Today's financial market environment demands for ever shorter times-to-insight when it comes to financial analytics tasks. For the analysis of financial times series or for typical tasks related to derivatives analytics and trading, Python has developed to the ideal technology platform.
Not only that Python provides powerful and efficient libraries for data analytics, such as NumPy or pandas. With IPython there is a tool and environment available that facilitates interactive, and even real-time, financial analytics tremendously.
The tutorial introduces into IPython and shows, mainly on the basis of practical examples related to the VSTOXX volatility index, how Python and IPython might re-define interactive financial analytics.
Quants, traders, financial engineers, analysts, financial researchers, model validators and the like all benefit from the tutorial and the new technologies provided by the Python ecosystem.