ChatGPT — Alpha.Sources — Alpha Sources.CV

The BIS gets it wrong on AI/LLM and feminism & reproduction

The BIS has a Bulletin out on the usefulness of AI and large language models. They’re not terribly impressed.

When posed with a logical puzzle that demands reasoning about the knowledge of others and about counterfactuals, large language models (LLMs) display a distinctive and revealing pattern of failure. 
The LLM performs flawlessly when presented with the original wording of the puzzle available on the internet but performs poorly when incidental details are changed, suggestive of a lack of true understanding of the underlying logic. 
Our findings do not detract from the considerable progress in central bank applications of machine learning to data management, macro analysis and regulation/supervision. They do, however, suggest that caution should be exercised in deploying LLMs in contexts that demand rigorous reasoning in economic analysis.

Demographics, Global Economy, Politics and societyclaus vistesenJanuary 14, 2024feminism, AI, BIS, ChatGPT, OpenAI, the Nation, Moira Donegan

Stock market signals with Chat GPT 4

This is my third use case for how to do quantitative analysis with Chat GPT 4. The two others, on Eurozone inflation and times series regression with macro data, can be found here and here. I started in the industry as Head of Research for Variant Perception, a research shop that specialises, among other things, in quantitative trading models, asset allocation tools, and trade signalling analysis. One tool that came up again and again in my analyses was binary signals to identify turning points in asset classes, stocks or economic data series. The idea is simple. First, you create a binary indicator which takes the value of 1, if a certain threshold in the data is breached to the upside or downside, and zero otherwise. Secondly, you investigate what happens after such a signal has gone off, either in the original data set or mapped to a separate data set. You can combine signals across datasets to get a rolling series of signals, which can be compared to asset prices or economic data. You can see an example of such an analysis with the Nasdaq here.

Markets and Tradingclaus vistesenDecember 31, 2023ChatGPT, Microsoft, stock market, stock price signals, AI

Time Series Regression Analysis with Chat GPT4

The following chart is one of hundreds that I use in my day-job as Chief Eurozone Economist at Pantheon Macroeconomics. It plots a normalised Z-score index of surveyed new manufacturing orders in Germany alongside year-over-year growth in factory orders, ex-major orders. It’s worthwhile spelling out the meaning of this chart in the world of economic research and forecasting. The factory orders numbers are so-called hard data, which in this case means that they’re official numbers of real activity reported by the statistical office. The PM new orders index, by contrast, is my home-cooked index of so-called soft data. Specifically, these are survey data, compiled by the likes of the EU Commission, IFO, S&P, and national statistical offices. We’re only interested in these numbers to the extent that they tell us something about the official/hard new orders data, which in turn could help us pin down trends in industrial production, exports, GDP growth, employment and so on. From simply eye-balling the chart, the two series look coincident, but note that the surveys are released ahead of the official data, so that we always have survey numbers that are one-to-two months ahead of the official data. In other words, when it comes time to forecast new orders for the month of December, we will already have survey data for that month. This should, in theory, help us to better forecast the official real new orders data.

Policy talk is cheap & we need more power

Monetary policymakers have been scrambling in the past week to push back against the dramatic shift in market expectations for rate cuts next year. This is true for Fed officials—despite the clear dovish pivot in the December meeting—and particularly so for the ECB, where Ms. Lagarde and her colleagues have been hard at work to disabuse investors of the notion that the central bank will start cutting rates in the first half of next year. Are central banks right to lean into the prevailing market winds here? It’s all in the eye of the beholder. The chart below plots futures-implied policy rates for the Fed and ECB through 2027. The focus at the moment is on 2024, where markets see 150bp and 120bp worth of cuts from the Fed and ECB, respectively. That sounds like a lot, but then again, inflation is now falling rapidly. The question we need to ask is whether markets will be fed information over the next few months that will drive a shift in pricing. I am not sure, and if they aren’t, talk from policymakers will be cheap.

02

Alpha Sources Blog