Are You Positioned? LFG Daily - December 15, 2025
- Luke Lloyd

- Dec 15, 2025
- 4 min read
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Two big things happened last week, and I think there wasn’t enough attention on the second thing. First, investors seemed to question the appropriate valuation of the AI trade, something I’ll talk about tomorrow.
Second, the Fed launched what’s popularly called ‘Not-QE,’ the buying of Treasury bills to expand their balance sheet and enhance liquidity.
I think ‘Not-QE’ matters, though I admit it doesn’t put us in a 2020 situation, where we had enormous federal support. Technically, by the way, the official program name is Reserve Management Operation Purchases (RMOP.) The plan is to inject $40B monthly into the Federal Reserve balance sheet through the purchase of Treasury bills. It’s overly simplistic (and may show off my poor understanding of cars,) but I think of QE like adding high-octane fuel, where Not-QE is more like adding oil to the car. The former is going to have a bigger effect, but the latter is still of good benefit.
Why is this happening?
The Fed saw there were problems in the repo market at the end of October (as I’m trying to show with the SOFR financing rate minus the rate on reserve balances, below) and this is an attempt to make sure the assets are available to keep normal functioning of markets. The first operation was on Friday, with $8.2B of T-bills bought.

Obviously, the market didn’t instantly soar on the purchase, so is this all much ado about nothing? Plenty will say so, but I disagree. Operations like this happened around Q4 2019, and 2023, with the first episode seeing stocks up about 10% and the second period (encompassing some of 2022 and 2024) saw about 50% gains. Obviously, a sample size of two isn’t a high-confidence statistical sample, and there were plenty of other things going on, but that looks encouraging.
Regardless, this move should stabilize liquidity and reduce funding stress, which in turn should help risk assets. Currently, the Fed said this move is temporary and set to expire in April. They’ve said that about many of these programs, though. They also are going to keep having this problem as money expands.
By the time tomorrow’s substack is out, Monday trading is likely to be over. Thus, I do want to say that there are people who are clearly concerned about the AI-trade. Once again, technical levels have been breached, and systematic sellers have cause to sell.
This could create selling in the space tomorrow, and for as long as those stocks go down and volatility goes up.However, given that the one troubled indicator, liquidity, is now set to improve, what’s the likelihood everyone runs away from AI now?
I admit that positioning was pretty heavy in the AI space, but that’s significantly less true now versus around the end of October. I can’t control what others do, but it’s easy for me to imagine some actors will end up taking this improved liquidity and jump into high-growth spaces.
Bottom line, the Fed adding to their balance sheet helps the most stressed part of the market, liquidity. The numbers involved aren’t huge, so this doesn’t have to make for a dramatic change and doesn’t mean we have to go straight up every day. It does, however, make me think this stock market has more upside potential than many think.

Trump said he’s leaning towards Warsh or Hassett to lead the Fed and the market thinks Hasset is most likely.
China said they want to expand exports and imports, next year.
FT says hedge funds are piling into commodities.
A WSJ story finds 68% of CEOs plan to increase AI spending despite less than half of current projects generating positive returns.
Stocks fell off on Friday given disappointment from AVGO. This meant OpenAI-centric stocks were sold off Thursday, while GOOG-centric stocks were sold off Friday. It’s not AI vs. AI, but the whole concept that’s been hit.
NY Empire State Manufacturing index today, and expectations are low. We also have two Fed speakers.
What does it all mean?
Futures are rebounding today, though without strong leadership, as markets recover from AI-losses.






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