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John wrote a great post a few months back on the virtues of lazy evaluation and using this to generate infinite length geometric Brownian motion prices series. Lazy evaluation is popular in functional programming, whereby the evaluation of expressions is deferred until when they are actually needed. The purely functional language Haskell defaults to lazy … Continue reading »

Variance Factors on VIX Futures II - Principal Component Analysis

In my last post I demonstrated how you can generate synthetic futures prices. In this post I am going to build on this and show how you can apply principal component analysis (PCA) to determine how much of the variability in returns each of the different futures are responsible for. Creating our data set was … Continue reading »

Variance Factors on VIX Futures I - Synthetic Futures

In her paper on ETNs on VIX futures, Carol Alexander demonstrates how principal component analysis can be used to identify the main variance factors in the term structure of the VIX. Over the next couple of posts I am going to demonstrate how you can implement this. Principal component analysis (PCA) is a useful tool … Continue reading »