Clarus Financial Technology

The Average Maturity of Swaps Is Increasing

SEFView Data

When I look at data for our markets, SDRView tends to be my first port of call. It is the most transparent source of data and allows us to run all types of analysis as trades are reported. However, as we acknowledge every month in our Swaps Reviews, the individual transactions are capped at the reporting threshold. It is therefore useful to look at SEFView as well.

The analysis I wanted to look at this week could easily be affected by very large trades. We are going to look at the Average Maturity of all USD Fixed-Float Interest Rate Swaps. These averages can clearly be affected by large trades over the reporting thresholds. Fortunately, SEFView data is not capped and includes maturity data that allows us to calculate the DV01 on each SEF.

Total DV01 Per Month

First off, we define the data set we are going to use. We’ll look at the largest market – Fixed Float, USD interest rate swaps.

Total DV01 traded per month. Volumes split D2C and D2D. The Green Line shows the % of D2C trades each month.

Showing;

Average Duration

We can export all of this data by tenor from SEFView. On a weekly basis, this gives us an impressively large time-series of data (see chart).

Using DV01 as our measure, we can calculate the volume-weighted average maturity of trades across each SEF. We can do this on a daily, weekly, monthly etc basis. We call this the Average Duration.

Let’s take a look at the trends in Average Duration. First – a high level monthly chart across the whole market:

Average Duration (in years) traded across SEFs each month

Showing;

Average Duration by Activity

Over the past three years, SEFView data therefore suggests an extension in duration across the market as a whole. Let’s see if these changes are consistent across the data series.

First – the same time-series on a weekly basis with a ten week rolling average:

Average Duration per week. Orange line is the ten week moving average.

Showing;

Let’s now look at this data by venue type – Dealer-to-Dealer (D2D) and Dealer-to-Customer (D2C) behaviour.

Average Duration by Venue Type

Showing;

Agency Execution and Differences in Hedging Behaviour?

I wanted to analyse the differences between the two time-series in more detail. I was following a few of these thoughts:

Therefore, let’s look at the average maturity mismatches in the time-series data between D2C and D2D SEF venues on a monthly basis:

Duration mismatches per month between D2D and D2C venues. Time-series is calculated D2D minus D2C, therefore a positive reading means that Dealers are trading longer maturity than Clients.

Showing;

In Summary

Stay informed with our FREE newsletter, subscribe here.

Exit mobile version