As we start the year of the 2024 American federal elections, there is significant uncertainty. One thing though is virtually certain: the year will be much more volatile than what is currently being priced into the Capital Markets.

There are considerable geopolitical issues, at least one of which is likely to shift economic outlooks. Wars are currently raging in Ukraine and Gaza with other tensions in the areas around the Red and South China Seas. These conflicts will require economic and political resources, both of which seem to be in more limited supply today than earlier.

As the day starts on this Thursday, the 10-year TSY and 30-year TSY yields are at 4.97% and 5.08% respectively. If these yields also are where these benchmark securities close this afternoon, they would represent yet another closing high yield level since 2007.

October 4th 2023 has already been a crazy day in the global capital markets. As Brass Rat Capital ("BRC") wrote in the 2023-09-04 WILT post, this FinTech skunkworks sensed the American economy and capital markets were about to go through some volatile and relatively negative times.

A very high percentage of the contacts in the Brass Rat Capital ("BRC") electronic Rolodex appear to use Google's Gmail service. BRC (or its predecessors) has done so for more than a dozen years. If you use the Google ecosystem, including contacts, Gmail, Docs, YouTube, and Maps, PLEASE, PLEASE refrain from using the new Google AI chatbot that allows it to act as a personal assistant. The same goes for the OpenAI, Microsoft, and Meta chatbots that supposedly can access both your personal information and web searches. DO NOT USE these AI Assistants yet.

If one is a capital markets participant, surely one recalls the 1979 Saturday Night Massacre. Correct? Most will not since many were not yet even born. Brass Rat Capital suggests that one pause now to conduct a deeper dive to understand the "Nifty Fifty" period and what happened during the 1973 and 1979 oil shocks that resulted in the October 1979 Saturday Night Massacre and ultimately doomed the Jimmy Carter Presidency. Does one appreciate the horrific gloom during the period that the actor Ronald Reagan started his Presidency?

This last week of September increasingly appears to be a turning point in the American capital markets. As Brass Rat Capital ("BRC") wrote about recently, longer-term interest rates are now rising. The equity market is breaking down in a technical sense. Prices in the energy sector are strongly increasing, and the U.S. Dollar is amazingly strong.

Perhaps the most major problem with Large Language Models ("LLMs") and hence generative AI is when the model(s) generate factually incorrect text. The Gen AI now refers to this phenomenon as producing "hallucinations." As a result, a key AI research area has become "explainability." In short, how does a human being understand how the model came up with "that" result?

The equity markets have not correlated with the fixed-income markets for most of the year. Energy has recently broken out to higher prices and the consumer confidence numbers are beginning to turn down.

Wow is the Bloomberg Surveillance program negative this morning. This correlates well with what Brass Rat Capital wrote about this weekend. The desire for a "higher for longer" Fed Funds rate seems to be permeating the thinking of many market participants.

The 10-year TSY yield hit 4.50% this past week -- its highest level since 2007. There is considerable talk about this being a good level to extend duration since the real yield is near 2 percent.

Lars Toomre would caution that the American economy is not yet in restrictive territory -- yet!! The 4.50 yield level is only the long-term 100-year average. Markets almost never correct from an excess just back to the average. They almost always go to the point that hurts the most participants the most.

Multi-AI collaboration sounds like a mouthful of gobbly gook. However, this approach makes much sense to refine the reasoning abilities of Large Language Models ("LLMs"), and sharply reduce hallucinations, potential inaccuracies, and flawed reasoning.

Assuming the LLMs are truly independent, the strategy to discuss and effectively argue with one another allows the agents for each LLM to converge on a best possible answer to a given query.