SpaceX’s IPO last week showcased continued investor appetite for equities, says Tobias Windecker, European head of equities trading at Allianz Global, touching on the record-breaking public offering of only 5% of shares and pointing to major retail participation as a sign of market confidence. Speaking to Trader TV, the head of desk, also unpacked AI and automation have become key priorities for buy-side firms, with machine learning already handling smaller rules-based trades. However, while AI can analyse vast amounts of data and can be used to identify opportunities, he says, human judgement today remains crucial for complex trading decisions.
Interview
Josephine Gallagher – So, in this conversation, we are going to talk about AI and automation, but I also do want to cover last week’s events, where we saw the record-breaking IPO from SpaceX. So, just to kick off, tell us, how have markets reacted to that IPO, and what does this mean generally for investor demand for equities?
Tobias Windecker – Well, I think, given the oversubscription, we can count that one as successful. Yeah, if you look at retail participation, I think it’s really a big thing here, not only for us in Europe, but also for the clients in the US. I mean, markets seem to digest the IPO quite well so far. US markets haven’t opened yet as we speak here, but yeah, I mean it’s definitely a groundbreaking IPO, and we will see whether this gives us a good indication where markets are heading next.
Josephine Gallagher – Very interesting. Now, moving on to the main part of our conversation, automation and AI productivity gains is a core priority for buy-side firms this year. How are you identifying where to apply AI and automation across your trading functions, and how far along are you in that journey?
Tobias Windecker – Well, for a company like ours in the asset management industry, it’s currently all about raising efficiency and productivity. There are certain parts of our business and value chain where AI is a perfect fit and can add meaningful value, probably not in the first stage in trading, but nevertheless we started looking at using AI tools and machine learning to trade parts of our exchange trader derivatives business. Quite successfully yet, and what’s much more important is that this tool is handling the less complex small orders, or orders with fixed instructions, where the human trader cannot really add value, and by that the trading team can spend more time on the really meaningful parts of our business, so complex or large orders consultancy of our internal and external clients, and it did raise within our organization the willingness to use AI.
Josephine Gallagher – Understood. So we’re in a climate where traders are having to adapt and sometimes react very quickly to headlines. For example, we have the SpaceX IPO that came out last week, and Central Bank decisions as well. So, how is that also factoring into how you adopt AI and where you apply it?
Tobias Windecker – Well, I mean, volatility is a trader’s daily job, and we have to cope with it, but you are right. I mean, those are really volatile times, and it’s probably one of the most headline-driven markets I have ever seen in my career. So, AI gives us and the trading team the opportunity to digest and analyze lots more of data information than even very experienced trader would be possible to handle, and that exactly is where AI comes in play, and will be will come into play in the future, yea. So it’s looking to recognize more quickly market patterns to give us more information about pockets of liquidity in the markets, or are there any signs of market abuse? That’s everything where AI can help a trader in their daily job. Nevertheless, I mean AI is super supportive for us, but it’s not creative, so you still will have human judgment as a vital part of the trading business, and you won’t be able to replace at the current stage of AI, the human trader through AI models.
Josephine Gallagher – Now, in previous conversations that we had, you mentioned that alpha-driven decisions should stay with the trader. Can you provide concrete examples of what you mean by this?
Tobias Windecker – Yes, of course. I mean, at AGUI we see the trading teams being part of the investment processes, so it’s our job to add as much alpha as we can to the alpha of the investment teams. You can only do that when you really have to focus on the complex and large parts of our business, and have time for precisely that. Think of complex derivatives transactions, or transactions across asset class, teams. Transactions across regions, or transactions in less liquid, hardly exchange traded equity orders, where you’re looking to get a stake, or get rid of a stake. That’s precisely where the human trader can be much better than AI, because he recognizes some patterns, he has experience in what he’s doing. He has a relationship to other market participants and can help where it’s really needed.
Josephine Gallagher – Gotcha. Understood. Now, beyond AI and automation, like what else is on your priority list for the rest of this year.
Tobias Windecker – Well, definitely the future will bring more of that what you just described. Yeah, automation and artificial intelligence, we need to reshape the trading teams over time to have a complete new generation of traders, which still have the animal spirits and everything, which makes a trader actually, but also bring along knowledge in the new technologies, coding, understanding of data analysis, and artificial intelligence, of course. At the same time, make sure that the existing know-how of our very experienced traders here in the teams are transferred to the new joiners, that is definitely priority one in our department, and we’ll make sure that we’re making the next step in trading here, and we’ll have the next evolution of trading in the next three to five years.
