Listed Volatility and Variance Derivatives: A Python-based Guide (Wiley Finance)
| Author | : | |
| Rating | : | 4.18 (850 Votes) |
| Asin | : | B01MQHHBSL |
| Format Type | : | |
| Number of Pages | : | 410 Pages |
| Publish Date | : | 2014-11-05 |
| Language | : | English |
DESCRIPTION:
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 marketsGain an understanding of the fundamental techniques of modelling volatility and variance and the model-free replication of varianceFamiliarise yourself with micro structure elements of the markets for listed volatility and variance derivativesReproduce all results and graphics with IPython/Jupyter Notebooks and Python codes that accompany the bookListed Volatility and Variance Derivatives is the complete guide to Python-based quantitative analysis of these Eurex derivatives 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. Leverage Python for expert-level volatility and variance derivative tradingLis
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 powerful language to support portfolio, trading and risk management functions. 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. . 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. Enhance and streamline your quantitative analysis with Listed Volatility and Variance De
YVES HILPISCH is founder and managing partner of The Python Quants (tpq), a group focusing on the use of open source technologies for financial data science, algorithmic trading and computational finance. Yves lectures on computational finance on the CQF Program as well as on data science at htw saar University of Applied Sciences. He has written the financial analytics library DX Analytics (dx-analytics) and organizes meetup groups and
For true Pythonistas wanting to jump inside quant finance 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