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you have had since at least the financial crisis from a top-down level ,” he explains .
“ The other side of that is the bottom-up liquidity when trying to buy a lot of a single name is much worse as more focus has gone to top-down . It ' s also drawn some experience down and so the knock-on effect is that bottom-up liquidity is reduced . If you need to trade three hundred million in Kraft then it ' s a lot harder now than it used to be especially pre-crisis . But even from a post-crisis level , the liquidity was worse .
“ The street goes through an evolution over time . What we ' re seeing partly because of the volumes being traded in portfolio trades is that there is a focus to move that risk . That is a very different skillset for the sell-side than it is trying to move 300 million of a single name . The street is focusing on this top-down element and so there ' s less skill on the bottom-up side . That provides an opportunity for a firm like us where we are very bottom-up focused in our research and our capabilities .”
A data-focused future Raymond ’ s focus , as with many other heads of trading , is now on the fine tuning of its processes using data . The future focus is centred on fixed income , which he claims has a way to go when compared with equities or foreign exchange given the nature of those businesses .
“ In fixed income , it is a lot more difficult to run the same kinds of analysis [ as equities and foreign exchange ]. I might get an order in the morning for 20 million to trade and I might only be able to trade 10 or I might be able to take zero ,” he explains .
“ I have to work that order and the market can move throughout the day . If I ' m measuring my personal performance on that trade versus when I received that order , it might look really good or it might look really bad based on what the market does and based on the liquidity of that individual trade . If the market got better at analysing that would add a lot of value .”
Central to several ongoing market discussions on the buy-side is the use of data pre-trade to better inform trading decisions , and LGIM is no different from its peers in this regard . Pre-trade particularly when it comes to LGIM ’ s portfolio trading business is front and centre in Raymond ’ s mind going forward .
“ Having done so many portfolio trades , we have a very good idea about who is going to win the trade or who is going to be competitive . But we ' re doing more work to be better about that – we ' re doing
“ When I first heard about fixed income ETFs , I said this is not going to work and this is going to decrease liquidity in fixed income . I was completely wrong .”
more work for beta portfolio trades where we ' re trading 100-line items because we want to add risk or to take risk off for the portfolio ,” he adds .
“ What we ' re trying to do there is partner with some of the electronic trading platforms that we trade PTs [ portfolio trades ] on . We have data on the 1000 portfolio trades that we ' ve done over the past four years . They have data on everything done on their platform and in the market . I want to reduce transaction costs but keep the top line steps of my portfolio – the duration , the spread target , the ratings target – and keep that within a 10 % range of where I started .
“ How can I optimise for transaction costs ? OK , let ' s take out these five securities and I can optimise for transaction costs . Let ' s get really fancy and say let ' s optimise for 50 % transaction costs and 50 % spread . What does that look like ? Can we talk about substituting securities to do it ? If we can get to the point where we can do that ultra-efficiently in a nice GUI and can make that decision within seconds based on the analysis and the previous
30 // TheTRADE // Q3 2024