I’ve been thinking about time recently. In economics and finance, time is central to our analysis. Most of the information we care about, after all, is spread and dispersed across time. As a result, the way we embed our models with information, and how we sort and organize that information, is often a question of time. The information embedded in time is powerful, often overwhelming.
Read MoreDani Rodrik is disappointed with the way the world is responding to Mr. Trump’s wrecking-ball foreign and economic policy. Professor Rodrik opens with the argument that Trump’s policies are “misguided, erratic, and self-defeating,” lamenting that the rest of the world is only feebly resisting—failing to recognize that “imperialism must always be challenged – not accommodated – and that [this] requires both power and purpose.”
Read MoreAdam Butler, head of ReSolve Asset Management, makes an interesting observation on AI in the wake of the publicised roll-out of ChatGPT 5. In effect, he argues that the AI cycle is over, for now.
Read MoreThe problem isn’t that the models stopped improving. It’s that the improvements we need are measured in orders of magnitude, not percentage points. Every step up the scaling laws now demands a city’s worth of electricity and a sovereign wealth fund’s worth of GPUs. You can still squeeze clever tricks out of mixture-of-experts or chain tiny specialists into something that looks like agency; that keeps the demo videos cinematic. It just doesn’t get us to super-intelligence. For that we need either an architectural miracle (unforecastable by definition) or a civil-engineering miracle (a decade-long sprint to build nuclear plants and 2-nanometer fabs). The first is luck. The second is politics. Both are scarce.
I’ve been sitting on this project for a while, but I’m finally ready to bring it above the fold. I’ve long wanted a straightforward overview of global debt levels—both public and private—and an easy way to compare them across countries, alongside their respective external dynamics. This is essential material for macro investors and researchers, yet it’s rare to find all the relevant information compiled in one place. The AS global debt chartbook is a first attempt at this. Like the LEI Chartbook, this project runs on Python code generated and compiled with the help of my trusty OpenAI assistant, with a few manual adjustments along the way. At the moment, it draws data from an Excel spreadsheet, but integrating APIs should be relatively straightforward down the line.
Read More