The corporate bond market is worth $41 trillion. It’s one of the most important markets for pensions, corporate balance sheets, and portfolios all over the world. Market participants crunch reams of data in high pressure environments to make the best decisions and find alpha in a hyper competitive space. Why has this advanced and competitive market not seen the technological innovations that other markets have benefited from?

Information in the corporate bond market is gold. This could be a pricing feed, reference data, completed trades, or the newest, most important data point: orders. In a market with deep liquidity and lots of trading, these data points are relatively less valuable – when everyone knows what is going on there’s no need to be too secretive. Just make sure you are not too far outside the market. Other asset classes enjoy fewer individual instruments issued and a nationally organized trade reporting system. Not so with credit.

Only three in ten corporate bond trades are made over electronic venues. These trades rely on the blunt tools of a central order book, sharing liquidity (and valuable information) with the whole market. Apart from this, traders are left with voice trading, hit-or-miss dark pools, or… not trading. Participants are incentivized to put any information into the market. As described above, these data points are valuable pieces of information. In an illiquid market, any move costs something to the trader. Offer to sell, and others who see that will lower the bid. Bid to buy, and the sellers will ensure the price goes up.

It might not matter if demand for trading was going down. But that’s not the case. In the US alone, the corporate bond market grew to an astonishing $10tn in 2021. Asset managers are searching for yield, refreshing portfolios at an ever-faster rate in the hunt for alpha. Better performance is the key in a world of low and no cost brokerage fees.

Much of the work that is entailed in a trading desk that is required to move bonds around the secondary market is all before that order occurs: the challenge is to find the correct part of the market to place that order, and then find the liquidity information about the bond in question. Selecting the correct counterparty to start to work with takes significant time.

Traders seek this performance today from a variety of order types which have evolved to address specific trading scenario needs. These include list trading, block trading, RFQ, and portfolio trading, to name a few. These are effective, but don’t solve the problems of data leakage and a wide ecosystem of opportunities to search.

Our own model, using distributed ledger technology allows for automatic enforcement of the agreements made in the marketplace through a set of programmed codes and smart contracts, which run automatically on pre-defined conditions. Those conditions define the type of opportunities the trader is interested in and can even include logic to alter the order or execute the trade. A smart order automatically searches the market for the right opportunities and doesn’t reveal itself unless those opportunities are found.

A smart order will help the user find the right part of the market to get the trade done without the burdensome time spent in searching – it is based on the concept of assisting the human – the trader is important, and they are empowered and not replaced by the smart order.

Smart orders have three levels of benefits for the trader:

• They can help the trader engage in the right trading method – whether that is an RFQ, a resting order, and so on. They can share interest with anyone else in the market on a smart basis.
• They can be predicated on a specific name, or a high-level order that only describes the type of risk the trader is seeking. The user can set the instructions for the smart order, those instructions describe what the smart order is looking for and when the smart order reveals itself. And that efficiently finds the right counterparty in the market, and does so without data leakage, which is incredibly powerful.
• With the advent of algo and systematic trading, firms are looking for a way to add more conditionality at the order level (at the exchange level), they allow for entering an expression into the market, listen, take that back and compute and put in another order, automatically. They can add a level of conditionality for the algo trade.

A smart order searches the entire rest of the market to find the very best possible counterparties, allowing the trader to get on and do other things, maybe bigger trades, maybe more complex trades, but it allows them to do a lot more with a lot less.

For the sell-side, smart orders are a powerful tool for traders to more efficiently find the trade they need, sales teams to find new opportunities in the market, and algo teams to deploy smarter, faster systematic strategies.

For the buy side, smart orders help traders and PMs evaluate opportunities with a more data-driven approach. It can even enhance relationships because you can incorporate those preferred relationships into the smart order logic.

At LedgerEdge, we build tools and systems that solve real problems for real users. We know the market inside out, and we have designed for this by working with our customers from day one. We are focused on user control, clarity, and better execution today. LedgerEdge is taking the market where it needs to go, and we have the ambition to address new markets and new asset classes. It’s trading technology, with a lot of advanced technology for the future.