The Markets ConversatION Podcast

Quick Takes: Time Series of Swap Prices and Volumes

January 5, 2024 | Duration: 09 minutes

Speakers: Amir Khwaja and Chris Barnes


In this episode, Amir breaks down how to analyze datasets in new and novel ways by showcasing a new feature on the Clarus website called SDRView.

SDRView has transaction level data for OTC Derivatives, made public under CFTC Regulations, which consists of more than 50 fields for each transaction.

Unlike Bonds or Equities, there are no security instruments as such for Swaps and OTC Derivatives, rather a set of fields, that allow customers to determine if it is a standard trade and the most common nomenclature/symbology for standard Swap instruments is the Bloomberg Ticker.

The new Ticker Summary view uses this to conveniently access a large historical record of trades for price and volume summary measures.


Ali Curi: Hi everyone, and welcome to ION Markets Quick Takes. I’m Ali Curi, and every week, along with my guests, Amir Khwaja and Chris Barnes, we take a quick dive into the headlines on the Clarus blog. Let’s get started.

Hi Amir. Hi Chris.

Amir Khwaja: Hi Ali.

Chris Barnes: Hey Ali, how you doing?

Ali Curi: I’m doing great. Amir, let’s start with you.
What’s your Quick Takes for this week? Which headline from the Clarus FT blog would you like to discuss?

Amir Khwaja: Sure. So I’m going to talk about “Time Series of Swap Prices and Volumes”.
Ali Curi: All right, let’s have at it.

Amir Khwaja: In the Clarus SDR View product, we’ve always collected for more than 10 years now, swaps data from trade repositories.

So that gives us information on what trades, and we have about, about 40-50 fields that describe the trade. I think swap markets, unlike futures or equities or bonds, every trade is an individual trade. And based on the field, you have to work out the instrument that trades to be able to compare price. And, most of our customers consume this data either to our professional GUI, where people in the market, like traders, brokers are looking at what trade is at what time, what size, at what price.

And then we have a researcher application for researchers and analysts to look at long term trends. And long term trends, we’ve really focused on volume trends, how much trades in a given day. And we’ve used filters like currency product to give people long term trends in dollar swaps volume or euro swaps volume or dollar cross currency euro basis swaps volumes, right?
But for our researcher audience, we haven’t given them much about price information. Because to do that, you have to aggregate comparable price instruments. And the way we’ve done that, at least in the database for years, is to use a Bloomberg ticker, which is a well known identifier for swaps traders of the Bloomberg terminals to identify the instrument that trades in the swap market, right?

Whether it’s a spread over or a curve switch or a butterfly. So now what we’ve done is in our researcher product, there’s now a new screen where someone can enter a ticker, so for a spread over a dollar SOFR swap, and get a whole time series back, not just of number of trades on a given day and the volume, but also a volume weighted average price.

So that gives us a nice time series of prices and volumes for instruments that has meaning in the marketplace. So rather than just looking at volumes for dollar swaps, we can now look at the volumes and the price volume with an average price of a five year spread over or a 5-10 curve switch trade or a, 2/5/10 butterfly trade or a cross-currency basis swap EURO USD in two years.
And that’s good information for analysts doing long term analysis of markets, both on how price changes and how volume changes. And that can be done for us, going back many years now, we can look at a daily time series, weekly time series, a monthly time series. In every case, it will search the millions of records we have or transactions and find that instrument that we’ve stamped with the appropriate Bloomberg ticker and it will find its time series of price, number of trades, volume.

And that just helps transparency. And for us, it’s important, it’s a new or a different way to make it easy to look at the data that we already have. And ease of use for analysts is very important in that field. So that’s a blog I did. I was going to just ask Chris if you had any questions on that, Chris.

Chris Barnes: I have one word, Amir. ISINs.

Amir Khwaja: That’s a bad word for the swaps market, yeah?

Chris Barnes: Oh, yeah? Oh, sorry.

Amir Khwaja: You’re setting me off.

Chris Barnes: I read it and just expected it all to be based on ISINs. That’s how, what Europe did.

Amir Khwaja: So the background there is the equivalent of this data, or at least in Europe under MIFID 2. Decided to use ISINs, which are used in the bond markets for securities to identify swaps and OTC derivatives.

