Off Topic| Wide and Deep Learning in R

R is an excellent environment for quick and dirty data science. I am a R user and obviously a bit biased, but between Python and R, R has always had the edge for data visualization and quick hypothesis testing. If you do not find the latest and greatest methods of bleeding edge analytics somewhere available already within the strong R package ecosystem, it is more or less safe to assume it does not exist anywhere else either. And forget Python, the IDE from R Studio is perhaps the best IDE across any development platform (although the Visual Studio perhaps has a better debugging interface). But one area where R has been weak is in machine learning, especially in the deep learning area. And with the explosion of interest (and fad?) in deep learning, this has become quite a glaring gap.

But hopefully not anymore. We already have Google's TensorFlow available in R for a while. But to be honest, it did not have much feel of R in it and looked like a deprecated version of the Python release. However, very recently the R Studio folks released a R support for the excellent Keras high level API, with back-end of TensorFlow. This feels like R (with some quirk like in memory modification of objects) and works like a charm. Although it runs on top of a local python platform, the package exposes pretty much all the functionalities Keras support.

You will already find a list of examples in their site here. Here is to add a basic example of how to set up a wide and deep learning network. This involves creating two separate learning network. The wide one has only one layer (effectively a logistic regression of sort). The deep network is created separately. The output of two is combined (concatenated) in a final decision layer (this is slightly different architecture than the TensorFlow example). This is run on the usual Census Income data-set. The error rate for this set up is around 16 - comparable to other methods officially reported.

Markets | Positioning For The UK Election

UK goes in to elections this week. Since the surprise announcement in April, the polling has narrowed quite a bit between the two major parties. (See chart below - although note a large part of Labour gain has been at the expense of smaller parties, especially UKIP). However although the markets had a sharp initial reaction to the announcement, the moves subsequently have been more cautious. The outcome of the election is touted as determining the direction of Brexit negotiation. And markets appear to be waiting to assess the situations once the results are out. However, what the market will focus on in Thursday evening is not only the UK's divorce from the European Union.
 

 

Looking past the Brexit, the major differences between the Tories and Labour campaign is their respective stance on tax and government spending. If conservatives have their ways, it will basically continue the status quo, without any significant change in taxation or spending.

 

On the other hand, the labor plans to increase taxation (focused on corporates and top earners) as well as infrastructure spending. The National Transformation Fund with a corpus of £250b proposed by the Labour compares to a £23b National Productivity Investment Fund of the Tory government. The net effect is an increased need for borrowing, put at 45b estimates by the Tories. The other major campaign difference will perhaps add to this bill. The Labour maintains a so called "soft Brexit" approach, and a change in government in London may actually increase goodwill in Brussels. But Labour's negotiation aims also implies the UK may actually end up footing a substantial Brexit bill.

 

Put together, these means increased issuance of Gilts for a Labour government compared to the Tories. So in an unlikely scenario of a major Labour win, all the market forces and economics fall nicely in place. Gilts will sell-off on the back of fiscal plans - along with a steepening of the curve. Sterling pound will rally, supported by both the new Brexit stance and a rising yields. Equities will sell off, triggered by both taxation and a rallying pound and rising yields. For a strong conservative win, the impact is mostly in market sentiments than any dramatic departure in economics.
 

As we see from the charts above, the correlation in Tory polling vs. GBP and Gilts have mostly switched to negative off-late (and to rather positive territory for Labour). These correlations implies a Tory win will have some downside impact for GBP. But strong win may even see a small upside driven by a reduced political uncertainty before the economics kicks in. Gilts have little scope to respond vigorously, facing the inflation pressure on one hand and a more than expected Dovish BoE on the other - marginally positive for Gilts (yields go down). Equities will perhaps shrug off all of it.
 

That leaves us with the scenario of a Labour-led coalition government. This will in general hurt the market sentiments, with a higher chance of a addled up Brexit negotiation and potentially another election around the corner. This will be a sort of risk-off moment for UK, with sell-off in pounds and equities and a rally in gilts. This will also be a shock event - as at present the betting markets prices in a 90+ % probability of a Conservative majority. Assigning some reasonable probabilities to various outcome, the pay-off matrix looks like below. And it suggests a short GBP position before the election.

 

 

Position-wise we have seen a large reversal of positions in futures (as per CFTC reports) after the election announcement - a large decrease in net speculative shorts in Sterling pound. On the other hand, the currency options market shows a significant increase in negative skew pricing (demand to protect from a sterling crash). In fact the GBP 1 week 10 delta risk reversals is near the highs around the Scottish referendum in 2014 (although much less than the highs reached around Brexit referendum). So it appears we have some options positioning (or at least demands) - indicating a position switch from futures to options. Assuming most dealers in the FX markets will have the opposite position, this adds to a negative bias on Sterling.