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This repository provides all Python codes and Jupyter Notebooks of the bookDerivatives Analytics with Python by Yves Hilpisch.

Oder the book herehttp://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119037999.html or herewww.amazon.com/Derivatives-Analytics-Python-Simulation-Calibration/dp/1119037999/.

There are two code versions available: forPython 3.6 andPython 2.7 (not maintained anymore).

There is now ayaml file for the installation of required Python packages in the repository. This is to be used with theconda package manager (seehttps://conda.io/docs/user-guide/tasks/manage-environments.html). If you do not have Miniconda or Anaconda installed, we recommend to installMiniconda 3.6 first (seehttps://conda.io/miniconda.html).

After you have cloned the repository, do on theLinux/Mac shell:

cd dawpconda env create -f dawp_conda.ymlsource activate dawpcd python36jupyter notebook

OnWindows, do:

cd dawpconda env create -f dawp_conda.ymlactivate dawpcd python36jupyter notebook

Then you can navigate to the Jupyter Notebook files and get started.

You can immediately use all codes and Jupyter Notebooks by registering on the Quant Platform underhttp://wiley.quant-platform.com.

Check out ourPython for Algorithmic Trading Course underhttp://pyalgo.tpq.io.

Check out also ourPython for Algorithmic Trading Certificate Program underhttp://certificate.tpq.io.

© Dr. Yves J. Hilpisch | The Python Quants GmbH

The Quant Platform (http://pqp.io) and all codes/Jupyter notebooks come with no representations or warranties, to the extent permitted by applicable law.

http://tpq.io |dawp@tpq.io |http://twitter.com/dyjh

Quant Platform |http://wiley.quant-platform.com

Derivatives Analytics with Python (Wiley Finance) |http://derivatives-analytics-with-python.com

Python for Finance (O'Reilly) |http://python-for-finance.com

Python for Algorithmic Trading Course |http://pyalgo.tpq.io

Python for Finance Online Training |http://training.tpq.io