Apart from the ISIN definition included, I think, a fixed maturity date, not a five year tenor. So there are literally millions, I lost count how many, 40 million last time I checked on the ISIN website, new ISINs created for OTC derivatives, which, hindrance in transparency makes the data pretty, pretty unusable ’cause every time I do a five year swap, each day there’s a new ISIN for that trade. So I can’t compare time series of five year swaps by search for ISINs ’cause I need a new ISIN every single day. So if I’m looking for the past one year’s history of five year swaps in MiFID Euro data, I need to have 250 ISIN lookups.

The mind boggles, it’s just nonsense, right? So that’s why using the OpenFIGI and Bloomberg ticker, there is an appropriate identifier and the either the OpenFIGI ID or the Bloomberg ticker that stays constant, that makes sense for OTC derivatives products. And it allows people to really query very easily transparency for U.S. OT derivatives.

So unfortunately, to do that for European data would add so much complexity to the query. Imagine doing a query in SQL where you’re sending 250 IDs in an “IN” clause. Obviously you can’t do that, right? So you have to do some other scheme, right?

Chris Barnes: It’s literally crazy. We spec’d, we spec’d this product together, right? And it was never a question of what should we chart? It was always, it should just be the Bloomberg ticker. It’s the obvious way of looking at swap markets. So the other thing I wanted to highlight is just how meaningful a volume weighted average price is, because when I used to trade swaps, the biggest frustration with all of that data is that your client’s asking you for prices in a yard.

And when you look at broker screens and what the prices are, they may be tradable in clips of 50 million. And so trying to work out what the fair price to do a billion dollars is when the market is quoted in clips of 50 is exactly what swap trade traders are doing day in day out. And the P&L on a swap trader’s book is therefore dictated by your volume weighted average price. Volume weighted average price that you get in and the volume weighted average price that you get out and that is something that you don’t see in swaps markets reflected anywhere, right? And so whilst you see these quotes moving all the time, there’s no way of knowing the sizes unless you’re in CLOB on a SEF.

It’s a very different concept to a traditional exchange traded product. And so I think really going forward for swap markets. This type of VWAP analysis is really helpful. It allows you to benchmark your traders. You can look at their series of trades on a day, see what they achieved as a VWAP compared to what the market achieved.

There are lots and lots of potential uses for this type of data, which is very different to your traditional data, which is quote driven broker screens. That’s something that I really like about the SDR data recently, is that I think I’m right in saying if we tried to produce these charts back in 2013, the data would have been so dirty and prices missing and units wrong that the charts wouldn’t have been as reliable as they are now. Is that a fair thing to say?

Amir Khwaja: Yes, I would say so, Chris. Yeah, I think your point is right, by able to mine the data for new types of use cases and VWAP, is a nice use case. And I think we could take it further, right? We could look at intraday, the at the moment we’re doing daily, weekly, monthly.

So there’s no end of analysis that you could do. So really, it’s our goal to make it easy for people to do that analysis. Using our tools, provide transparency, help people think of things they would want to do and just make it very easy. And I love your point there about, what a trader is doing, right?

So they’re obviously making prices, they’re hedging, and say a volumetric average price of making prices and hedging is kind of their P&L and all this stuff really helps you look at what the market is doing, what you’re doing and, and we’re great believers that people should be benchmarking their trading, their hedging, their risk, with volume of the market and price in the market.

Chris Barnes: Agreed. If you look at a portfolio manager, if you look at an ETF, they’re all benchmarked on their alpha, their relative performance compared to what a market…, what analysis like this allows you to do even for a market making swaps desk.

Amir Khwaja: Great. Thanks, Chris. Yeah. So I think, Ali, so I think that’s really what I wanted to cover.
The blog is called “Time Series of Swap Prices and Volumes,” and it allows people to very quickly search for a long time series of price and volume for a whole range of swap contracts, whether interest rates, cross currency basis, et cetera.

Ali Curi: Great. Thank you, Amir. And thank you for sharing again, the title of your blog post.
Amir Khwaja, Chris Barnes, thank you both for sharing your Quick Takes. And that’s our episode for today. You can read more about these topics on the Clarus blog and you can follow ION Markets on X and on LinkedIn. And from your friends at ION and Clarus, we wish you and your family Happy Holidays and a very Happy New Year.
Thank you for joining us this year. Let’s do it again next year.