Showing posts from January, 2015

Adding a Slider Widget to Implied Volatility

In the last post on Implied Volatility, we downloaded real options data from the CBOE and calculated the volatility curves/surface. We saw the calculations of 30,000 implied volatilities in roughly 10 seconds. 
In this post we concentrate on the speed of calculating implied volatility via a variety of different methods. We look at the volatility curve/surface using Python's Scipy, the NAG Library for Python, and the NAG C Library. In addition, we've added a slider widget to the Python graphs from before to see the real-time effects of changing the interest and dividend rates (see the video below). All the code can be downloaded to produce the graphs, and a NAG license is not required for the case using scipy.optimize.fsolve.
The script and utility methods can be downloaded from here. The script begins by generating sample option prices. These are fed through different root finding methods (chosen by the user) to back out the implied volatilities. 
The methods tested include: …