| Good morning. US stocks are on course for their best week of the year after reassuring economic data. SpaceX is launching a methane satellite. And the yen carry trade is back. Here's what markets are talking about — Morwenna Coniam. Want to receive this newsletter in Spanish? Sign up to get the Five Things: Spanish Edition newsletter. US stocks are on course for their best week so far this year after a flurry of data spurred optimism the economy will avoid a recession and is heading for a "Goldilocks" scenario of contained price pressures and resilient growth. The S&P 500 has rallied 3.7% this week, while the tech-heavy Nasdaq 100 is up more than 5%, the biggest gains for both indexes since November. Asian stocks also headed for their best weekly performance in over a year, led by Japan as a weak yen boosts exporters' earnings prospects. The currency is set for its sharpest weekly drop since May, easing fears that yen-based carry trades are unwinding. Nomura has seen a variety of investors start borrowing the yen again to invest the proceeds elsewhere in higher-yielding assets, suggesting corporate clients and hedge funds, who have been enthusiastic carry traders, are getting back into those deals. It's been a brutal week for Iron ore, which hit the lowest level since 2022 on concern steel mills in China are cutting back on output due to lackluster demand and sinking product prices. Supplies from miners have also remained robust. The steel ingredient has lost almost 9% this week — the most since March. If weak prices persist, it'll be a challenge for the highest-cost producers as their operations risk becoming unprofitable. Bayer shares jumped in Germany following a significant win in long-running cancer litigation over its Roundup weedkiller. A Philadelphia appeals court said federal regulations governing the pesticide's warning label supersede laws under which a Roundup user in the state claimed Bayer's Monsanto unit should have warned them about cancer risks. The ruling suggests one of the central claims against the company may fail in state court, where the majority of the current cases are. SpaceX is launching a methane satellite to hold super polluters accountable. The Tanager-1 satellite, scheduled to launch on Friday, will be managed by a nonprofit carbon mapper and will make the data available once it's operational in the coming months. It's the second methane-detecting satellite launched in the past six months by a nonprofit, reflecting the growing scrutiny around the potent greenhouse gas and the satellites' low cost relative to others used for atmospheric monitoring. This is what's caught our eye over the past 24 hours. More than a year ago, I interviewed a few hedge funds about how they're using ChatGPT. At the time, it already seemed clear the new tech could be very helpful in automating grunt work, but it was unclear what more it could do and data security was a big question mark. Over the last few months I've been speaking to hedge funds again and trying to get a sense of how their gen AI applications have evolved. Here are a few observations: - No one talks about data security any more, presumably because they've become comfortable their queries are not being used for training by the AI companies. The system (at these more resourceful places) now seems to be to build an interface that can plug into the different closed-source models (ChatGPT, Claude) and also some open-sourced ones that can be fine-tuned internally.
- Boosting productivity of specific tasks like coding and extracting information from documents is still the main use. Some people wonder if gen AI ultimately has to be used for more complex tasks to justify its cost, but it seems at least the time savings are real and substantive.
- Some funds are exploring more sophisticated uses. Man Group's moonshot idea is to use it to search through research, generate a hypothesis and even test it all on its own.
- It's clear that anything more complex requires much more than typing a prompt into ChatGPT. Balyasny said that in order to get the AI to analyze a question like 'which stocks will be winners and losers from higher tariffs?', it had to first train it to break the topic down into sub-questions. (In computer science, this is called chain of thought.)
- Relatedly, in a lot of the cool use cases -- like one Balyasny showed me where the gen AI read an academic paper and backtested the strategy in it -- you're combining the GPT's mastery of natural language with other tools. For instance, in that case, the GPT itself can't actually conduct a backtest, so it was relying on a separate program coded by Balyasny.
- For quants, there is a particular use case: sentiment analysis, or finding systematic signals in text. The most cutting-edge firms have been doing that for ages, but as Two Sigma told me, you used to have to code a tool that looks for particular keywords or expressions. Now because large language models are able to parse context you can build the signal by just asking them, say, "Is this story about an executive departure?" That means they can test far more signals.
The upshot seems pretty positive. One thing I wondered throughout my reporting is whether these gen AI tools level the playing field; now sentiment analysis is no longer the preserve of a firm that can build out a natural-language processing team, for instance. But even putting aside the cost of using ChatGPT and the like, it seems that putting it to good use still requires a team of engineers. The important caveat to all that is that OpenAI says they're working on taking ChatGPT toward "human-level" problem-solving, so it might be that we all just need to wait for it to get there. Justina Lee is a cross-asset reporter based in London. Follow Bloomberg's Justina Lee on X @Justinaknope. | 
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