Clarus Financial Technology

US Treasuries and Spreadovers – Market Comparisons

Half of all trades are not what they first seem!

Amazingly, it’s been over six months since we last took a look at Spreadovers. Back then, I used the identification of package trades to highlight that over half of the SDR trades were linked to at least one other trade. Therefore, without the Clarus identification of their package type, the price information is pretty opaque and the standard coupon yields little value.

Now, we can run that analysis as a single query using SDRView. Reducing my 1,000 words of quality analysis to an executable line of code – such is life in fin tech I guess.

Looking at packages across this year, we can see that this claim stays broadly stable – only around 50% of trades can be attributed to outrights:

SDR Trades by trade type. Only around 50% in any given month can be considered an Outright trade.

And remember that could be further distilled into spot, forward, IMM etc trades. A point we’ve made before, but it’s worth repeating when considering anything to do with Trade Reporting.

But this week, let’s take a detailed look into Spreadovers.

The Spreadover market vs the UST market

I can’t believe I’ve not done this blog before! Having had a delve into the SIFMA data set on US Treasury Average Daily Volumes, it is high time that we compare the market in US Spreadovers with the underlying US Government bond markets.

Overall Volumes

We at Clarus fully support the recent discussions over UST reporting plans and we think it would bring welcome transparency to one of the largest markets in the World. However, there is some useful data already out there. SIFMA, for example, issue some statistics about volumes. Below, I use this high-level data to compare to some amalgamated statistics of the Spreadover market.

Because SIFMA does not provide trade-by-trade figures, we need to talk about Average Daily Volumes. Whilst this may be a nice large number, it doesn’t account for the subtleties of duration differences between bonds – so sadly we can’t leverage our DV01 stats for swaps to their full potential. However, SIFMA do split the ADVs by maturity, so we can compare like-for-like notional by maturity bucket.

The overarching message is that Spreadovers are a tiny percentage of turnover compared to the underlying cash market:

Spreadovers account for around 2.3% of daily UST trading

Showing:

The fact that Spreadovers only account for a small portion of UST trading shouldn’t be that surprising, considering:

SDR CustomView Spreadover Trade Counts

And along similar lines….

Given the inherent link between the markets and the small proportion of UST trades attributable to swaps trading, it is perhaps not surprising that there are two clear features in the data. Namely:

Percentage of UST turnover attributable to Spreadovers is a pretty stable time-series

 

UST and Spreadovers have similar maturity profiles

Showing;

Maturity Profile Differences

The chart above can be further analysed to drill-down into the differences between the two data sets – as that is really what is interesting when they are so similar! Below, we show the % differences between the two maturity profiles:

Differences in the maturity profiles between UST trading and Spreadovers

Showing;

In Summary

Stay informed with our FREE newsletter, subscribe here.

Exit mobile version