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Volatility

This category contains 6 posts

Ether Mining 101

I gave a talk last night about getting up and running mining the cryptocurrency Ether at the SydEthereumMeetup last night. The slides from my talk are available below. Thanks to Tyro for the space, and the SydEthereum crew for putting on such a good night.

Lazy GARCH

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 »

VIX Futures Expiry Dates

As VIX futures do not expire on the same day each month, I thought I'd share the following code you can use to determine the when the next expiry date is. There is one caveat - if the CBOE is closed on the third Friday of the month the date moves back one day, you'll … Continue reading »

Parkinson Versus Close to Close Volatility Estimators

The Parkinson volatility estimator provides an alternative to the close to close estimator for determining historical price volatility. It uses a range based sample interval - high() and low() price log returns in its estimates, instead of a fixed sample interval such as the close price log returns used by the close to close estimator. … Continue reading »