Dan Barnes:

Welcome to Trader TV at FILS. Your insights into institutional trading. I'm Dan Barnes. Electronic trading in large size is the holy grail for bond traders. Here to discuss how they can potentially find that grail is AJ Cass, Head of Market Structure and Liquidity at LTX. AJ, welcome to the show.

AJ Cass

Thank you so much, Dan. It's a pleasure to be here.

Dan Barnes:

Average trade sizes have been falling, indicating that blocks are becoming harder to execute. What's your take on the liquidity picture?

AJ Cass:

Average volumes in the corporate space has been hovering about 40+ billion a day for the last couple of months. So the overall volume is good. IG is probably 37% of that, and high yield, which has had a very nice growth in the last six months or so, is up to 32%. But the problem we're seeing is in the trace buckets of where that volume is coming from. And that volume is coming from increased in the buckets of 500 to 1 million and under. So, it's definitely a real challenging environment to trade larger size, but we think it's a wonderful opportunity and the data set which we're going to focus on is those larger size trades.

Dan Barnes:

So how does data shift to supporting data in larger sizes?

AJ Cass:

I think data will not only support but drive this shift to trading in larger sizes and I think a lot of that is coming from pre-trade data which helps assess real-time liquidity. So at LTX we have a liquidity cloud. Think of that as a repository of IOIs, axes, and positions from both the buyside and the sell side which gives them a clear picture on exact liquidity at that moment in time and where they can go to get that liquidity. Another focus is our dealer selection analysis to help the buyside figure out the best dealer to go to - dealer or dealers - that’ll give them the optimum amount of liquidity at that moment in time. Some of the drivers of this data is obviously the behavior in a dealer’s axes, behavior in their positions, how they trade that bond, how they trade similar bonds. And, also, physical behavior: response rates, response times, response prices. So, we certainly help the dealer focus on what is important to help them execute with their customers. I mean traders typically do not send out a bid 1 or an offer 1 on 15 or 20+ million. All that’s going to do is spam the marketplace – information leakage – they’ve disclosed to the marketplace what they’re looking to do, and that doesn’t solve any problems. So, we think with our pre-trade analytical tools, will eliminate that and help them get liquidity from their customers when the time is right for them.

Dan Barnes:

So what are your expectations for liquidity and larger sizes going forwards?

AJ Cass:

I think what’s going to help with getting larger sizes done is not only the data and the pre-trade analytics we bring, but I think taking a look at some of the mechanisms for how we trade and how we trade in an RFQ. So at LTX, we're announcing RFQ Plus, and by adopting and embracing the standard RFQ. But inserting our tools, we think we can help traders trade larger size. Not only our dealer selection analysis, which helps the buy side figure out which dealer or dealers to go to that moment in time for liquidity, but also, we're incorporating our patent pending liquidity aggregation capabilities. In a normal RFQ, the winners usually take all. We've developed a RFQ protocol where we aggregate the responses not only to get more size done, but possibly a better price. So, with this new RFQ+ protocol, between the pre-trade dealer selection analytics and our aggregation capability, we're really focusing on leveraging our AI to bring RFQ to a new level.

Dan Barnes:

AJ That's been great. Thank you so much.

AJ Cass:

Thank you very much for having me.

Dan Barnes:

I'd like to thank AJ for his insights today and of course, you for watching. To catch up on our other shows or to subscribe to our newsletter, go to TraderTV.net and don't forget to watch Trader TV this week. 06:45, a.m. UK time every Monday.