Unified framework for anomalies - all in the past month of return behavior

 

The daily return information factor (DRIF) is a new concept that helps explain many of the anomalies we see in financial markets. Instead of imposing or seeking a new risk premium, the authors of this paper, “A unified framework for anomalies based on daily returns”, examine the overall mapping of returns over the last month to make predictions about next month’s returns. The authors examine both the time ordering and the magnitude of returns to develop a forecasting framework.

A chronological vector preserves time ordering and captures short-term reversal dynamics, while a ranked vector accounts for magnitude effects. The DRI variable will combine these two vectors so that next month's returns are based on the beta of the time and magnitude vectors. A chronology dimension captures price pressure and liquidity effects, while ranking reflects investors' focus on extreme outcomes. These effects remain after controlling for other risk factors. 

Manufacturing employment and trend

 The US has talked about a resurgence in manufacturing, but the numbers do not suggest it is happening. Where is the surge? Construction, perhaps a small uptick after being flat. Manufacturing no change in trend. The same with mining and logging. Transportation has fallen off a cliff. Utilities are also below trend. Employment is always fighting productivity. We may be doing more with less, but workers are not seeing the improvement.  

China - the electrostate

This chart from Ember has me thinking about how to classify China. I am not thinking about the politics or the finance, but China as an innovative state. The future of geopolitical power is centered not on the military but on the ability to bend others’ lives through technology. This does not dismiss the political, but we have seen politics devoid of innovation and technology, and its scope is limited to coercion. Technology drives hegemony.

 

Is AI a stochastic parrot?

There’s a well-known phrase that AI is not true intelligence, but just a “stochastic parrot”. But human beings do quite a bit of parroting in conversation, as it turns out. So maybe the comparison is a little more complicated.

Six Questions on the Value of Humanities Research

A Podcast Interview with Chris Yeomans, Justin S. Morrill Dean of Liberal Arts, Purdue University

I found this phrase thought-provoking. We all parrot what we hear from others. Perhaps most of our conversations are parroting what we may have learned from someone else. AI is just a sophisticated parrot because it can search through more work than we can. AI, like us, does this with noise. It is a stochastic process. 

So what makes us or AI more than a parrot? The difference is what we can call creativity. It is rephrasing or making extensions or narratives that are not just a repeat of what we have heard before. The reordering of fact. The prioritizing of data is a part of the creative process. This is done by AI, so it is more than just parroting with noise. However, we should be aware that AI is creating something new through this reordering. If we ask the questions differently or use a different algorithm, we will create something different.