Quant solutions for macro traders

20170402 Japan

Over the past two weeks I’ve been travelling in Asia to Singapore and Japan, my mind simultaneously awash with discovering new places and a sampling of local burgers (yes, I make it a duty to try burgers whichever part of the world I’m in…). The first week was for work, and the second week was for (an overdue) holiday. It’s been a great experience meeting so many people in the market in Asia and also to have a bit of down time.


One thing that’s become pretty obvious is that trying to keep up with markets whilst away for an extended period is tricky (admittedly during the holiday portion of my trip, I deliberately tried to avoid checking prices!). Getting back to London, it’ll likely take me some time to get back up to date with market events and where everything is trading.The whole episode, however, did get me thinking about how macro traders try to keep up to date with the market. Let’s take for example the last release for UK retail sales, can you remember it? Probably, but can you remember the last three, to help give some context about the current print, that’s less likely. Let’s then multiply the number of economic data points for not only the UK, but all developed markets, which a macro trader might conceivably trade from a rates or FX point of view. Let’s then add to that what Fed speakers have been saying in the past few weeks, after all with monetary policy actually shifting in the US, it’s important to follow the Fed! You’re now talking several hundred data points, along with numerous text articles.


We haven’t even taken into account any of the price action or news from a broader perspective as well, which would add even more to remember. Basically, we get to the point where there is simply too much data for any person to remember quickly. The result is information overload! The solution of course is to use quant techniques to help summarise what’s been going on! This can free up time for a macro trader and potentially give them insights that wouldn’t have usually been able to capture without using quant. It also gives them more time to concentrate on generating trade ideas, rather than spending that time in the midst of a remembering a mountain of data.


So what quant techniques can we employ to help a discretionary macro trader?

  • We could for example summarise all the data releases into a single index (many banks creating growth surprise indices which seek to do this).
  • We could machine read the bulk of Fed communications into an easy to use time series using natural language processing, such as Cuemacro’s Fed communications index (or indeed we can look at alternative data in general to give us additional insights into the market, whether that is news, satelite imaging etc.)
  • We could create models to give an indication of what certain types of factors are giving like trend, which can provide an input into a macro trader’s thinking
  • We can automate a lot of daily Excel updates into Python a trader might have
  • There are literally endless possibilities for quant to help macro traders save time!

If you’re interested in hearing how quant techniques can help macro discretionary traders, drop a message to Cuemacro!