Blog Archives

A quick look at FX realized vol

May 31, 2014
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A quick look at FX realized vol

Much has been said about the decline in volatility. At the moment I am very active in FX spot trading and as a generalization do better the more vol there is. I wanted to see how things stood on the crosses I am most active in, namely EUR/USD, GBP/USD and USD/JPY. I took hourly data from FxPro (not my broker, nor...

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RcppArmadillo cheatsheet

May 17, 2014
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I have been using RcppArmadillo more and more frequently, so thought I would make a cheatsheet/cookbook type reference that translates common R operations into equivalent arma code.I have put them up on a github wiki page here.The functions are al...

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Just for fun: attractors in R

November 24, 2013
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Just for fun: attractors in R

I have a borderline unhealthy obsession with attractors. I thought I got it out of my system, but here we are. For whatever reason, I felt like making some in R.You can find the R code here. It uses the attractor function to define density in a ma...

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Book Review: Applied Predictive Modeling by Max Kuhn and Kjell Johnson

November 24, 2013
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This is a gem of a book.From the introduction: We intend this work to be a practitioner’s guide to the predictive modeling process and a place where one can come to learn about the approach and to gain intuition about the many commonly used and modern, powerful models. …it was our goal to be as hands-on as possible, enabling the readers...

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Another Rcpp/RcppArmadillo success story

October 25, 2013
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I finally had an excuse to try out RcppArmadillo and was amazed at just how well it worked out.The exact details are a bit beyond a blog post, but basically I had a matrix of roughly 80,000x2 double valued samples (call it A) and needed to fi...

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The case for data snooping

October 25, 2013
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The case for data snooping

When we are backtesting automated trading systems, accidental data snooping or look forward errors are an easy mistake to make. The nature of the error in this context is making our predictions using the data we are trying to predict. Typically, it comes from a mistake with our calculations of time offsets somewhere. However, it can be a...

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Building models over rolling time periods

September 23, 2013
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Often I have some idea for a trading system that is of the form “does some particular aspect of the last n periods of data have any predictive use for subsequent periods.” I generally like to work with nice units of time, such as 4 weeks or 6 months, rather than 30 or 126 days. It probably doesn’t...

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Type conversion and you (or and R)

September 5, 2013
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Types and type conversion can be a tricky and intricate topic, and sometimes can lead to some real head-scratcher issues in R. Hence a somewhat confusing title.This is for people still relatively new to R, and I will skip some gory details. Actually I will skip most of them, the canonical source for type and conversion information is the...

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A volatility filter using historical vol

March 6, 2013
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A volatility filter using historical vol

We have been looking at a way to improve risk adjusted returns by using a volatility filter. Although we could use VIX or equivalent, it turns out that historical volatility will work just as well, if not a little better.You can see part 1 here Digging into the VIX, and part 2 here What can we use...

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What can we use the VIX for?

March 3, 2013
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What can we use the VIX for?

In part 1, we took a look at VIX and the relationship it had between historical volatility and realized volatility.Continuing on, I thought I would take a look at next day returns and the VIX. There is a relationship between SPX and VIX in that when SP...

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