Oliver Blower previously worked at the trading desks of Merrill Lynch and Barclays. He is currently CEO of telecom analytics company VoxSmart.
Otto von Bismarck once famously said, “Politics is the art of possibility.” If he had been around by now, he might have replaced the word “politics” with “artificial intelligence.”
It’s beyond frustrating that every man, woman, and dog is talking about AI in the abstract right now. Even the world’s institutional investors seem to be caught in constant hype and exaggeration.
Nvidia is a great example. Last month, the company increased its market capitalization to a staggering $220 billion just an hour after its earnings release. Nvidia essentially added more market cap than the combined value of Intel and Micron combined, making him the 6th most valuable public company in the world.
There is no planet big enough or deep enough investor depth to carry out this kind of blue-sky thinking about AI. The reality is that few people today understand what AI really means, let alone how it can be deployed to improve the business of investment banking. It’s about time that some real-world use cases beat theory.
read AI may prove to be a big problem for finance, but don’t hold your breath
A question arises here. If you’re a senior investment bank executive exposed to all the AI literature, where do you even start? It was a deal.
Stocks have led while others have followed suit, thanks to exchange-traded, liquid and transparent technology. One of his most prominent followers is Bonds. Over the years, the dog of bond market restructuring has really been swung by the tail of cash equities.
From algorithmic trading to transaction cost analysis, fixed income trading desks have historically embraced equity innovation. But with the advent of AI, we could very well reach the apex of a paradigm shift.
read Xavier Lorre: “Quantum is on us”
Unlike stocks, most of the bond market is traded over the counter. As a result, the market has become highly opaque, with varying levels of illiquidity dotted across every sector, especially corporate bonds.
This is why there is such a wide range of views when it comes to prices for multiple commodities. Fixed income markets have also become more complex and highly nuanced over the last decade, but the valuation process remains relatively straightforward. Days or even weeks may pass without a particular high-yield bond entering the market. This means more commodities are left without market-based prices.
Collecting all the disparate data relevant to the fixed income desk and putting AI on top of it is a viable way to solve some of the long-standing pricing and illiquidity problems in this market.
As it stands, no one has described in such detail how AI can bring tangible benefits to investment banking executives. Until the industry as a whole begins to have mature, pragmatic, and hands-on discussions about concrete use cases for AI, we are fascinated by grandiose, hollow statements about how this technology will transform capital markets. will continue to be
Anyone looking to start a reverse equitization of bonds as a new AI possibility?
