1. U.S. Stock Market Concentration
From Irrelevant Investor Blog
https://www.theirrelevantinvestor.com/p/animal-spirits-the-leverage-mania
2. S&P 500 Forward P/E Back to 2021 High 22.5x
Equities: The forward P/E ratio climbed to 22.5x, indicating elevated valuations
Source: @TheTerminal, Bloomberg Finance L.P.
3. Short-Sellers Capitulate
Bloomberg-By Michael Msika
4. S&P 500’s December After +25% Through November
5. AI Enters the Oil Market
Barrons
Oil companies are on a relentless quest to produce more oil at lower costs, and AI is boosting that effort. Their success has already been remarkable. Over the past decade, the U.S. pumped out 60% more oil a day with 40% fewer workers. The industry’s annual productivity gains in that stretch outpaced even those of online retailers, and are roughly seven times as large as those of the average U.S. business. By extracting more oil while reducing capital expenses and manpower, they’re lowering the costs at which they can drill profitably. In the Permian, the “break-even” price for oil producers has fallen to $40 a barrel from over $90 in 2012, according to S&P Global Commodity Insights. AI should take that number even lower, boosting oil company margins and cash flow.
https://www.barrons.com/articles/ai-oil-industry-profit-permian-basin-8adcacdd?mod=past_editions
6. Banks at Historical Lows Still vs. S&P
State Street
7. Canada Exports to U.S.
Dave Lutz Jones Trading
Canadian Prime Minister Justin Trudeau promised President-elect Donald Trump that Canada would toughen controls over the long undefended joint border, a senior Canadian official said on Sunday. Trudeau flew to Florida on Friday to have dinner with Trump, who has promised to slap tariffs on Canadian imports unless Ottawa prevents migrants and drugs from crossing the frontier. Canada sends 75% of all goods and services exports to the United States and tariffs would badly hurt the economy.
8. The Ethereum-Bitcoin Ratio
Yahoo Finance Bram Berkowitz, The Motley Fool
Given their history and the fact that cryptocurrencies can be hard to value because they have no intrinsic value, many investors have looked for trends between the prices of Ethereum and Bitcoin. After all, groups of stocks are often compared to one another to determine relative valuation. A simple way to track Bitcoin and Ethereum is by looking at the relationship between Ethereum’s and Bitcoin’s prices by dividing the price of Ethereum by the price of Bitcoin. Seeing where this ratio has trended over time can offer clues as to which looks undervalued or overvalued relative to the other.
Data source: TradingView. Chart by author.
As you can see in the chart, the Ethereum-Bitcoin ratio recently fell toward 0.035, the lowest level seen since April 2021. The average ratio dating back to 2020 is 0.0538. Ethereum has performed well since Election Day, up roughly 38% compared to Bitcoin’s 44%. However, Bitcoin has widely outperformed this year.
https://www.yahoo.com/finance/news/bitcoin-ethereums-relationship-doing-something-103000709.html
9. Expensive Zip Codes
NY Times By Josh Ocampo
https://www.nytimes.com/2024/11/28/realestate/most-expensive-zip-codes.html
10. AI Predicts Neuroscience Study Results Better Than Experts
Psychology Today LLMs beat human neuroscience experts in predicting study outcomes.
The results were clear—each LLM (Large Language Model) beat human neuroscience experts by a wide margin. The LLMs average accuracy of 81.4 percent far exceeded the 63.4 percent average of human experts.
Next, the scientists created a new LLM called BrainGPT by fine-tuning an existing version of Mistral and training data from twenty years of neuroscience publications from a hundred journals published during 2002-2022. BrainGPT had an 86 percent accuracy in predicting neuroscience study results, which was a three percent gain from the general-purpose version of Mistral.
“LLMs can be part of larger systems that assist researchers in determining the best experiment to conduct next,” the researchers wrote.
The ability to predict results of neuroscience research in advance can help guide neuroscientists to optimize limited resources such as time and money, enable timely adjustments based on probable outcomes, and augment our understanding of the brain and central nervous system that may lead to better treatments and health interventions.
This proof of concept is not limited to neuroscience. According to the scientists, none of their methods used was specific just to neuroscience and can be applied more broadly to other knowledge-intensive domains in the future.
“LLM’s impressive forward-looking capabilities suggest a future in which LLMs help scientists make discoveries,” the researchers concluded.
Copyright © 2024 Cami Rosso About the Author