivatives products, and has the distinction of being both the first to cover European volatility and variance products provided by Eurex and the first to offer Python code for implementing comprehensive quantitative analyses of these financial products. For those who want to get started right away, the book is accompanied by a dedicated Web page and a Github repository that includes all the code from the book for easy replication and use, as well as a hosted version of all the code for immediate execution.

Python is fast making inroads into financial modelling and derivatives analytics, and recent developments allow Python to be as fast as pure C++ or C while consisting generally of only 10% of the code lines associated with the compiled languages. This complete guide offers rare insight into the use of Python to undertake complex quantitative analyses of listed volatility and variance derivatives.

Learn how to use Python for data and financial analysis, and reproduce stylised facts on volatility and variance markets Gain an understanding of the fundamental techniques of modelling volatility and variance and the model-free replication of variance Familiarise yourself with micro structure elements of the markets for listed volatility and variance derivatives Reproduce all results and graphics with IPython/Jupyter Notebooks and Python codes that accompany the book

Listed Volatility and Variance Derivatives is the complete guide to Python-based quantitative analysis of these Eurex derivatives products.

Includes bibliographical references and index.

Description based on print version record.

Electronic reproduction. Ann Arbor, MI : ProQuest, 2016. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.

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