Listed Volatility and Variance Derivatives: A Python-based Guide (Wiley Finance)
| Author | : | |
| Rating | : | 4.17 (812 Votes) |
| Asin | : | B01MQHHBSL |
| Format Type | : | |
| Number of Pages | : | 131 Pages |
| Publish Date | : | 2014-09-06 |
| Language | : | English |
DESCRIPTION:
He has written the financial analytics library DX Analytics (dx-analytics) and organizes meetup groups and conferences about Python for quantitative finance in Frankfurt, London and New York. DR. He is the author of Python for Finance, and Derivatives Analytics with Python. YVES HILPISCH is founder and managing partne
"For true Pythonistas wanting to jump inside quant finance" according to Cary. I've had many discussions with Yves and followed his trajectory over the past few years. He is basically a full time professor with a side job as a leading expert in Python for quantitative finance who travels around the world consulting WS and educationally paving the way for any kid who dreams of not just being a Quant, but a new, cutting-edge type of one. For myself having spent most of my career in volatility, he is an invaluable resource. Be warned thoug
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. Leverage Python for expert-level volatility and variance derivative tradingListed 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. This complete guide offers rare insight into the use of
Because of this and also due to its powerful ecosystem of libraries, it has become one of the most widely used programming languages and technology platforms in the financial industry. From the Inside FlapPython in general requires much less code than other languages, like C++ or C#, to accomplish the same goal. This complete guide is the first of its kind to offer practical, expert insight into how industry leaders use Python to undertake complex quantitative analysis in the field. . From understanding the fundamental techniques of modeling to reproducing your own results and graphics with Jupyter Notebooks, this single resource gives you everything you need to use this pow